BLOOD-MEAL HOST SELECTION, MALARIA INFECTION, AND GENOTYPING TO DELINEATE HUMAN TO MOSQUITO PLASMODIUM TRANSMISSION: IMPLICATION FOR MALARIA PARASITE INFECTIONS IN MALAWI By Rex Barnett Marregah Mbewe A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Entomology —Doctor of Philosophy 2021 ABSTRACT BLOOD-MEAL HOST SELECTION, MALARIA INFECTION, AND GENOTYPING TO DELINEATE HUMAN TO MOSQUITO PLASMODIUM TRANSMISSION: IMPLICATION FOR MALARIA PARASITE INFECTIONS IN MALAWI By Rex Barnett Marregah Mbewe Malaria is endemic in Malawi with continuing transmission and high rates of infection in the human population, despite ongoing interventions by the national malaria control program. The two main malaria control interventions in Malawi are long-lasting insecticidal treated nets (LLINs) and indoor residual spraying (IRS). The research described in this dissertation investigated Anopheles vector blood host selection among vertebrate hosts and within the human population, and from these investigations inferred pathways of malaria transmission from human to mosquito populations. The primary hypothesis was that biases in mosquito human feeding could drive malaria infection transmission. The study setting was two districts in southeastern Malawi. One district, Balaka, had conventional LLINs, those containing pyrethroid insecticide only; and the other, Machinga, had LLINs containing pyrethroids and the synergist piperonyl butoxide (PBO). Adult female Anopheles mosquitoes were sampled indoors in rural villages by CDC light traps, Pyrethrum spray catches and aspiration. Human demographic data and blood spots on filter paper by finger prick were collected from consented participants. Anopheles mosquito species were identified by morphological and molecular methods. Mosquito blood meal sources and Plasmodium falciparum infection in abdomen or head-thorax of mosquitoes were determined by qPCR with host-specific oligonucleotide probes and parasite specific probes, respectively. Blood meals from humans and human blood spots were analyzed by genotyping 24 microsatellite loci, to generate genetic profiles that were matched one to the other, and between blood meals and blood spots, using an algorithm executed in RStudio (Version 1.1.456). The results showed similar mosquito species community composition of the three main malaria vectors (An. arabiensis, An. gambiae, An. funestus), but different in abundance, with substantial malaria infection rates (ranging from 14-36%) in the mosquitoes at both sites. Potential secondary malaria vector mosquito species were present. Most mosquitoes fed upon humans (81%) and relatively less upon dogs (2%) and goats (5.2%). There were strong biases in human host selection, with a highly nonrandom and aggregated distribution of blood meals, with few individuals contributing most of the blood meals and most individuals contributing few. In human blood meals, males of the age group 6-15 were the most malaria infected group compared to younger and older age groups, and individuals of this group contributed most of the blood meals. These results incriminate males of age 6-15 as drivers of malaria infection from human to mosquitoes. The district with LLINs containing PBO had a lower Human Blood Index (HBI) and Entomological Inoculation Rate (EIR) compared to the district with conventional LLINs. Mixed blood meals of human and non-human hosts suggest interrupted feeding and the adaptability of the mosquitoes to switch amongst host species, possibly circumventing malaria control interventions. Malaria transmission was well sustained despite implementation of LLINs containing synergist PBO or not. Likely, other factors such as net durability and efficacy may be reducing effectiveness of the LLIN program and need further investigation. Continued efforts in malaria control and prevention should include deliberate efforts focused on key demographic population groups, such males of 6-15 years old, which while not the most vulnerable population to malaria, are reservoirs of infection. This dissertation is dedicated to my precious wife Angela and our two gorgeous daughters Rexilina and Rexangel. They all have been a great pillar of support to me in this arduous academic journey, enduring the unrelenting COVID-19 pandemic, Michigan cold winters, and my absence on some of our family activities. However, we had fun all the way, making new friends, visiting places, enjoying the four seasons and of course taking lots of pictures. iv ACKNOWLEDGEMENTS I would like to acknowledge the following individuals and organizations below for their contribution to the success of the research described in this dissertation and my PhD program. First and foremost, my deepest gratitude goes to Dr. Edward Walker, Professor of Microbiology, Molecular Genetics and Entomology at Michigan State University (MSU), for accepting me into his laboratory, being my academic advisor and for supporting me in various ways throughout my graduate program. His scientific guidance, wisdom, sense of humor and mentorship were instrumental to my academic and research achievements. Ned, you will always be remembered with fondness for having a great impact in shaping my life. Secondly, I would also like to acknowledge the MSU faculty who served on my guidance committee Dr. Eric Benbow, Dr. Jean Tsao, Dr. Jennifer Owen, Dr. Ke dong (past), Dr. Barry Pittendrigh (past) and Dr. Lauren Cohee from University of Maryland. I thank you all for your guidance and oversight on my research project and academic training. Special thanks also should go to Dr. John Keven who trained me in molecular laboratory and forensic techniques that were relevant to my research. John was an advance graduate student in the lab and finished a year before me. John, we worked together as brothers and I learnt a lot from you. Please continue helping others who may cross your path as I did and help them to shine. May you continue to rise in your profession, and I wish you all the best. My research project was supported through collaborative efforts between Dr. Walker’s laboratory at MSU and International Center for Malaria Research (ICEMR) Malawi under Malaria Alert Center (MAC-CDAC). I would like to thank all member of staff in these two organizations who helped in my project starting from field workers doing data collection and management dealing with my financial support. Special v appreciation also goes to Dr. Don Mathanga (MAC), Dr. Terrie Taylor (ICEMR, MSU), and Dr. Mirriam Laufer (University of Maryland) and all staff for all their administrative support during my training. Last but not least, special recognition to management and staff of my employer Polytechnic, University of Malawi, soon to be Malawi University of Business and Applied Sciences (MUBAS), for allowing me to go on study leave and giving me support in a variety of ways when I needed it. Finally, I would like to give a very special thanks to my parents for making me believe in my intellectual capabilities, for their words of wisdom and encouragement, and for getting me on the path to arrive at this highly unlikely stage of my life, and to my family, Angela my wife, our daughters Rexilina and Rexangel for their company, emotional support in a foreign country and making this experience enjoyable all the way to my graduation, I could not trade that for anything. Your great sacrifices will only be repaid by our loving father Jehovah. vi TABLE OF CONTENTS LIST OF TABLES………………………………………………………………………………...x LIST OF FIGURES………………………………………………………………………………xi KEY TO ABBREVIATIONS………………………………………………………………......xiii CHAPTER 1 : INTRODUCTION .................................................................................................. 1 1.1. Background .............................................................................................................................. 1 1.2. Plasmodium life cycle .............................................................................................................. 2 1.3. Clinical disease ........................................................................................................................ 3 1.4. Significance of Anopheles mosquitoes .................................................................................... 5 1.5. Vectorial capacity .................................................................................................................... 6 1.6. Mosquito vectors and epidemiology ........................................................................................ 7 1.7. Malaria situation in Malawi ..................................................................................................... 8 1.7.1. Description and map of Malawi…………………………………………………………8 1.7.2. Malaria vector control……..…….………………………………..……………………11 1.8. Research significance and objective ...................................................................................... 15 1.8.1. Significance...………………………………………………………………………..…15 1.8.2. Objective ........................................................................................................................ 16 1.9. Research ethical approval ...................................................................................................... 17 APPENDIX ……………………………………………………………………………………...19 CHAPTER 2 : MOSQUITO COMPOSITION, ABUNDANCE AND DISTRIBUTION IN RELATION TO PLASMODIUM INFECTION TRANSMISSION IN ANOPHELES MOSQUITO SPECIES REVEALS PRESENCE OF POTENTIAL SECONDARY MALARIA VECTORS IN SOUTHEASTERN MALAWI ...................................................................... …..……………….20 2.1. Abstract ................................................................................................................................ ..20 2.2. Introduction… ...................................................................................................................... ..22 2.3. Methods.......................................................................................................................... ……24 2.3.1. Study sites.....…….……………….………...…………………………………………..24 2.3.2. Description of study areas…………………………...………………………………….25 2.3.3. Study design……...………….…………………………………………………………26 2.3.4. Sample collection and processing……..……………………………………………….26 2.3.5. Data analysis……..………………………...………………………………...………....30 2.4. Results……………………………………………………………………………………….31 2.4.1. Mosquito species composition, distribution and abundance………………….……......31 2.4.2. Mosquito processed in head-thorax, for blood fed status and species abundance…….33 2.4.3. Plasmodium falciparum infection status per body part of blood fed and unfed mosquitoes combine…………..…...………………………………………………………………………….34 2.4.4. Mosquito blood-fed status and Plasmodium falciparum infection per body part…….35 2.4.5. Mosquito species abundance and Plasmodium falciparum infection of blood fed mosquitoes analyzed in the abdomen section ............................................................................... 36 vii 2.4.6. Plasmodium falciparum infection of blood fed Anopheles species……….…………….38 2.5. Discussion .............................................................................................................................. 41 2.6. Conclusion ............................................................................................................................. 46 APPENDIX ................................................................................................................................... 47 CHAPTER 3 : BLOOD MEAL SOURCES OF ANOPHELES VECTORS OF HUMAN MALARIA IN MALAWI: IMPLICATIONS FOR MALARIA TRANSMISSION AND EFFECTIVENESS OF INTERVENTIONS……………………………………………………..52 3.1. Abstract .................................................................................................................................. 52 3.2. Introduction ............................................................................................................................ 54 3.3. Methodology .......................................................................................................................... 56 3.3.1. Study area…...………...………………………………..……………………………....56 3.3.2. Mosquito sampling and analysis……………....………………………………………..57 3.3.3. PCR identification of mosquitoes…...………………………………………...………..57 3.3.4. Blood meal analysis…...………………………………..…………………………...….58 3.3.5. Molecular identification of Plasmodium falciparum…………..…………………….…60 3.3.6. Data analysis....……………………………………………………………………...….61 3.4. Results……..… ..................................................................................................................... .63 3.4.1... Species composition…………………………………...……………………………..63 3.4.2. Host selection and human blood index (HBI)…….……………………………..……...63 3.4.3. Entomological inoculation rate (EIR)…………………………………………………..67 3.5. Discussion ............................................................................................................................ ..68 3.6. Conclusion ........................................................................................................................... ..74 CHAPTER 4 : GENOTYPING OF ANOPHELES MOSQUITO BLOOD MEALS REVEALS NONRANDOM HUMAN HOST SELECTION: IMPLICATIONS FOR PLASMODIUM FALCIPARUM TRANSMISSION, MALAWI ............................................................................ 75 4.1. Abstract .................................................................................................................................. 75 4.2. Introduction ............................................................................................................................ 77 4.3. Methods.................................................................................................................................. 80 4.3.1... Study site………...…………………………………………………………….……..80 4.3.2... Sample collection and processing…..………………………………………………...80 4.3.3. .. Microsatellite genotyping and profile matching……………………………………...82 4.3.4. Data analysis…...…………………………………….…………………………………83 4.4. Results ................................................................................................................................ …85 4.4.1. Human genetic profiling…...………….………………………………………………..85 4.4.2. Genotyping human blood meals……...…..………….....................................................87 4.4.3. Frequency distribution of human blood meals.…...…………………………………….87 4.4.4. Mosquito human host selection by sex and age category…...…………………………..89 4.4.5. Plasmodium falciparum infection in mosquito blood meals and the human population..91 4.5. Discussion ............................................................................................................................ ..94 4.6. Conclusion ........................................................................................................................... 102 APPENDICES ............................................................................................................................ 103 APPENDIX 4.1. OUTPUT OF ALLELIC SIZE VISUALIZATION. ....................................... 104 APPENDIX 4.2. EXAMPLE OF GENETIC PROFILES GENERATED FROM SAMPLES...105 viii CHAPTER 5 : GENERAL CONCLUSION ............................................................................... 107 APPENDIX ................................................................................................................................. 110 REFERENCES ........................................................................................................................... 112 ix LIST OF TABLES Table 2.1. Anopheles mosquito species abundance and distribution per site based on molecular identification……………………………………………………………………………………..32 Table 2.2. Blood-fed status of Anopheles mosquitoes processed in the head-thorax section..........34 Table 2.3. Number of Plasmodium falciparum infected mosquitoes per body section…………..34 Table 2.4. Mosquito blood-fed status and Plasmodium falciparum infection per body part and study site...………………………………………………………………………………………..35 Table 2.5. Anopheles species Plasmodium falciparum infection proportion per body part and study site………………………………………………………………………………………………..36 Table 2.6. Number of mosquitoes showing distribution and abundance of blood fed mosquitoes analyzed in the abdomen section (n (%)………………………………………………………….37 Table 2.7. Total number of Anopheles mosquitoes collected per month of sampling in 2019 and 2020 in the two sites……………………………………………………………………………...48 Table 2.8. Blood fed and unfed Anopheles mosquitoes sampled in 2019 and 2020 showing month of sampling and numbers per site………………………………………………………………....50 Table 3.1. Blood meal host primers and probes used in the qPCR reactions………………...……60 Table 3.2. Blood meal sources identified from Anopheles mosquitoes of Namanolo and Ntaja.…65 Table 3.3. Percent deviation of observed blood meal frequencies from those expected by chi-square analysis, two sites combined……………………………………………………………………..65 Table 4.1. Pairwise testing, percent match and probability of having similar genetic makeup…....86 Table 4.2. Example of profiles generated from human blood spot samples…………..…………105 Table 4.3. Example of profiles generated from mosquito blood meal samples…..…...…………106 x LIST OF FIGURES Figure 1.1. Malaria parasite life cycle……………………………………………………………...3 Figure 1.2. Map of Malawi showing the study sites by district…………………………………...10 Figure 1.3. Conceptual framework…..…………………………………………………………...19 Figure 2.1. Map of Malawi showing the study sites………………………………………............25 Figure 2.2. Anopheles mosquito species abundance and composition per site. Abundance calculated as mean number of mosquitoes per household with their standard errors……………..32 Figure 2.3. Anopheles mosquito species proportions detected by COI gene bar coding from a subset of the non- PCR detected samples indicating presence of other Anopheles species……………....33 Figure 2.4. Composition, abundance, and distribution of mosquitoes from blood fed abdominal sections only, per site expressed as a proportion………………………………………………….37 Figure 2.5. Blood fed mosquitoe Plasmodium falciparum (Pf) infection status in head-thorax and abdomen section expressed as proportion. Positive infection rate ranging from 13 to 31%............38 Figure 2.6. Mosquito Plasmodium falciparum infection proportion across the five Anopheles species in head-thorax vs. abdomen in Namanolo and Ntaja…………………………………..…40 Figure 2.7. Number of mosquitoes collected per month of sampling….….…………………......49 Figure 2.8. Number of blood-fed mosquitoes collected and month of sampling per site………….51 Figure 3.1. Map of Africa showing the study sites in Namanolo and Ntaja in Malawi…………....56 Figure 3.2. Blood meal identification to vertebrate host, including mixed meals, for Anopheles mosquitoes two sites combined…………………………………………………………………..64 Figure 3.3. Anopheles species blood meal host selection in relation to number of available hosts. Top panels; goat selection in relation to human, bottom panel; human selection in relation to goats. The black shaded circles are theta values with 95% CI bars. Red dotted line at 1.0 represents random selection in relation to availability of both hosts. The 95% CI bars represent deviation from random selection pointing to over-selection (theta significantly > 1.0) or under-selection (theta significantly < 1.0)…………………………………………………………………………66 Figure 4.1. Frequency distribution of number of blood meals on individual male and female humans taken by Anopheles mosquitoes sampled in Ntaja and Namanolo communities of southeastern Malawi……………………………………………………………………………...88 xi Figure 4.2. Fits of the frequency distribution of number of human blood meals taken per person from Anopheles mosquitoes sampled in houses using all data (Insert: distributions in Ntaja and Namanolo showing similar trend) in communities, southeastern Malawi…………………….….89 Figure 4.3. Proportion of Anopheles blood meals (red) taken from males and females humans compared to the proportion of the two human sexes in the household survey (blue). Results of Chi- square tests comparing the proportion of males and females in the blood meals to their proportion in the household survey, and of male versus female blood meals are shown inside the plot. Note, data from both sites (Namanolo and Ntaja) were combined in this analysis…………………..…..90 Figure 4.4. (a) Comparisons of the proportion of blood meals taken from humans in three age groups in relationship to the number of humans in those age groups as determined by household survey. (b) Comparison of the proportion of blood meals taken from the three human age groups along with Chi-square results of test of homogeneity of blood-meal proportion. Data from both sites (Namanolo and Ntaja) were combined in this analysis……………………………………...91 Figure 4.5. Proportion of abdomens and head-thorax of Anopheles mosquitoes positive for P. falciparum classified by whether the sex of the human host in the blood meal was male or female. (b) Proportion of human blood spot samples positive for P. falciparum classified by sex of the human source of the blood. Chi-square tests of homogeneity of proportion of infections between the two sexes are shown in the plots. Data from both sites (Namanolo and Ntaja) were combined in this analysis……………………………………………………………………………………92 Figure 4.6. The proportion of Anopheles mosquito abdomens and head-thorax body sections in relation to human blood samples positive for P. falciparum for all samples regardless of human genotype, classified by male or female. Namanolo and Ntaja communities, southeastern Malawi.92 Figure 4.7. Comparisons of the proportion of Anopheles mosquito body part (abdomen with blood; head-thorax) positive for P. falciparum classified by age category and compared to the proportion of the human population positive by age category. (b) Comparisons of the proportion of Anopheles mosquito body part (abdomen with blood; head-thorax) positive for P. falciparum classified by human age group of the genotyped blood meal…………………………………………………...93 Figure 4.8. Proposed model of flow of blood meals and P. falciparum infection between human and mosquito populations. Age 6-15 as reservoir and contributors of P. falciparum to mosquitoes…………………………………………………………………………………….. .101 Figure 4.7. Example of output for visualization of allelic sizes on each loci for creating genetic profiles of each individual sample………………………………………………………………104 xii KEY TO ABBREVIATIONS ACT – Artemisinin-based combination therapy BLAST– Basic Local Alignment Search Tool CDC – Centre for Disease Control CI– Confidence interval COMREC – College of Medicine Research Ethics Committee DNA – Deoxyribose nucleic acid EIR – Entomological Inoculation rate HBI- Human blood index ICEMR- International Centers of Excellence for Malaria Research ID – index of dispersion IRB – Institution Review Board IRS – Indoor Residual Spray LLIN – Long-lasting insecticidal net MSU – Michigan State University MSU IRB – Michigan State University Institutional Review Board NIH – National Institutes of Health NSO – National Statistics Office PBO – Piperonyl butoxide PCR – Polymerase Chain Reaction PSCs – Pyrethroid spray catches Ro – Basic reproductive number xiii VC – Vectorial Capacity WHO – World Health Organization xiv CHAPTER 1 : INTRODUCTION 1.1. Background Malaria continues to be a major contributor to worldwide disease burden, linking to poverty and impeding social development. Malaria control efforts have increased tremendously in the past two decades, culminating in appreciable and measurable declines in global burden of the disease (Chanda et al., 2015; Cibulskis et al., 2016; WHO, 2014, 2021b). In 2010, the World Health Organization ranked malaria as the eighth-highest contributor to the global disease burden and was the leading cause of premature death and disability in sub-Saharan Africa (Http://Www.Healthdata.Org, 2013). By the year 2020, Malaria cases and deaths had decreased from 216 million and 655,000 in 2010 to 215 million and 386 000 in 2019 respectively (WHO, 2021b). Human malaria is caused by sporozoan protists of the genus Plasmodium, family Plasmodiidae (Order Haemosporidida, Class Haemosporidea, Phylum Sporozoa) that infect blood tissues and other organs of the body, primarily the liver. These organisms are transmitted from person to person by female Anopheles mosquito bites. They are called human malarias because they are naturally known to cause disease in infected humans and not in other mammalian, avian or reptilian hosts (Antinori et al., 2012; H. Gillies, 1993; Schlagenhauf, 2004). These human malaria protozoans are obligate intracellular parasites. There are four species of solely human malaria: P. falciparum, causing malignant tertian malaria; P. vivax, causing benign tertian malaria; P. malariae, causing quartan malaria; and P. ovale tertian malaria. The first two species are widespread in the tropics, but P. vivax also occurs in some temperate areas. Interestingly, P. vivax is noticeably absent in much of sub-Saharan Africa due to the absence of a gene encoding a 1 receptor protein (the so-called Duffy negative phenotype) that facilitates infection of red blood cells. P. malariae also is distributed widely in endemic regions of the world, but in low prevalence. P. ovale is rare, occurring mainly in Africa. Recently, a fifth species of Plasmodium that causes quotidian malaria, P. knowlesi, has been discovered to be relatively common in the human population of some countries of Southeast Asia (28-84% of malaria cases in Malaysian Borneo). This species had been known to occur almost exclusively in monkeys, with only occasional human infections (Foster and Walker, 2009 in Mullen & Durden, 2009). Malaria currently occurs in sub- Saharan Africa, parts of northern Africa, the Middle East, Southeast Asia, Latin America, Central America and South America (Lysenko & Semashko, 1968;Chima et al., 2003; Hay et al., 2004; Guerra et al., 2006; Feachem et al., 2010; Sinka et al., 2012; Griffin et al., 2014; WHO, 2021a). A variety of factors determine the degree of endemicity, typically measured as prevalence of infection of humans by the various species of Plasmodium present. These factors include environmental and social as well as species of vectors. Literature abounds on human malaria and its vectors. Among comprehensive sources are Boyd (1949), Macdonald (1957), Molineaux & Gramiccia (1980), Wernsdorfer & McGregor (1988) and Warrell & Gilles (2017). 1.2. Plasmodium life cycle The life cycle of Plasmodium species is complex involving both sexual and asexual reproduction and depends on both humans and mosquitoes (Figure 1.1). In the mosquito, the malarial parasite (Plasmodium spp.) develops an exogenous sexual phase (sporogony cycle). When the sporozoites have developed, they make their way to the mosquito salivary glands, from which they are transmitted to humans via the mosquito bite. The parasites develop in an asexual cycle within the human host through a series of nuclear division which increases parasite density and eventual 2 production of gametocytes (gametogony). An infective mosquito is a prerequisite for malaria transmission. It takes between 8 and 35 days to complete the parasite’s life cycle in the mosquito host, depending on the environmental conditions and the species of malaria parasites (Ndoen et al., 2012). Figure 1.1. Malaria parasite life cycle. Source: https://www.cdc.gov/malaria/about/biology 1.3. Clinical disease Malaria is characterized by a syndrome of symptoms signaled by sudden episodes of fever and rigor-like chills (known collectively as a paroxysm) that recur at highly predictable intervals (Warrell & Gilles, 2017). Other acute symptoms include headache, lethargy, fatigue, and profuse sweating after each bout of fever. Episodes of chills and fever are triggered by parasite-mediated events in the circulatory system. After erythrocytes are infected by merozoites, erythrocytic 3 merogony leads to the synchronous rupture of the erythrocytes and release of new merozoites, toxins, and heme digestion products causing chills and fevers. The next episode occurs in 24, 48, or 72 hours, depending upon the species of Plasmodium. From these cyclic episodes come the terms quotidian (daily), tertian (every two days, or days 1 and 3), and quartan (or every four days, or days 1 and 4) (Mullen & Durden, 2009). Malarial infections in humans can range in outcome from asymptomatic infection to chronic infection with anemia, to acutely severe illness and sometimes death. These various outcomes are related to age of the human host, sex (as malaria in pregnancy can lead to maternal anemia, preterm delivery, and low birthweight), immune status, and genetic factors related to race. However, the particular symptoms, including timing and severity, vary with the species of Plasmodium. The most severe form of malaria (malignant tertian malaria) is caused by P. falciparum, in which merozoites invade both young and old red blood cells. Repeated reinvasions and mass destruction of red blood cells over time may lead to high parasitemia, severe anemia, and anoxia of tissues. In falciparum malaria, infected red blood cells stick to the vascular epithelium of capillaries in organs including the brain, impeding blood flow and causing a serious and sometimes lethal end-organ damage including cerebral malaria (Desai et al., 2007; Mullen & Durden, 2009; Idro et al., 2010; Postels & Birbeck, 2013). P. vivax malaria is called benign tertian malaria because symptoms are less severe than P. falciparum malaria, and death rarely occurs. Thus, unlike falciparum malaria, vivax malaria has fewer severe symptoms of anemia and toxemia, making death unlikely. The infected red blood cells do not stick to the epithelial lining of capillaries as they do in falciparum malaria. Vivax malaria can evolve into chronic infection with development of an enlarged spleen, or splenomegaly. This can happen in other forms of malaria as well when these organs work to 4 replace red blood cells lost to infection. P. ovale is a less common tertian malaria with milder symptoms. It’s course of infection is similar to that of P. vivax. P. knowlesi species was previously known only as one of the monkey malarias and is morphologically similar to P. malariae. The high frequency of asexual reproduction in red blood cells results in hyperparasitemia, making it especially virulent if left untreated. The difference between P. malariae, which causes quartan malaria, from P. vivax and P. falciparum is that the parasites invade only mature erythrocytes. Therefore, symptoms can be more severe than in vivax malaria in the acute phase. However, infections tend to develop more slowly and become chronic. In human malaria, there is a clear distinction between relapse and recrudescence of infection. The course of infection of malaria in humans varies with many factors, including history of past exposure and presence of antibodies; age, health, and nutritional status; and genetic resistance (Dechavanne et al., 2016). 1.4. Significance of Anopheles mosquitoes There are nearly 3,500 known species of mosquitoes and about 430 described species of Anopheles (Kitzmiller, 1982). Of the Anopheles species, only about 40 species are important in malaria transmission as primary or secondary vectors in endemic settings (Besansky, 2008). Among the important malaria vectors are; Anopheles albimanus in Central America, An. darlingi in South America, An. gambiae and An. funestus in Africa, An. culicifacies in Asia, and An. dirus in Southeast Asia. Anopheles gambiae is considered the most important of all, because it is responsible for causing large numbers of malaria cases and deaths, mainly in Africa. This species lives in close association with humans, feeds primarily on them, and can complete a gonotrophic 5 cycle in only two days. A wide variety of sunlit surface pools during the rainy seasons provides places for larvae development. Many of such places are associated with human activity, such as borrow pits, roadside ditches, wheel ruts, and the hoof prints of domestic animals. Larval development normally only lasts one week (Mullen & Durden, 2009). Several studies have described mosquito contribution to malaria around the world, especially sub- Saharan Africa, where Anopheles funestus species assemblage and Anopheles gambiae species complex are the primary vectors (Fontenile & Lochouarn, 1999; Sachs et al., 2004; Sinka et al., 2012). 1.5. Vectorial capacity Anopheles mosquitoes have specialized traits that permit them to function as biological vectors of human malaria (Collins & Paskewitz, 1995). The traits that are important to their role in malaria transmission include susceptibility of the mosquito to the parasite throughout the entire sporogonic stage, mosquito population density, longevity, and blood feeding behavior (Besansky, 2008). Together these traits define the concept of vectorial capacity (VC). VC can be summarized as the total number of potentially infectious bites that would eventually arise from all the mosquitoes biting a single perfectly infectious (i.e., all mosquito bites result in infection) human on a single day (Brady et al., 2016; Kramer & Ciota, 2015). It is understood therefore, that VC describes the potential of a vector to transmit a pathogen (Catano-Lopez et al., 2019). However, in general not all mosquito vectors have the same potential of parasite transmission including malaria pathogens. Other genera like culicine mosquitoes for example, cannot transmit human (indeed, mammalian) Plasmodium species due to the fact that they are not susceptible to infection by these parasites. Interestingly though, some members of the Anopheles species do not transmit malaria parasites. 6 This phenomenon acknowledges differences in vector competence even within the same mosquito species. The phenotypic differences in susceptibility to parasites are well-described, both among anopheline species and among individuals of other species (Collins et al., 1986; Vernick et al., 2005). If a mosquito is susceptible to parasite infection, its blood-feeding behavior, population density and longevity become the most important determinants in vector capacity. For a mosquito to transmit malaria efficiently, it must have a high probability of feeding on humans, high enough populations and must live long enough to allow the malaria parasite to complete extrinsic development (Edalat et al., 2015). The average longevity among anopheline species in the tropics ranges widely, from 10 days to over one month (Ndoen et al., 2012). On average the parasites need between 8-35 days to develop in a mosquito and the longer the mosquito’s life span, the more effective the mosquito becomes as a vector (Ndoen et al., 2012). Average lifespan can account for differences in vectorial capacity among species, but it is certainly not the only factor, as illustrated by the An. gambiae species complex. An. gambiae and its sibling species An. quadriannulatus represent an example of paired vector and non-vector species that differ profoundly in their roles in malaria transmission. An. quadriannulatus is not naturally found infected with malaria parasites, yet can be infected with cultured P. falciparum (albeit at lower infection prevalence compared to An. gambiae; Takken et al., 1999; Besansky, 2008). The non-vector status of An. quadriannulatus in nature is due to its preference for feeding on animals, and very rarely on humans. An. gambiae on the other hand, shows an overwhelming preference for human odor (Besansky, 2008). 1.6. Mosquito vectors and epidemiology Malaria has been viewed in the context of stable or unstable transmission, reflecting in part attributes of an Anopheles population that affect its vectorial capacity. Stable malaria is most 7 often associated with P. falciparum infection in highly endemic settings. It is characterized by low fluctuations in parasite incidence in human and vector populations, high prevalence, and high seroprevalence for antibodies. Epidemics are unlikely under these conditions because transmission continues at high rates. In such settings, vectors tend to be highly anthropophagic, exhibit greater longevity, and have relatively low, stable densities but still exhibit considerable seasonal variation (Mullen & Durden, 2009). Unstable malaria most often tends to be associated with P. vivax infections in endemic settings of high fluctuation in disease incidence. In these settings, vectors tend to be zoophagic, have seasonally profound variation in population densities, low or nondetectable field infection rates, and may have shorter longevity than do those in stable malaria settings. Epidemics can occur in conditions of unstable malaria if environmental changes favor increased vector-human contact; e.g., during civil strife, following water projects such as dams or irrigation schemes, or when a new vector species is introduced into an area (Mullen & Durden, 2009). Human-vector contact driven by human availability and exposures to mosquitoes forms the critical point for pathogen transmission in many vector borne disease systems (Martinez et al., 2021; Schaber et al., 2021; Thongsripong et al., 2019, 2020). The same provides an opportunity for vector borne disease prevention and control interventions. 1.7. Malaria situation in Malawi 1.7.1. Description and map of Malawi Malawi is a landlocked country located in southeastern Africa in the Great Rift Valley on the western shore of Lake Malawi, the most southerly lake in the Great African Rift Valley system. Malawi shares international borders with Tanzania, Zambia and Mozambique. It is geographically located on -13° 15' 4.38" S and 34° 18' 5.50" E. The country covers an area of 8 118,484 km². The nation is divided into three main regions: Northern, Central and Southern. There are also three different geographical regions, the Rift Valley, the Central African Plateau, and the Highlands. The Shire river is the largest in Malawi and the only outlet of Lake Malawi. Mulanje Mountain is the highest at an elevation at 3,002 m (9,849 ft) above sea level. Malawi is one of the world's most densely populated nations with a population of 17.5 million people (NSO, 2019). The study was conducted in Machinga and Balaka districts in in the Southern region of Malawi (Figure 1.2). 9 v (Namanolo) (Ntaja) Chiladzulu AFRICA Figure 1.2. Map of Malawi showing the study sites by district. Malaria is highly endemic in Malawi causing an estimated six million annual cases (in a population of approximately 17 million people), and remains a major public health burden, one of the most significant causes of morbidity and mortality (Riveron et al., 2015; Spiers, et al., 2002; Snow et 10 al., 2013; NSO, 2019; WHO, 2021b). Transmission is mainly determined by climatic factors such as temperature, humidity, and rainfall and the rural landscape which promotes production of Anopheles mosquitoes in association with agriculture. The extent and distribution of these factors influence malaria prevalence. In Malawi, transmission is highest in areas of high temperature and frequent rainfall from October through April (Government of Malawi, 2015). Studies have also shown that, although every Malawian resident lives in a region of malaria risk, defined as greater than one case per 1000 residents, the risk is highly uneven and varies by a variety of factors such as landscape (topography, agriculture, urban or rural setting), quality of housing, socioeconomic status (degree of poverty), demographic (age and gender) history of infection and exposure, proximity and access to health care facilities, extent of use of malaria protection measures such as long-lasting insecticidal nets (LLINs), and so on (Buchwald et al., 2016, 2017, 2018; Coalson et al., 2016, 2018). In 2008, over 18% of hospital deaths of children less than five years old, and over one third of all outpatient visits, were attributed to malaria, and the most highly prevalent parasite species was Plasmodium falciparum. Illnesses classified as malaria represented one half of all outpatient consultations that occurred in the country (Mathanga et al., 2012; Mzilahowa, et al., 2012). By 2018, it was reported that nearly 4 million people in Malawi were diagnosed with malaria infection every year and the country accounted for 2% of malaria cases worldwide becoming among the top 15 countries with high malaria burden in the world (Chilanga et al., 2020). 1.7.2. Malaria vector control The push for malaria elimination and eventual eradication is heavily dependent on the ability to reduce parasite transmission. In highly endemic areas the ability to reduce malaria transmission is 11 dependent on controlling vectors to a low level. It is after achieving low vector populations that control strategies can shift to killing the parasite in infected people (Mendis et al., 2009). Two forms of vector control, indoor residual spraying (IRS) and distribution of long-lasting insecticidal nets (LLINs) have been shown to reduce transmission when properly deployed against insecticide susceptible mosquito populations (Tukei et al., 2017; WHO, 2006). Endemic countries have deployed efficacious vector control using IRS and LLINs as hallmark interventions, alongside case management with effective treatment using artemisinin-based combination therapy (ACT) guided by definitive diagnosis (Chanda et al., 2015). In Malawi, current malaria control efforts rely heavily on the insecticide-based interventions. The initial malaria interventions are being targeted at protecting those at highest risk of disease (pregnant women and under five children) with the aim to towards universal coverage. However, to move from control to elimination there is need to effectively interrupt transmission in the population, hence the fight against malaria in Malawi is far from over. While there has been substantial research in Malawi on the pathology, immunology and chemotherapy of malaria, knowledge of malaria transmission dynamics and of the vectorial roles (ecology and behavior) of various anopheline species known to occur in Malawi is spars (Spiers, et al., 2002; Mzilahowa, et al., 2012). Starting in 1911, studies on malaria transmission in Malawi identified two vectors of malaria parasite, An. funestus which was the most common, and An. gambiae sensu lato (i.e., s.s.) (Mzilahowa et al., 2012). Reports of increasing resistance in these vectors against the main insecticides used in public health are of concern for the continued effectiveness of the control tools in different parts of Africa (Czeher et al., 2008; Djouaka et al., 2008; Hargreaves et al., 2000; Martinez-Torres et al., 1998; Ranson et al., 2009, 2011). In Malawi, the concern is even greater 12 because of the increasing cases of resistance against pyrethroids (the only insecticide class used in bed nets) in the major malaria vector Anopheles funestus s.l. and An gambiae s.l. (Mzilahowa et al., 2016; Riveron et al., 2015). Challenges facing malaria vector control strategies in Malawi as in many countries include lack of effective program implementation and management, faulty manufacture and quality control in LLINs, low uptake of LLINs into communities, and elements of the transmission system outside of what coverage provides (Cohen et al., 2012; Lindblade et al., 2015; Vinit et al., 2020; Lindsay et al., 2021). It is against this background that the current study aimed at furthering the understanding of vector species distribution, host preference and malaria transmission patterns (from humans to mosquitoes) in the local mosquito population. This study also aimed at characterizing human-to- mosquito parasite transmission in detail. This was done by using molecular techniques to link mosquito blood meals to individuals that were fed upon and to determine the mosquito host selection range in few vertebrate hosts (human, dog and goat). Human availability and vector preferences determine which hosts are most frequently bitten (Keven et al., 2017; Toe et al., 2018). We hypothesize that An. gambiae s.l. and An. funestus will be the most abundant mosquito species in the study sites. Previous ICEMR-supported research in an urban-rural site in Malawi found that 90% of vectors captured were An. gambiae s.l. (primarily. An. arabiensis) and An. funestus was the only other species detected (Dear et al., 2018). We also hypothesize that humans will be the mostly utilized source of blood meal and that school-age children (6-15 years old) are the predominant source of Anopheles blood meals. Previous studies have suggested that a greater proportion of blood meals are taken from adults and older children than young children and infants (Carnevale, Frézil, Bosseno, Le Pont, & Lancien, 1978; Muirhead- 13 Thomson, 1951) partially because of differences in body surface area. Studies have also shown differential use of LLINs by age, with school-age children being least likely to sleep under nets in Malawi (Buchwald et al., 2016; Walldorf et al., 2015). Thus, school-age children are likely to be bitten more frequently based on size and limited LLIN use. In addition, previous studies reported that Plasmodium-infected individuals are more attractive to vectors than uninfected individuals (De Moraes et al., 2014; Lacroix et al., 2005). Given the observations that school-age children have the highest prevalence of both asexual stage infection (Walldorf et al., 2015) and gametocytes (Coalson, 2015), we anticipate that vectors will preferentially take blood meals from them. We further hypothesize that human transmission reservoirs that are not sufficiently impacted by standard malaria interventions, contribute to malaria being recalcitrant in Malawi. We aim to identify these populations by quantifying the complex interactions that determine the human-to- mosquito Plasmodium transmission from different population sub-groups. Exposure to Anopheles feeding is one major component of the spread of infection. However, if the person is uninfected or has only asexual parasites, biting frequency is irrelevant to parasite transmission. Thus, the prevalence of gametocyte-containing infections in human sub-groups critically influences their differential contributions. Finally, not all gametocyte infections result in transmission to every feeding mosquito. The population-level dynamics of human-to-mosquito transmission depend on each component: the probability of being bitten, the probability of carrying parasites/gametocytes when bitten, and the probability of successful transmission per blood meal. Estimating all three in the same setting thoroughly quantifies human contributions to malaria transmission and enables the characterization of the predominant transmission reservoirs. 14 1.8. Research significance and objective 1.8.1. Significance This study aims to increase our understanding of malaria transmission from humans to mosquito, malaria infection reservoirs, and to inform designing of effective malaria control strategies. The linking of human to mosquito infection is not well understood. However, characterizing transmission from humans to mosquitoes is complex. Identifying which humans harbor gametocytes is insufficient because successful transmission involves complex, multidimensional relationships between human and vector behaviors, and human, vector, and parasite biological interactions. Few studies have attempted to fully describe and model the factors that contribute to human-to-mosquito transmission, yet that information is essential to reducing malaria transmission. Our overall goal is to understand the complex human, parasite, and vector relationships (human and vector behaviors, and human, vector, and parasite biological interactions), identify the most important sources of malaria parasite transmission in the human population. This information could be applied in the designing of new control strategies targeting these malaria reservoirs. It was envisaged that the study will contribute to the current understanding of malaria transmission dynamics and the vectorial roles of mosquitoes (ecology and behavior) and improve the practice of malaria vector control interventions in Malawi. This research was part of a larger endeavor called the International Centers of Excellence in Malaria Research (ICEMR), a multi-site program funded by the US National Institute of Allergy and Infectious Diseases of the NIH. One of the sites is in Malawi and associated with the College of Medicine and its Malaria Alert Center in Blantyre, with institutional partners in the US being Michigan State University and the University of Maryland School of Medicine in Baltimore. The 15 project is titled “The Intransigence of Malaria in Malawi: Understanding Hidden Reservoirs, Successful Vectors and Prevention Failures” and the award number is U19AI089683. The overall goal of the ICEMR project in Malawi is to determine why malaria persists in the country despite strong interventions imposed against it (primarily distribution of insecticide treated bed nets, indoor residual insecticide sprays, and distribution of antimalaria drugs to vulnerable groups of people). The aim is to use knowledge gained from the research program to guide Malawi’s malaria policies and intervention strategies to achieve malaria control and, ultimately, elimination. The ICEMR program has three arms or projects: (P1) Epidemiology, (P2) Transmission, and (P3) Infection and Disease. The research reported here falls under P2. The overall aim of P2 was to identify the most important sources of malaria transmission in the human population and to apply this information in the design of new strategies to target these reservoirs. 1.8.2. Objective The aim of the research described in this dissertation was to delineate human to mosquito Plasmodium infection transmission through blood meal and genotyping analysis to understand drivers of malaria infection in different population groups. This aim was broken down into three objectives and their hypotheses as outlined below. Objective 1 (Chapter 2): To quantify malaria vector species composition, relative abundance and distribution in the study area as they relate to malaria transmission. Hypothesis 1.a. The composition, distribution and abundance of the different mosquito vector species is the same across the study area. 16 Hypothesis 1.b. Mosquito infection rates are similar across the study area by species and site. Objective 2 (Chapter 3): To investigate blood host selection behavior of malaria vector mosquitoes for blood meal sources, addressing the question: which vertebrate hosts are the primary sources of blood meals, amongst the available humans and non-human hosts? Hypothesis. Mosquito feeding is host specific with regard to human and non-human hosts available in the study area. Objective 3 (Chapter 4): To determine sources of mosquito blood meals within human population demographic groups. Hypothesis 3.a. Mosquito feeding on individual humans is nonrandom. Hypothesis 3.b. Mosquito feeding is preferential on certain human population groups (males and 6-15 years old), classified by age and gender in the study area and these groups drive malaria transmission. 1.9. Research ethical approval Institutional Research Board (IRB) reviews of this sample design were submitted and approved by the University of Malawi, College of Medicine (COMREC) and Michigan State University (MSUIRB) (IRB00003905 FWA00005976), under the International Center of Excellence in Malaria (ICEMR) research program awarded to these two institutions from the National Institutes of Health (NIH) (U19AI089683). This project was a component of the ICEMR research program under Project 2: Transmission. 17 APPENDIX 18 Sampling Mosquitoes Human Host Aspiration, CDC light traps, PSCs Finger prick Sample processing (dried samples) Sample processing Mosquito dissection Dried filter paper Head and Thorax Abdomen DNA Extraction DNA Extraction PCR PCR Plasmodium DNA profile detection Plasmodium Mosquito Host ID detection species ID Matching DNA profile Age Sex Figure 1.3. Conceptual framework 19 CHAPTER 2 : MOSQUITO COMPOSITION, ABUNDANCE AND DISTRIBUTION IN RELATION TO PLASMODIUM INFECTION TRANSMISSION IN ANOPHELES MOSQUITO SPECIES REVEALS PRESENCE OF POTENTIAL SECONDARY MALARIA VECTORS IN SOUTHEASTERN MALAWI 2.1.Abstract Introduction. Understanding mosquito species composition, abundance and distribution is vital step in malaria vector surveillance and control. Variations in distribution and abundance of Anopheles species are important factors driving spatiotemporal changes in transmission intensity and infection prevalence. This study aimed at understanding differences in species composition and quantifying the malaria vector species abundance and distribution and P. falciparum infection rates as they relate to malaria transmission. Method. Morphologically identified female Anopheles mosquitoes were sampled in human dwellings in Namanolo and Ntaja for almost one year using aspiration, CDC light traps and pyrethrum spray catches. Molecular mosquito species identification and Plasmodium falciparum infection detection in the mosquito head-thorax and abdominal sections were done by PCR. Statistical data analysis included frequency distribution, chi-square and fisher’s exact test with all tests done at 0.05 significance level. Results. Of 6,763 mosquito samples analyzed and morphologically identified as Anopheles only five Anopheles species were molecularly identified. The dominant species were An. arabiensis (8.8%), An. funestus s.s. (25%) and An. gambiae s.s. (2.9%). An. parensis and An. vaneedeni were less abundant (<0.1%); 63.1% were other as yet unidentified Anopheles species. There were no significant differences in species composition, but species abundance varied from 0.03 to 65.8% 20 in the two study sites. The infection rates among the species in the head-thorax section of the mosquitoes were significantly different but no significant difference was observed in the abdominal sections of blood fed samples. The infection rate was higher in the abdomen (26 and 36%) than the head-thorax section (14 and 28%) across all species in all sites with infection rates higher in Ntaja than Namanolo. The highest Plasmodium falciparum infection rate in both abdomen and head-thorax section was observed in An. gambiae s.s. In the blood-fed mosquitoes, Plasmodium falciparum positive rates in the PCR unidentified Anopheles species suggests the presence of potential secondary malaria vectors. Conclusion. Anopheles species composition and distribution except abundance is similar across the study area. The infection rates in An. arabiensis, An. funestus and An. gambiae s.s. in head- thorax and abdomen of mosquitoes point to a potential situation of residual malaria transmission. Presence of potential secondary malaria vectors needs further investigation. 21 2.2. Introduction Malaria remains one of the major health burdens in African including Malawi where malaria cases are estimated at four to six million annually (Government of Malawi, 2015; Riveron et al., 2015; WHO, 2021b). The two dominant species of Anopheles mosquitoes that transmit malaria in Malawi are Anopheles gambiae species complex and An. funestus species assemblage (Mzilahowa et al., 2012; Spiers et al., 2002). Since 2000, a decrease in malaria incidence and mortality has been reported in sub-Saharan Africa, mainly due to widespread use of LLINs (Cibulskis et al., 2016; WHO, 2014). However, the gains have been faced with challenges such as the rise of insecticide resistance in the malaria vector mosquitoes which appear to be wide spread across countries and malaria mosquito species (Hunt et al., 2010; Mzilahowa et al., 2016; Ranson et al., 2011; Riveron et al., 2015). Others challenges facing malaria control include lack of effective program implementation and management, faulty manufacture and quality control in LLINs, uptake of LLINs into communities, and elements of the transmission system outside of what coverage provides (Cohen et al., 2012; Lindblade et al., 2015; Vinit et al., 2020; Lindsay et al., 2021). Therefore, understanding mosquito vector species composition, abundance and distribution is a vital step in malaria vector surveillance and control. Variations in distribution and abundance of Anopheles species are important factors driving spatiotemporal variation in transmission intensity and infection prevalence (Eba et al., 2021). Mosquito species composition varies greatly among geographic locations (villages), even among villages that are less than 1 km apart (Keven et al., 2017). Without quantitative estimates, it is difficult to describe the degree to which two localities differ in their mosquito species composition and therefore malaria transmission. 22 This study aims at understanding the degree of dissimilarities in species composition among localities in the study area (Roberts & Hsi, 1979; Almeida et al., 2008) and quantifying the malaria vector species abundance and distribution as they relate to malaria parasite transmission in Machinga and Balaka districts. We, therefore, hypothesis that (1) the composition, distribution and abundance of the different mosquito vector species is homogenous and (2) Mosquito infection rates are similar across the study area by species and site. 23 2.3. Methods 2.3.1. Study sites Malawi is a landlocked country located in southeastern Africa in the Great Rift Valley on the western shore of Lake Malawi, the most southerly lake in the Great African Rift Valley system. Malawi shares international borders with Tanzania, Zambia and Mozambique. It is geographically located at -13° 15' 4.38" S and 34° 18' 5.50" E (Figure 2.1). The country covers an area of 118,484 km². The nation is divided in three main regions: Northern, Central and Southern. There are also three different geographical regions, the Rift Valley, the Central African Plateau, and the Highlands. The Shire River is the largest river in Malawi and the outlet of Lake Malawi, flowing south to the Zambezi River. Mulanje mountain is the highest at an elevation of 3,002 m (9,849 ft) above sea level. Malawi is one of the world's most densely populated nations with a population of 17.5 million people (NSO, 2019). 24 Machinga Balaka (Ntaja) (Namanolo) MALAWI Figure 2.1. Map of Malawi showing the study sites. 2.3.2. Description of Study areas The study was conducted in Machinga and Balaka districts in the Southern region of Malawi. Machinga district covers an area of 3,771 km² and has a population of 735,438 (NSO, 2019). Balaka is a township in the southern region of Malawi and headquarters for Balaka District. The township was formerly a boma of Machinga District, before Balaka District was created in 1998. The district covers an area of 2,193 km² and has a population 438,379 (NSO, 2019). Both districts are mostly rural areas with the majority of the people sustaining their livelihood through 25 subsistence farming. Balaka district is located on a lower elevation and close to the Shire River, the largest river in the country, while Machinga is on a higher elevation further away from the river but has small semi-permanent and temporally water bodies more prominent in the rainy season. 2.3.3. Study design The overall study approach was a longitudinal cohort study in communities located in Balaka and Machinga districts within the catchment area of two health centers, Namanolo health center in Balaka and Ntaja in Machinga district. Mosquito sampling was conducted in these catchment areas from which ~100 households in each site (total 200) were sampled. Index houses were randomly sampled within an ecogeographic quadrant in a 10 kilometers radius from the health center. Then neighboring houses were identified to create clusters. On each selected household, the household head was consented. Households were visited for entomological sampling for one year after the universal Long-Lasting Insecticidal Nets (LLINs) distribution campaign in 2018 (Government of Malawi, 2018). 2.3.4. Sample collection and processing Mosquito sampling and analysis Indoor resting female Anopheles mosquitoes were sampled until there were none found resting on walls in the sleeping spaces of human dwellings on any sampling morning. The households were selected by the randomized cluster sampling method, monthly for three times each period from May-June 2019, October-November 2019, and December 2019-January 2020. Beginning in February to April of 2020, only a subset of households in each site were sampled once every two 26 weeks. Mosquito sampling tools including hand and battery powered aspirators, standard miniature CDC Light Trap (Model 512; John W. Hock Company, Gainesville, Florida, USA) and pyrethrum spray catches (PSCs) (WHO, 1995; Odiere et al., 2007) were used to maximize sampling effort. Mosquitoes were morphologically identified (Gillies & Coetze, 1987) into Anopheles mosquito species with emphasis on identifying major malaria vectors Anopheles gambiae sensu lato (Giles,1902) and Anopheles funestus sensu lato (Giles, 1900). The mosquito samples were stored in silica gel and processed. Blood feeding status was scored by visual inspection into fully engorged (fed), gravid, half-gravid and unfed mosquito. The abdomen was separated from the head and thorax of each mosquito using sterile techniques, and these two body parts were processed separately. Genomic DNA was extracted from mosquito abdomens and mosquito head-thorax using Qiagen extraction kits (DNeasy® Blood & Tissue Kit; Cat. No. 69506) following the manufactures standard protocol. The mosquito abdomens (a subset which included all blood fed and a random sample of unfed mosquitoes) were analyzed for P. falciparum blood-stage and oocyst infection while the head-thorax was analyzed for P. falciparum (presumably, sporozoite) infection and mosquito species identification. Molecular mosquito species identification Mosquitoes of the Anopheles gambiae species complex were identified to species using real time quantitative PCR method of Walker et al., (2007). The universal primers were forward 5'-GTG AAGCTTGGTGCGTGCT-3' and reverse 5'-GCACGCCGA CAAGCTCA-3'. The probe for An. gambiae s.s. (Giles, 1902) was 5'-VIC-CGGTA GGAGCGGGACACGTA- MGBNFQ-3' and the probe for An. arabiensis (Patton, 1905) was 5'-6FAM-TAGGATGGAGAAGGACACTTA- 27 MGBNFQ-3'. Mosquitoes of the Anopheles funestus species assemblage (Giles, 1900) were identified to species using the real time PCR method of Scott et al., (1993) and Koekemoer et al., (2002). The universal primers were forward 5'-AGAACACTATGGCGAGCAGC-3', and the reverse was 5'-TTACGACGGATACGGTCAACG-3'. The probe for An. funestus s.s. was 5'- 6FAM - CATGGGGAAATTCAATCGAAAACCTCT-QSY-3', the probe for An. parensis (Gillies, 1962) was 5'-ABY-TGGCGTGCTCGGAACCTAGC-QSY-3', and the probe for An. vaneedeni (Gillies, 1968) was 5'-VIC-CGTTGTGAAAAATGGAGATTCATTTGAAAACC- QSY-3'. PCR amplifications for An. gambiae s.l. and An. funestus s.l. were carried out in a volume of 10 µL reaction with 5 µL of 2X Taq Universal Master Mix (Cat. No. 4304437), 0.6 µL of each primer (10 µM), 0.4 µL of each probe, 2 µL of DNA, and nuclease-free water. PCR cycling conditions for the amplification of DNA from An. gambiae s.l. and An. funestus s.l. sources on QuantStudioTM RT-PCR System were as follows: one cycle at 50 oC for 2 minutes, 95 oC for 10 minutes, followed by 40 cycles at 95 oC for 15 seconds, denaturization, and 60 oC for 1 minute annealing/extension temperatures. Positive DNA controls for An. arabiensis An. gambiae, An. funestus obtained from beiresources.org (MRA-495, MRA-142 and MRA-1027 respectively) and negative controls as blank were included within each experiment. The amplification curves were visualized on QuantStudio software. Molecular identification followed morphological identification for the following crucial reasons. 1) non-Anopheles species need to be separated from the sample, 2) morphological identification can be challenging in the field especially where a species complex is involved, 3) morphological identification is prone to human error and 4) the two methods complement each other (Friedheim, 2016). 28 Cytochrome oxidase subunit 1 (COI) gene barcoding (Beebe, 2018; Maekawa et al., 2021) was applied to a subsample of the mosquitoes that were not identifiable using the above PCR method. Molecular identification of Plasmodium falciparum Plasmodium falciparum was detected in nucleic acid extractions of mosquito abdomens, or heads- thoraces targeting 18S rRNA gene (Bass et al., 2008; Mangold et al., 2005). The primers used were forward 5'-ATTGCTTTTGAGAGGTTTTGTTACTTT-3' and reverse 5'- GCTGTAGTATTCAAACACAATGAACTCAA-3'. The probe was 5'-FAM- CATAACAGACGGGTAGTCAT-MGBNFQ-3' adopted from Kamau et al., (2013). PCR reactions for Plasmodium falciparum detection were performed in a volume of 10 µL with 5 µL of 2X Multiplex Master Mix (Cat. No. 4461882), 0.6 µL of each primer (10 µM), 0.4 µL of each probe, 2 µL of DNA, and nuclease-free water. PCR amplifications were with the QuantStudioTM RT-PCR System as follows: one cycle at 95 oC for 20 seconds, 40 cycles at 95 oC for 1 second, and 60 oC for 20 seconds. Positive genomic DNA controls for P. falciparum obtained from beiresources.org (MRA-506) and negative controls as blank were included within each experiment. The amplification curves were visualized on QuantStudio software. The number of Plasmodium falciparum positive mosquito samples was used to estimate human infection (using mosquito abdomen for asexual stages and gametocytes) and mosquito infection prevalence (using mosquito head and thorax for sporozoites). 29 2.3.5. Data analysis An estimate of community mosquito composition was assessed. Relative abundance and species distribution were calculated based on absolute numbers and proportions of specimens collected per location (household) and mosquito species in each site (Mbokazi et al., 2018). The infection rate for sporozoites in salivary glands (i.e., the sporozoite rate) and abdomen (mosquito infection; asexual stages and gametocytes) was compared for each species between districts. Statistical analysis included frequency distribution analysis to access abundance and distribution of mosquito species, chi-square, and contingency table fisher’s exact test where applicable was used to compare the mosquito proportions, all tests were carried out at 0.05 significant level. 30 2.4. Results 2.4.1. Mosquito species composition, distribution and abundance A total of 6,763 Anopheles mosquitoes were collected, including 3,766 (56%) from Namanolo and 2,997 (44%) from Ntaja (see supplementary data Appendix 2.1). Head-thorax sections from all 6,763 were analyzed, however, only a subset of samples, 1386 comprising of all blood fed mosquitoes and a few randomly selected nonblood feds, were analyzed in the abdominal sections. A total of 2,566 (37.9%) were identified as An. arabiensis, An. gambiae s.s., An. funestus s.s, An. parensis and An. vaneedeni (Table 2.1). An. funestus s.s. was the most abundant while Anopheles vaneedeni was only detected in Namanolo. Molecular identification did not detect 4197 (62.1%) of the entire samples to species using the five set of primers and probes in the scope of the study and were referred to as Anopheles spp. Those species identified molecularly were in agreement to morphological identifications done prior to extraction of nucleic acids. In addition, the morphological identifications also revealed the presence of An. pretoriensis (Theobald, 1903), An. maculipalpis (Giles, 1902), and An. coustani (Laveran, 1900). The results by Cytochrome oxidase subunit 1 (COI) gene barcoding on a subsample of the non-identified samples revealed the presence of other Anopheles species and that most of the non-identified mosquitoes were of the Anopheles gambiae complex (Figure 2.3). Mosquito relative abundance across species expressed as mean number of mosquitoes per household showed significant difference between the two sites (X2 = 396.3, P<0.001) (Figure 2.2). The non-identified species (Anopheles spp.) did not show significant differences between the two sites. 31 Table 2.1. Anopheles mosquito species abundance and distribution per site based on molecular identification. Number of mosquitoes collected per site (n (%)) Species Overall (n=6763) Namanolo (n=3766) Ntaja(n=2997) An. arabiensis 593 (8.8) 502 (13.3) 91 (3.0) An. funestus s.s. 1,694 (25.0) 730 (19.4) 964 (32.2) An. gambiae s.s. 198 (2.9) 50 (1.3) 148 (4.9) An. parensis 8 (0.1) 6 (0.2) 2 (0.1) An. vaneedeni 1 (0.01) 1 (0.03) 0 (0.0) Anopheles spp. 4,269(62) 2,477 (65.8) 1,792 (59.8) Namanolo Ntaja 40 40 mean number of mosquitoes per household 30 30 20 20 10 10 0 0 An. An. An. An. An. Anopheles An. An. An. An. An. Anopheles arabiensis funestus gambiae parensis vaneedeni spp. arabiensis funestus gambiae parensis vaneedeni spp. Anopheles species Figure 2.2. Anopheles mosquito species abundance and composition per site. Abundance calculated as mean number of mosquitoes per household with their standard errors. 32 Cytochrome Oxidase subunit 1 (COI ) gene barcording (n=376) 0.8 0.755 0.7 0.6 0.5 0.4 0.3 0.2 0.149 0.1 0.072 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.005 0.0 . ac ul ip s.l An a lp An a re .p . p is ns An An . pr h a is ro en si .qua e dr ens ia to s nn sri i An tu s .r ul a An ufi .v pe An An .s qu an see de ni .m An osu .c An stan .f am ou si An un . g us am e st bi ae Anopheles mosquito species Figure 2.3. Anopheles mosquito species proportions detected by COI gene bar coding from a subset of the non- PCR detected samples indicating presence of other Anopheles species. 2.4.2. Mosquito processed in head-thorax, for blood fed status and species abundance Of the 6,763 mosquitoes analyzed, 827 (12%) were visibly engorged blood fed. There were significant differences in mosquito feeding status across species between the two sites (X2 = 121.1, P < 0.001) (Table 2.2.). However, blood fed status across species showed An. arabiensis, An. gambiae s.s. and An. funestus s.s. to have higher proportion of blood fed than An. parensis, An. vaneedeni and Anopheles spp. Significantly more blood fed mosquitoes were collected in Namanolo (17%; n=542) than Ntaja (11%; n=285) (X2 = 37, P < 0.001) (Table 2.2). 33 Table 2.2. Blood-fed status of Anopheles mosquitoes processed in the head-thorax section. Number of mosquitoes based on blood fed status (fed and unfed) of all processed head sections (n (%)) Namanolo (n=3,766) Ntaja (n=2,997) Species fed (n=542) unfed (n=3224) fed (=285) unfed (n=2712) An. arabiensis 244 (0.45) 257 (0.08) 39 (0.14) 52 (0.02) An. funestus 165 (0.31) 564 (0.17) 138 (0.48) 826 (0.30) An. gambiae s.s. 32 (0.06) 18 (0.01) 67 (0.24) 81 (0.03) An. parensis 1 (0.002) 5 (0.00) 1 (0.00) 1 (0.00) An. vaneedeni 1 (0.002) 0 0 0 Anopheles spp. 99 (0.18) 2,380 (0.74) 40 (0.14) 1,752 (0.65) Note: percentage in parenthesis 2.4.3. Plasmodium falciparum infection status per body part of blood fed and unfed mosquitoes combined. Plasmodium falciparum infection detections in the head-thorax and abdominal sections of the mosquitoes revealed significantly higher infection rates in the abdominal sections (16%; n = 221) of the mosquitoes compared to the head-thorax sections (2%; n = 149) in all the two sites combined (X2 = 422, P < 0.001) (Table 2.3). Overall, there was no significant difference in head-thorax or abdomen infection between the two sites. Table 2.3. Number of Plasmodium falciparum infected mosquitoes per body section Head-Thorax section Abdomen section P. Overall Namanolo Ntaja Overall Namanolo Ntaja falciparum (n=6763) (n=3766) (n=2997) (n=1386) (n=855) (n=531) status positive 149 (0.02) 95 (0.03) 54 (0.02) 221 (0.16) 130 (0.15) 90 (0.17) negative 6614 (0.98) 3671 (0.97) 2943 (0.98) 1165 (0.84) 725 (0.85) 441 (0.83) 34 2.4.4. Mosquito blood-fed status and Plasmodium falciparum infection per body part There was an observable difference in infection rates between blood-fed status as well as body parts. The blood-fed mosquitoes had higher infection rates than non-blood feds and abdominal sections than heads (Table 2.4). There were no significant differences in infections between the study sites per mosquito body part. Significant differences were observed in the overall infection of the head-thorax section of fed (14%) vs unfed (0.006%), and overall abdominal infections of fed (26%) vs unfed (0.009%). Table 2.4. Mosquito blood-fed status and Plasmodium falciparum infection per body part and study site. Number of infected mosquitoes according to feeding status (n (%)) Head-Thorax section Abdomen section Blood Overall Namanolo Ntaja Blood Overall Namanolo Ntaja fed (6763) (n=3766) (n=2997) fed (n=1386) (n=855) (n=531) status status Fed 112 69 43 Fed 215 126 89 (n=827) (0.14) (0.13) (0.15) (n=827) (0.26) (0.23) (0.31) unfed 37 26 11 unfed 5 4 1 (5936) (0.006) (0.008) (0.004) (559) (0.009) (0.013) (0.004) Plasmodium falciparum infection across Anopheles species per body part and study site blood fed and unfed mosquitoes combined. The infection proportions varied greatly across the main malaria vector species and study sites ranging from 1 to 12% in head-thorax section and 5-39% in abdominal section. The overall infection proportion in both mosquito head and abdominal sections in Namanolo when compare across the mosquito species, An. arabiensis had number of high infections, followed by An. funestus and lastly An. gambiae. In Ntaja however, the highest number of infections were observed in An. funestus followed by An. gambiae and lastly An. arabiensis (Table 2.5) All species showed 35 no significant difference in infection within body parts across study sites except for An. gambiae which had significantly higher abdominal infection in Ntaja (48%; n = 32) than Namanolo (21%; n = 7) (X2 = 30.4, P < 0.001). Table 2.5. Anopheles species Plasmodium falciparum infection proportion per body part and study site. Number of infected mosquito species per body section (n (%)) Heads-Thorax Abdomen overall Namanolo Ntaja overall Namanolo Ntaja Species (n=6763) (n=3766) (n=2997) (n=1386) (n=855) (n=531) An. arabiensis 51 (0.09) 45 (0.09) 6 (0.07) 79 (0.25) 72 (0.25) 8 (0.20) An. funestus 39 (0.02) 20 (0.03) 19 (0.02) 77 (0.20) 36 (0.18) 41 (0.21) An. gambiae s.s. 24 (0.12) 6 (0.12) 18 (0.12) 39 (0.39) 7 (0.21) 32 (0.48) An. parensis 0 (0.00) 0 (0.00) 0 (0.00) 0 (0.00) 0 (0.00) 0 (0.00) An. vaneedeni 0 (0.00) 0. (0.00) 0 (0.00) 0 (0.00) 0 (0.00) 0 (0.00) Anopheles spp. 35 (0.01) 24 (0.01) 11 (0.01) 26 (0.05) 15 (0.05) 9 (0.04) 2.4.5. Mosquito species abundance and Plasmodium falciparum infection of blood fed mosquitoes analyzed in the abdomen section A total of 827 female blood fed Anopheles mosquitoes were collected in the two study sites. The overall species composition of blood-fed mosquitoes included An. arabiensis (n=283; 34%), An. funestus s.s. (n=303; 37%) and An. gambiae s.s. (n=99; 12%), An. parensis (n=2; 0.002%)), An. vaneedeni (n=1; 0.001%) and other Anopheles spp. (n=139; 17%). The most abundant species in general was An. funestus s.s., however, per site An. arabiensis (n=244) was most abundant in Namanolo followed by An. funestus s.s. (n=165) and lastly An. gambiae s.s. (n=32). In Ntaja the most abundant species was An. funestus s.s. (n=138) followed by An. gambiae s.s. (n=67) and lastly An. arabiensis (n=39). An. parensis (n=2) and An. vaneedeni (n=1) were the least abundant species. There were no significant differences in overall blood fed mosquito abundance between the two sites (X2 = 3.3, P = 0.07) although there were significant differences across species 36 abundance between the sites (X2 = 121.1, P < 0.001) (Table 2.6). Figure 2.4 shows abundance and distribution of mosquito analyzed in the abdomen section of blood fed samples. Table 2.6. Number of mosquitoes showing distribution and abundance of blood fed mosquitoes analyzed in the abdomen section (n (%). Anopheles species blood feeding status of all processed Abdomens (n=1386) Namanolo (n=855) Ntaja (n=531) fed unfed fed unfed Species (n=542) (n=313) Species (n=285) (n=246) An. arabiensis 244 (0.45) 37 (0.11) An. arabiensis 39 (0.14) 1 (0.004) An. funestus s.s. 165 (0.31) 36 (0.11) An. funestus s.s. 138 (0.48) 57 (0.23) An. gambiae s.s. 32 (0.06) 3 (0.01) An. gambiae s.s. 67 (0.25) 0 An. parensis 1 (0.002) 4 (0.01) An. parensis 1 (0.004) 0 An. vaneedeni 1 (0.002) 0 An. vaneedeni 0 0 Anopheles spp. 99 (0.18) 233 (0.74) Anopheles spp. 40 (0.14) 188 (0.76) Blood fed mosquito abundance and composition 0.90 0.80 0.70 0.60 0.48 0.50 0.14 Proportion 0.40 0.30 0.14 0.45 0.20 0.24 0.30 0.10 0.18 0.06 0.00 0.00 0.00 0.00 0.00 An. arabiensis An. funestus An. gambiae An. parensis An. vaneedeni unidentified Anopheles spp. Namanolo (n = 542) Ntaja (n = 285) Figure 2.4. Composition, abundance, and distribution of mosquitoes from blood fed abdominal sections only, per site expressed as a proportion. 37 2.4.6. Plasmodium falciparum infection of blood fed Anopheles species We looked at the infection in the mosquitoes by testing the presence of Plasmodium falciparum DNA of the head-thorax and abdominal section of the blood fed mosquitoes in the two sites. The overall infection was 14% in head-thorax and 27% in abdomen section. There was no statistical difference in head-thorax infection (13% Namanolo, 15% Ntaja; X2= 0.9, P = 0.34), but significant difference was observed in abdominal infection (23% Namanolo, 31% Ntaja; X2= 49, P < 0.001) between the sites (Figure 2.5). Blood-fed Anopheles mosquito Pf positive proportions Blood-fed Anopheles species Pf positive in head and (a) (b) 0.69 Namanolo (n = 542) Ntaja (n = abdomen 0.31 0.80 0.80 Ntaja 0.70 0.70 0.85 0.60 0.60 head 0.15 0.50 0.50 0.48 0.40 0.40 0.77 0.30 0.30 0.23 0.30 0.30 abdomen 0.21 0.20 0.20 Namanolo 0.23 0.21 0.13 0.10 0.18 0.16 0.10 0.15 0.12 0.25 0.08 0.06 0.87 0.00 0.00 0.00 0.00 head ra ra 0.13 An ens bi b .f un e is A n i en .f si An An . g us am s bi t un s A n es t An . p ae a re . g us An An .v an sis e n An An am b .a o p d en he le e i .a . p iae ar 0 0.2 0.4 0.6 0.8 1 ss pp A head abdomen head ab negative positive Figure 2.5. Blood fed mosquito Plasmodium falciparum (Pf) infection status in head-thorax and abdomen section expressed as a proportion. Positive infection rate ranging from 13 to 31%. In all species, there were significant differences in infection among them in the head-thorax section of the mosquitoes (X2= 33.1, P < 0.001) with some species having higher infections than others and significant difference in the abdominal section (X2= 64.6, P < 0.001) across all species in the in all sites. P. falciparum infections in the three main malaria vectors were higher in the abdominal section 38 than the head-thorax across all species in all sites. The overall infection rates ranged from 6 to 25% in the head-thorax, and from 13 to 48% in the abdomen. In Namanolo, in the three main malaria vector mosquitoes, the abdominal infection rate ranged from 21 to 30% with the highest infection observed in An. arabiensis (30%) followed by An. gambiae s.s. (23%) and lastly An. funestus s.s. (21%) (X2= 4.2, P < 0.12). The head-thorax infection rate (sporozoites) ranged from 8 to18% with the highest infection observed in An. arabiensis (18%) followed by An. gambiae s.s. (16%) and lastly An. funestus s.s. (8%) (X2= 7.3, P < 0.02) (Figure 2.5). In Ntaja, in the three main malaria vector mosquitoes, the abdominal infection rate ranged from 21 to 48% with the highest infection observed in An. gambiae s.s. (48%) followed by An. funestus s.s. (30%) and lastly An. arabiensis (21%) (X2= 9.9, P < 0.007). The head-thorax infection (sporozoites) rate ranged from 12 to 25% with highest infection rates observed in An. gambiae s.s. (25%), followed by An. arabiensis (15%) and lastly An. funestus s.s. (12%). (X2= 9.9, P < 0.007). Overall infection was higher in Ntaja than Namanolo in all body sections. (Figure 2.6). 39 Blood-fed Anopheles species Pf positive in head and abdomen (a) (b) Namanolo (n = 542) Ntaja (n = 285) 0.80 0.80 0.70 0.70 0.60 0.60 Proportion 0.50 0.50 0.48 0.40 0.40 0.30 0.30 0.23 0.30 0.30 0.21 0.20 0.21 0.20 0.13 0.25 0.20 0.10 0.18 0.16 0.10 0.15 0.08 0.12 0.06 0.05 0.00 0.00 0.00 0.00 0.00 0.00 sis ne m ns ed sis ne m ns ed ab st us biae is An en ab st us biae is An en ien pare op i ien pare op i fu ga vane he fu ga vane he ar An An An . le ss ar An An An . le ss An . . . An pp An . . . An pp . . head abdomen head abdomen Figure 2.6. Mosquito Plasmodium falciparum infection proportion across the five Anopheles species in head-thorax vs. abdomen in Namanolo and Ntaja. 40 2.5 Discussion The study results from indoor house collections show large numbers of unidentified species (62.1%), low percentage of blood fed mosquitoes (12%), high infection rates in abdominal sections and blood fed mosquitoes, and varied infection rates across species and sites. Several reasons could explain the high number of non-identified samples, including failure of the PCR (possible but very unlikely because these are standard methods in our lab) or availability of other Anopheles species outside the main known malaria vectors in Malawi. Other studies in Malawi have identified An. pretoriensis, An. maculupalpis and An. coustani, the same species morphologically identified in the current study (Maekawa et al., 2021). This observation could suggest the existence of potential secondary vector of malaria as evidenced by 18% blood fed mosquitoes and 1 to 5% infection rate for P. falciparum and calls for more research in the unidentified Anopheles species, or to a lesser extent, this could be due to indoor resting behavior of other Anopheles species. The molecular identification on a subset these mosquitoes by using COI gene barcoding revealed the presence of other Anopheles mosquito species with the majority belonging to the An. gambiae complex. These observation are consistent with other studies recently conducted in Malawi (Maekawa et al., 2021) using DNA barcoding where other Anopheles species were identified. However, COI gene barcoding need to be used with caution or in combination with other approaches like using ITS2 gene to resolve closely related species (Beebe, 2018). Prior studies have shown that dominant and epidemiologically important Anopheles species in Malawi are An. funestus s.s., An. gambiae s.s. and An. arabiensis. The other two species An. parensis (n=2) and An. vaneedeni (n=1) are in low abundance, rarely reported and not very important in malaria transmission in Malawi ( Gillies & Coetze, 1987; Hunt et al., 2010; 41 Mzilahowa et al., 2012; Riveron et al., 2015; Vezenegho et al., 2013). However, the presence of An. parensis and An. vaneedeni resting in human dwellings is an interesting observation because both of these have been demonstrated to be potential malaria vectors (Burke et al., 2019; Mouatcho et al., 2018). The same can be said about the PCR non-identified species of which some were by morphological and DNA barcoding identified as An. pretoriensis, An. maculipalpis and An. coustani and others. However, their role in malaria transmission in Malawi has not been fully explored largely due to their low abundance. This observation emphasizes the importance of accurate identification of mosquitoes in malaria studies (Dahan-Moss et al., 2020). Observed difference in species composition between the two sites was not significant despite differences in environmental conditions of the two sites where Namanolo is lower in elevation and flatter, as opposed to Ntaja which is drier and more elevated. The proportion of blood fed mosquitoes (12%) could be considered low because elsewhere Anopheles blood feeding is much higher ranging from 58 to 94% (Adugna et al., 2021, 2021; Escobar et al., 2020). The lower number of blood fed mosquitoes could be attributed to the widespread use of malaria control intervention in the area or that the mosquitoes are resting somewhere. In the study area it was very difficult to find blood fed mosquitoes. The use of LLINs and IRS initiatives could be responsible for the reduction of human mosquito contact and hence reduced accessibility to blood meals (CDC, 2016; Killeen et al., 2000; Mathanga et al., 2012). The proportions of blood fed mosquitoes were high in Nanamolo than Ntaja probably due to the presence LLINs containing pyrethroid with the synergist piperonyl butoxide (PBO) in Ntaja which is more effective against pyrethroid resistant mosquito species available in Malawi (Mzilahowa et al., 2016; Ogola et al., 2017; WHO, 2018a). 42 We looked at the infection in the mosquitoes by testing the presence of Plasmodium falciparum DNA of the head-thorax and abdominal section of the mosquitoes in the two sites. The results showed statistical difference in head-thorax infection between the sites analyzing all samples (fed and unfed, head-thorax sections) and differences in abdominal infections of blood fed mosquitoes only or all samples. This observation could mean that the infection prevalence in the population of the two districts is different with Ntaja having a higher plasmodium infection in the head-thorax region of the blood-fed mosquitoes than Namanolo. This is in line what literature shows where Ntaja (Machinga) is an area with high Malaria transmission than Namanolo (Balaka) (Bennett et al., 2013; Townes et al., 2013). The abdominal infections on the other hand, showed statistical differences in the two sites especially in the blood fed mosquitoes. This shows that the rate of acquisition of infection from human to mosquitoes during blood feeding is different in the two sites. One reason to explain this could be the difference in the mosquito species abundance in the two sites. As shown in this study, although species composition were similar, Namanolo was dominated by An. arabiensis and An. funestus s.s. while Ntaja was dominated by An. funestus s.s. and An. gambiae s.s. in significantly different proportions. Several studies have shown that these species exhibit differences in their host seeking and resting behavior, where An. funestus s.s. is highly anthropophilic and endophilic while An. gambiae s.l. is more zoophilic and exophilic (Sinka et al., 2010). This phenomenon adds to the explanation of the differences in the abdominal infection in the two sites where Ntaja has a higher positive infection rate (probably due to An. gambiae s.s.) and Namanolo having more blood feds (probably due to An. arabiensis). The infection results comparing the two mosquito body parts in the two sites showed that infection was higher in the abdominal section than the head-thorax across all species in all sites. This 43 observation is as expected. The infections in the abdomen could first and foremost be due to the gametocytes and other parasite asexual stages obtained from infected humans during blood feeding. However, remnants of previous feeding may also be detected in the mosquito midgut (oocytes) as the infection cycle progresses in the mosquito (cdc.gov, 2020; Pimenta et al., 1994). The combination of these two as detected by the standard Plasmodium PCR may explain the elevated levels of infection in the abdomen. As such not all infections in the abdomen could be attributed to the infected human population. However, the comparison with the head-thorax infection is one step toward understanding Plasmodium infection rates in the human population. In all cases the infection rates were high in Ntaja than Namanolo as explained above. The differences in infection among species in the head-thorax section and in the abdominal section across all species underscores the fact that different mosquito species have different efficiencies in acquiring plasmodium infection and becoming infectious (Medica & Sinnis, 2005; Stresman et al., 2010). This is a phenomenon referred to related concepts of vector competency and vectorial capacity (Ceccato et al., 2012; Garrett-Jones & Grab, 1964; Sallum et al., 2019). Some mosquitoes can acquire the parasites upon blood feeding activity, but they may not become infectious, that is, the infection not detected in the salivary glands (head-thorax) due to failure in the complex developmental process to infect the salivary glands (Ndoen et al, 2012). This may explain the lower infection rates observed in the head-thorax region of all species. The non-significant difference in the abdominal infection among the mosquito species maybe due to the mosquitoes obtaining the blood meal from the same infected populations and hence the rate of plasmodium acquisition may not vary greatly. The relatively lower infection rates in An. arabiensis could be attributed to its zoophilic and exophagic tendencies (Sinka et al., 2010). Considered at the district 44 level, the three major vector of malaria in the study sites maybe equally responsible in the acquisition of malaria parasite infection (abdomen infection) and transmission (head-thorax infection) from human to human respectively (Medica & Sinnis, 2005; Stresman et al., 2010). The rate of mosquito infection in the head-thorax is high indicating a presence of infectious mosquitoes which is crucial in malaria transmission (Ghosh et al., 2000; Kariu et al., 2002; Medica & Sinnis, 2005; Pimenta et al., 1994). The high rate of mosquito abdomen infections brings to light the fact that malaria maybe high in the human population where the mosquitoes obtain the blood meal from the human reservoir (Adhikari et al., 2018; Cheaveau et al., 2019; Githeko et al., 1992; Karl et al., 2011; Stresman et al., 2010). Also, high infection in blood fed mosquitoes could suggest that access to blood feeding increases chances of mosquitoes acquiring malaria parasites. These observations have serious implication on malaria transmission. First is the challenge posed by multiple vectors in malaria control strategies. This is even made worse due to the emergent of insecticide resistance that is observed in these species in many African countries including Malawi (Hunt et al., 2010; Mzilahowa et al., 2016; Ranson et al., 2011; Riveron et al., 2015). Second, the study has revealed that the three main malaria vector species are actively acquiring malaria infection from humans and becoming infectious. The availability of malaria reservoirs in the study area as demonstrated by the higher number of infected abdomen (blood meals) mean that there is perpetuation of residual malaria transmission. Unless these people are identified and targeted with control intervention, the basic reproductive number (Ro) remains high and transmission continues (Karl et al., 2011; Smith et al., 2007). And lastly, there exist potential secondary malaria vectors in the area which needs further investigation. 45 2.6 Conclusion The study has shown that there are five blood feeding Anopheles mosquito species present in the study sites with low percentage of blood fed mosquitoes. Of these five, three An. arabiensis, An. funestus s.s. and An. gambiae s.s. continue to pose threat of malaria transmission. The infection rates in head-thorax and abdomen of mosquitoes point to a situation where perpetuation of residual malaria transmission exists. Potential secondary vectors maybe present in the study area and needs more investigation. Understanding malaria species vector composition, infection rate in both head- thorax and abdominal section of the mosquito is key in determining effective malaria control and prevention strategies. We therefore recommend mass drug administration to reduce infection in the human population, increased and continued LLINs coverage and use to reduce contact between mosquitoes and humans as well as strategies aimed at further reducing mosquito populations. 46 APPENDIX 47 NUMBER OF MOSQUITOES SAMPLED IN 2019 AND 2020 Table 2.7. Total number of Anopheles mosquitoes collected per month of sampling in 2019 and 2020 in the two sites. Namanolo 2019 2020 Augus Januar month May June t October December y February March April Total An. arabiensi s 0 0 0 2 27 82 278 105 8 502 An. gambiae 0 1 0 0 3 12 34 1 1 52 An. funestus 10 15 0 0 2 61 434 317 107 946 An. parensis 0 4 0 0 1 0 0 1 0 6 An. vaneedeni 0 0 0 0 0 0 0 1 0 1 Anophele s spp. 1 10 68 1 24 412 1309 290 144 2259 Total 11 30 68 3 57 567 2055 715 260 3766 Ntaja 2019 2020 Ma Jun Novembe Decembe Februar Marc Apri Tota month y e October r r January y h l l An. arabiensi s 0 0 0 1 0 4 36 46 8 95 An. gambiae 0 0 0 0 2 8 98 44 2 154 An. funestus 16 62 3 1 40 129 353 302 60 966 An. parensis 0 0 0 0 0 1 0 1 0 2 An. vaneedeni 0 0 0 0 0 0 0 0 0 0 Anophele s spp. 4 4 0 0 17 152 820 725 58 1780 Total 20 66 3 2 59 294 1307 1118 128 2997 48 Number of mosquitoes collected per month 2500 2000 1500 1000 500 0 May June August October November December January February March April 2019 2020 Namanolo Ntaja Figure 2.7. Number of mosquitoes collected per month of sampling 49 Table 2.8. Blood fed and unfed Anopheles mosquitoes sampled in 2019 and 2020 showing month of sampling and numbers per site. Namanolo 2019 2020 May June August October December January February March April Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed total An. arabiensis 0 0 0 0 0 0 2 0 15 12 50 32 124 154 44 61 6 2 502 An. gambiae 0 0 1 0 0 0 0 0 3 0 6 6 22 12 0 1 1 0 52 An. funestus 0 10 2 13 0 0 0 0 1 1 11 50 57 377 83 234 10 97 946 An. parensis 0 0 1 4 0 0 0 0 0 0 0 0 0 0 0 1 0 0 6 An. vaneedeni 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 Anopheles spp. 0 1 3 7 0 68 0 1 16 8 28 384 43 1266 12 278 3 141 2259 Total 0 11 7 24 0 68 2 1 35 21 95 472 246 1809 140 575 20 240 3766 Ntaja 2019 2020 May June August October December January February March April Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed total An. arabiensis 0 0 0 0 0 0 1 0 0 0 2 2 4 32 30 16 2 6 95 An. gambiae 0 0 0 0 0 0 0 0 2 0 6 2 29 69 32 12 1 1 154 An. funestus 0 16 5 57 1 2 0 1 2 38 25 104 50 303 45 257 11 49 966 An. parensis 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 2 An. vaneedeni 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Anopheles spp. 0 4 0 4 0 0 0 0 1 16 3 149 16 801 19 709 0 58 1780 Total 0 20 5 61 1 2 1 1 5 54 36 258 99 1205 127 994 14 114 2997 50 Number of blood-fed and unfed mosquitoes 2000 1800 1600 1400 1200 1000 800 600 400 200 0 Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed Fed Unfed May June August October November December January February March April Namanolo Ntaja 2019 2020 Figure 2.8. Number of blood-fed and unfed mosquitoes collected and month of sampling per site. 51 CHAPTER 3 : BLOOD MEAL SOURCES OF ANOPHELES VECTORS OF HUMAN MALARIA IN MALAWI: IMPLICATIONS FOR MALARIA TRANSMISSION AND EFFECTIVENESS OF INTERVENTIONS Manuscript submitted, Malaria journal Rex B. Mbewe, John B. Keven, Themba Mzilahowa, Don P. Mathanga, Mark L. Wilson, Lauren M. Cohee, Miriam K. Laufer, Edward D. Walker. 3.1. Abstract Background. Selection of blood meal hosts by mosquitoes is a key variable in the vectorial capacity of Anopheles mosquitoes for human malaria. Blood feeding on humans is likely to be modulated by use of different types of long-lasting insecticidal nets (LLINs) and the effectiveness of LLINs is impacted by the relative intensity of insecticide resistance. The aim of this study was to test the hypothesis that LLINs containing pyrethroid and the synergist piperonyl butoxide (PBO) would lead to a reduction of human host utilization than LLINs containing only pyrethroid and that blood feeding patterns of Anopheles in Malawi compromise malaria interventions. Methods. Female Anopheles mosquitoes were sampled indoors from May 2019 through April 2020 by aspiration, pyrethrum spray catch, and CDC light trap in rural villages of Namanolo (conventional nets) and Ntaja (PBO nets) in Balaka and Machinga districts respectively. Anopheles species, blood meal sources, and infection with Plasmodium falciparum in the head-thorax of individual mosquitoes were determined by PCR. Human blood index (HBI) and Entomological inoculation rate (EIR) were also estimated. 52 Results. Of a total of 6,585 Anopheles females sampled indoors in 203 houses, 633 (9.6%) were blood-fed and consisted of An. arabiensis (44.1% (n=279)), An. gambiae s.s (16.2% (n=103)), An. funestus s.s (33.5% (n=212)), An. parensis 0.3% (n=2), and unidentified Anopheles spp (5.8% (n=37)). Of the 541 mosquitoes (85.5%) successfully identified blood meals, 436 (81.0%) were solely human, 28 (5.2%) goat, 11 (2.0%) dog, 60 (11.1%) mixed goat-human, 5 (0.9%) dog- human, and 1 dog-goat. Human blood index and EIR were higher in Namanolo than Ntaja (0.96 vs 0.89 (p = 0.001) and 0.11 vs 0.06 infective bites per person per year respectively) despite high net ownership (92%) and nightly use (75%) rates. Relative to host availability, non-human hosts were over selected in the two sites. Conclusion. The use of PBO nets was associated with lower HBI and EIR, however, the wide availability of LLINs was still associated with extensive successful human blood meals by the main malaria vectors in Malawi. The presence of a small fraction of mixed blood meals indicates constrained plasticity of Anopheles vectors to switch to non-human hosts and circumvent malaria control interventions. 53 3.2. Introduction Malaria is endemic in Malawi with transmission occurring throughout the country, having generally greater transmission in the south than the north (Malawi Malaria Indicatior Survey, 2017; Mathanga et al., 2012; Wilson et al., 2012). The nation-wide prevalence of infection for Plasmodium falciparum among 2 to10 year old individuals, sampled from 2010 to 2017, declined from 29.4% in 2010 to 15.2% in 2017 but this change was uneven across the country’s 28 jurisdictional districts (Chipeta et al., 2019). Despite these successes, which are largely attributed to reduction in transmission owing to the implementation of long-lasting insecticidal nets (LLINs) distributed throughout the country, Malawi remains a high malaria burden country with meso- endemic transmission (Chipeta et al., 2019). In 2017, the country-wide incidence of malaria was 247 per 1,000, with an estimated 7,077 deaths (WHO, 2018b). One of the drivers of persistent Plasmodium transmission is access to human blood by host-seeking female Anopheles mosquitoes. Selection of blood meal hosts by Anopheles mosquitoes is a key variable in their vectorial capacity - a measure of transmission - for human malaria because vectorial capacity increases with the square of the rate of human biting (Garrett-Jones & Grab, 1964). Further, host selection is likely to be modulated by use of different types of LLINs whose effectiveness is impacted by the extent of insecticide resistance in the Anopheles populations, and the relative availability of hosts (Keven et al., 2017; Toe et al., 2018). These factors will enhance or limit mosquitoes’ access to humans relative to non-human hosts. Emergence of pyrethroid resistance could severely compromise malaria control efforts by reducing the effectiveness of LLINs. Newer LLINs which combine pyrethroids with a synergist, piperonyl butoxide (PBO), have shown to be effective at restoring pyrethroid susceptibility (Protopopoff et al., 2018; Staedke et al., 2020; WHO, 2018a). 54 Vector incrimination studies in Malawi have identified members of the Anopheles gambiae sensu lato (s.l.) and Anopheles funestus species assemblage as the most important malaria vectors and pyrethroid insecticide resistance have been reported (Hunt et al., 2010; Mzilahowa et al., 2008, 2016; Spiers et al., 2002). However, only a single study has analyzed mosquito host selection and estimated the human blood index ((HBI) the proportion of blood meals obtained from humans by mosquito vectors) of these vectors in the southern region of the country before LLINs were available (Mzilahowa et al., 2012). Accordingly, whether human host selection has changed after LLINs availability is unknown. The objective of this study was therefore twofold. Firstly, we aimed to expand on knowledge of blood feeding patterns of malaria vectors, a key feature of malaria risk, by conducting host selection analyses and estimation of HBI and Entomological inoculation rate ((EIR) a standard matrix for malaria transmission intensity by anopheline vectors, defined as the number of infectious bites per person per time period) (Das et al., 2017; Mwesigwa et al., 2017). Secondly, we aimed to test the prediction that blood feeding on human hosts is reduced where LLINs containing pyrethroid and the synergist PBO (i.e., Olyset Net Plus, Sumitomo Corporation, Tokyo, Japan) compared to where standard, pyrethroid-only LLINs (i.e., Olyset Net, Sumitomo) have been distributed. Our hypothesis was that mosquito feeding is host specific with regard to human and non-human hosts available in the study area. 55 3.3. Methodology 3.3.1. Study area This study was conducted in two malaria-endemic districts of Malawi (Figure 3.1), Balaka (14° 58’ 45” S; 34° 57’ 20” E) and Machinga (15° 10’ 6” S; 35° 18’ 0” E). These districts, like the whole of Malawi, have distinct wet and dry seasons where malaria proliferates especially in the rainy wet season (Mathanga et al., 2012). In 2018, residents of Machinga received LLINs with PBO (Olyset Plus net, Sumitono Corporation, Tokyo, Japan), whilst residents of Balaka received standard LLINs only (Olyset net) (Government of Malawi, National Malaria Control Programme, 2017) (PMI, 2018). Households in rural areas located within the catchment areas of Ntaja (Machinga) and Namanolo (Balaka) health centers were enrolled in the study. Household surveys were conducted to determine the extent of LLINs ownership and utilization by householders and to quantify the number of occupants. Figure 3.1. Map of Africa showing the study sites in Namanolo and Ntaja in Malawi. 56 3.3.2. Mosquito sampling and analysis Blood-fed Anopheles mosquitoes were sampled in houses, selected by the randomized cluster sampling method. All households were sampled three times each period from May-June 2019, October-November 2019, and December 2019-January 2020. Beginning in February to April of 2020, only a subset of households in each site were sampled once every two weeks. The mosquito samples for each visit were accumulated. The number of humans and goats in the households were also counted. Dogs were too mobile to be counted reliably. Cattle were rare in the study area and scored as absent. Mosquito sampling tools included mouth and battery-powered aspirators, standard miniature CDC light traps (Model 512; John W. Hock Company, Gainesville, Florida, USA) and pyrethrum spray catches (PSCs) (Mzilahowa et al., 2012, 2016). Mosquitoes were morphologically identified (Gillies & Coetze, 1987) into An. gambiae sensu lato, An. funestus sensu lato, or other Anopheles species, stored in tubes with silica gel, and kept at laboratory temperatures. The abdomen was separated from the head-thorax of each mosquito using sterile, cross- contamination-proof technique. For each mosquito, genomic DNA was extracted from the abdomen and head-thorax separately using the Qiagen extraction kit (DNeasy® Blood & Tissue Kit; Cat. No. 69506) following the manufacturer’s standard protocol. 3.3.3. PCR identification of mosquitoes Mosquitoes of the An. gambiae (s.l.) complex were identified to one of two species, An. gambiae sensu stricto (s.s.) or An. arabiensis, using a published multiplex quantitative PCR (qPCR) method (Walker et al., 2007). Mosquitoes of the An. funestus (s.l.) species assemblage were identified to one of three species (An. funestus (s.s.), Anopheles parensis and Anopheles vaneedeni) using 57 another multiplex qPCR as follows. A universal primer pair (forward: 5’-AGA ACACTA TGG CGA GCA GC-3’, reverse: 5’-TTA CGA CGG ATA CGG TCA ACG-3’) that amplifies a region of the internal transcribed spacer region 2 of rRNA gene of members of the An. funestus (s.l.) species assemblage was designed along with two oligonucleotide probes specific to An. funestus (s.s.) (5’-FAM-CAT GGG GAA ATT CAA TCG AAA ACC TCT-QSY-3’) and An. parensis (ABY-TGG CGT GCT CGG AAC CTA GC-QSY). The probe specific to An. vaneedeni (5’-VIC- CGT TGT GAA AAA TGG AGA TTC ATT TGA AAA CC-QSY-3’) was obtained from a published source (Vezenegho et al., 2009). After performing optimization tests involving 10-fold dilution series of positive DNA control of the three species, the optimum PCR mixture (10 µL reaction volume) consisted of 1x TaqMan Universal Master Mix (Cat. No. 4304437; Thermo Fisher Scientific, Waltham, MA, USA), 0.6 µM of each primer, 0.4 µM of each probe, and 2 µL of mosquito DNA. The reactions were performed on QuantStudio 7 Flex PCR system (Applied Biosystems, Foster City, CA, USA) using the following cycling conditions: one cycle of 50 °C for 2 minutes and 95 °C for 10 minutes, 40 cycles of 95 °C for 15 seconds and 60 °C for 1 minute. PCR sensitivity was one target gene copy/µL sample and efficiency was > 90%. Positive genomic DNA controls for An. arabiensis An. gambiae, An. funestus obtained from beiresources.org (MRA- 495, MRA-142 and MRA-1027 respectively) and negative controls as blank were included in each experiment. The PCR results were visualized with QuantStudio software (version 1.3). 3.3.4. Blood meal analysis Individual mosquito abdominal DNA was first tested for human blood meal using a uniplex qPCR method that involved amplification of a region of intron 1 of the nuclear tyrosine hydroxylase gene with primers and probes (forward: 5’-GGC CTG TTC CTC CCT TAT TT-3′, reverse: 5’- TAC 58 ACA GGG CTT CCG AGT-3′, probe: FAM-ATG GAG TCT GTG TTC CCT GTG ACC -QSY) as described in Keven et al., (2020). Samples that did not react with the human probe in the qPCR were subjected to a standard PCR to amplify the vertebrate mitochondrial cytochrome B gene using a generic primer pair (forward: 5′-CCC CTC AGA ATG ATA TTT GTC CTC A-3′, reverse: 5′-CCA TCC AAC ATC TCA GCA TGA TGA AA-3′) (Boakye et al., 1999; Goldberg et al., 2009; Lee et al., 2002; Meece et al., 2005; Molaei et al., 2006). The PCR reaction mixture (25 µL volume) consisted of 10 mM Tris at pH 8.3, 50 mM KCl, 1.5 mM MgCl2, 0.01% gelatin, 1.0 mM dNTP, 0.5 units of Taq polymerase, 50 pmol of each primer, and approximately 20 ng of DNA template. The reaction condition included one cycle of 95 °C for 5 minutes (initial denaturation) followed by 35 cycles of 95 °C for 1 minute (denaturization), 57 °C for 1 minute (annealing) and 68 °C for 1 minute (extension), followed by one cycle of 68 °C for 5 minutes (final extension). The PCR products were visualized with 2% agarose gel electrophoresis and amplicons of positive samples were purified using QIAquick PCR purification kit (Cat. No. 2810; Qiagen) following the manufacturer’s protocol. The nucleotide sequence of amplicons was determined by direct sequencing and the sequences were subjected to BLAST (Basic Local Alignment Search Tool) search for matches to the available vertebrate host cytochrome B gene sequences in GenBank (https://blast.ncbi.nlm.nih.gov/Blast.cgi). A sequence similarity of 97% or higher was used as the cut-off for an acceptable match, based on literature (Goldberg et al., 2009; Kent, 2009; Nagaki et al., 2021; Stevenson et al., 2012). The different hosts identified in the mosquito blood meals based on the results of BLAST searches aided the development of new qPCR primers and probes specific to those host species; humans, dogs and goats were the only hosts identified by BLAST searches. Primers and probes (Table 3.1) for humans and dogs were adopted from literature (Keven et al., 2020) but those for goats were 59 designed and validated in this study using the same procedure for humans and dogs (Keven et al., 2020). Another set of qPCR procedures was performed on all the blood meal samples. The purpose of this second qPCR was to detect presence of mixed blood meals as well as to confirm the results of the previous uniplex qPCR. The qPCR mixture (10 µL reaction volume) consisted of 1X TaqMan Universal Master Mix (Cat. No. 4304437; Thermo Fisher Scientific), 0.5 µM of each primer, 0.25 µM of each probe, and 2 µL of DNA. PCR cycling condition (QuantStudio 7 Flex PCR System) was the same as described for An. funestus (s.l.) above positive and negative DNA controls were included in each experiment. Table 3.1. Blood meal host primers and probes used in the qPCR reactions Species Forward Reverse probe human Homo 5’- 5’- 5’-FAM- sapiens GGCCTGTTCCTCCCT TACACAGGGCTTCCGAGT ATGGAGTCTGTGT TAT TT-3’ -3’ T CCCTGTGACC - QSY- 3’ goat Capra 5’- 5’- 5’-ABY- hircus TAGGCGCCATGCTAC GAGTGGATTTGCTGGGAT ATTCACACCCGAC TAATTC-3’ ATAG-3’ CTACTCGGAGA- QSY-3’ dog Canis 5’- 5’- 5’-ABY- lupus TGGACAAAGCAACC CCGGTTTCGTGTAGAAAT TCATCCTCCCTTTC familiaris CTAACA-3’ AGGA-3’ ATCATCGCAGC- QSY-3’ *Note: goat primers and probes were developed in this study, human and dog were from Keven et al., (2020). 3.3.5. Molecular identification of Plasmodium falciparum DNA from both the abdomen and head-thorax of each mosquito was tested for presence of P. falciparum using a multiplex qPCR containing two fluorescent-labelled TaqMan probes targeting the 18S rRNA gene of P. falciparum (forward primer: 5’-ATT GCT TTT GAG AGG TTT TGT 60 TAC TTT-3′; reverse primer: 5’-GCT GTA GTA TTC AAA CAC AAT GAA CTC AA-3′; probe: 5’-FAM-CAT AAC AGA CGG GTA GTC AT- MGBNFQ-3′). These primers and probes were developed and tested for specificity to the target organism and gene locus using published methods (Kamau et al., 2013). The PCR reaction (10 µL volume) consisted of 1X TaqMan Multiplex Master Mix (Cat. No. 4461882; Thermo Fisher Scientific), 0.6 µM of each primer, 0.4 µM of each probe and 2 µL of DNA. PCR amplification (QuantStudio 7 Flex PCR System) was performed using the same cycling condition as with An. funestus (s.l.) described above. Positive genomic DNA control for P. falciparum was obtained from beiresources.org (MRA-506). 3.3.6. Data analysis Mosquitoes that had fed on one species of host, as determined by blood meal analysis as described above, were classified as single host blood meals. If the blood meal analysis revealed two or more species of vertebrate hosts, then the blood meals were classified as mixed blood meals. The HBI of an Anopheles population (i.e., mosquitoes of a particular species from a particular village) were calculated as the proportion of blood-fed mosquitoes that fed on human hosts. Human-fed mosquitoes included both single human blood meals as well as human-nonhuman mixed blood meals. (Escobar et al., 2020; Garrett-Jones, 1964; Keven et al., 2020; Overgaard et al., 2011). Differences in host utilization by district were analyzed by contingency table analysis. To test for variation in the propensity of the three main malaria vector species to feed on humans, non-humans and human-nonhuman mix blood meal types, a 3 x 3 contingency table analysis was carried out, and the percentage deviations of observed from expected frequencies were calculated. Host selection of a vector population was quantified using the theta statistic (q = p1/p2), which tested whether the ratio (q) of the proportion of a host species in mosquito blood meals (p1) and 61 proportion of the host in the village (p2) is different from unity (Aho & Bowyer, 2015). A host species was considered over-selected by the vector population if theta was significantly greater than 1.0 or under-selected if theta was significantly less than 1.0. A host species was considered to be fed on by the mosquitoes in proportion to its relative availability in the village if theta was not significantly different from 1.0. The theta statistical analysis was performed using the ci.prat.ak function of asbio package in Rstudio Version 1.1.456. The sporozoite rate (SR) was estimated as the proportion of mosquito heads-thoraces that tested positive for Plasmodium. The entomological inoculation rate (EIR) can be estimated indirectly from samples obtained by indoor resting mosquitoes, and also directly from samples obtained by the human landing catch (HLC) method (Kilama et al., 2014). In our study, samples from indoor resting collections were used to indirectly calculate the EIR using the formula: EIR = (M*SR*HBI)/N, where M is the mean number of blood fed mosquitoes per house, SR is Sporozoite rate, HBI is Human blood index and N is the mean number of human occupants per house per night. Annual EIR was estimated by multiplying the EIR by 365 days. 62 3.4. Results 3.4.1. Species composition Mosquitoes were collected in 203 household yielding 6,585 female Anopheles mosquitoes including 633 (9.6%) blood-fed. The blood-fed mosquitoes consisted of the following species: An. arabiensis (Overall: 44.1%, n=280; Namanolo: 59.2%, n = 243; Ntaja: 13.0%, n = 37), An. funestus (s.s.) (Overall: 33.5%, n=213; Namanolo: 26.7%, n = 110; Ntaja: 46.2%, n = 103), An. gambiae (s.s.) (Overall: 16.2%, n=103; Namanolo: 7.8%, n = 32; Ntaja: 30.0%, n = 70), and Anopheles parensis (0.3%, n=2, one each in Namanolo and Ntaja). Thirty-seven (5.8%) were not identified to species by morphological or molecular means. 3.4.2. Host selection and human blood index (HBI) Of the blood-fed Anopheles mosquitoes (n = 633), the blood meal host of 541 (85.5%) were successfully identified either by qPCR or direct sequencing (Figure 3.2 and Table 3.2). The remaining 92 (15%) were either non-reactors in PCR reactions (n=42), or amplicons generated by standard PCR failed to match any feasible host (n=50). Of the 541 mosquitoes whose blood meal host was successfully identified, 436 (81.0%) were solely human blood meals, 28 (5.2%) were solely goat blood meals, 11 (2.0%) were solely dog blood meals, and mixed blood meals were: 1 (0.2%) dog-goat, 5 (0.9%) dog-human, and 60 (11%) goat-human (Figure 3.2 and Table 3.2). 63 Figure 3.2. Blood meal identification to vertebrate host, including mixed meals, for Anopheles mosquitoes two sites combined. Humans were the most frequently identified blood-meal host for all three of the most abundant Anopheles species (An. arabiensis, An. funestus s.s. and An. gambiae s.s.), at approximately 70% of blood meal samples for each species (Table 3.2). Mixed blood meals comprising human and goat were present for all three mosquito species and ranged from 7.1 to 11.7% among species. Blood meals identified solely from goats ranged from 1.4 to 5.8% and were also found in all three species. Dog-only, and mixed dog-human or dog-goat blood meals, were present but uncommon. Differences in human or non-human (goat and dog) and mixed (human-nonhuman) host feeding by these three species, and the percentage deviations of observed from expected frequencies are shown in Table 3.3. Although the chi-square test was not significant (X2 =6.4, p=0.17), the percentage deviation values were suggestive that An. arabiensis tended to feed on nonhuman hosts more so than did An. gambiae (s.s.) and An. funestus (s.s.), whereas An. funestus s.s. tended to 64 underutilize nonhuman hosts compared to An. gambiae (s.s.) and An. arabiensis. Additionally, An. funestus (s.s.) tended to have fewer human-nonhuman mixed blood meals compared to the other species (Table 3.3). Table 3.2. Blood meal sources identified from Anopheles mosquitoes of Namanolo and Ntaja. Mosquito Species Blood meal source No. Human Dog Goat Human/Dog Human/Goat Dog/Goat Other tested n (%) n (%) n (%) n (%) n (%) n (%) n (%) An. arabiensis 280 195(69.6) 8(2.9) 11(3.9) 4(1.4) 30(10.7) 1(0.4) 31(11.1) An. gambiae 103 75(72.8) 0 6(5.8) 0 12(11.7) 0 10(9.7) An. funestus 212 152(71.8) 3(1.4) 3(1.4) 0 15(7.1) 0 39(18.4) An. parensis 2 0 0 1(50) 0 1(50) 0 0 An. spp 36 14(38.9) 0 7(19.4) 1(2.8) 2(5.6) 0 12(33.3) Total 633 436(68.9) 11(1.7) 28(4.4) 5(0.8) 60(9.5) 1(0.2) 92(14.5) Table 3.3. Percent deviation of observed blood meal frequencies from those expected by chi-square analysis, two sites combined. Species Human Non-human Human-nonhuman mix An. arabiensis - 4.2 +27 +15.5 An. gambiae -1.8 +7 +8.7 An. funestus +7.0 -42.5 -26.9 The results for analysis of host selection by the theta statistic are shown in Figure 3.3 In Ntaja, An. arabiensis and An. gambiae (s.s.) overselected goats and under-selected humans, whilst An. funestus (s.s.) selected these two host species in proportion to their relative abundance in the village. In Namanolo, by contrast, all three vector species selected both hosts in proportion to their relative abundance, although there was a nonsignificant tendency for over-selection of goats compared to humans. 65 Figure 3.3. Anopheles species blood meal host selection in relation to number of available hosts. Top panels; goat selection in relation to human, bottom panel; human selection in relation to goats. The black shaded circles are theta values with 95% CI bars. Red dotted line at 1.0 represents random selection in relation to availability of both hosts. The 95% CI bars represent deviation from random selection pointing to over-selection (theta significantly > 1.0) or under-selection (theta significantly < 1.0). The three abundant mosquito species (data from both villages combined) had similar HBI: An. funestus (s.s.) (96.5%); An. gambiae (s.s.) (93.5%); An. arabiensis (92.3%) (X2 =0.11, p=0.946). 66 Their combined HBI (i.e., regardless of species) was significantly higher in Namanolo with conventional nets (96.4%) compared to Ntaja with PBO nets (88.9%) (z =3.32, p = 0.001). 3.4.3. Entomological inoculation rate (EIR) Results of PCR analysis for P. falciparum infection showed that 15.6% (99/633) of the Anopheles mosquitoes (regardless of species) were positive in the head-thorax. The infection prevalence according to mosquito species was as follows: An. arabiensis 17.7% (50/283), An. funestus (s.s.) 12.3% (26/212), An. gambiae (s.s.) 22.2% (22/99), An. parensis 0% (0/2), and unidentified Anopheles spp. 2.6% (1/39). To estimate EIR, results from 203 houses with 1,106 occupants (97 houses, 488 occupants in Namanolo, 106 houses, 618 occupants in Ntaja) were used. EIR for both sites combined was equal to (633/203 * 16% * 94.0%)/(1106/203) or 0.09 infectious bites per person per night. For Namanolo, the estimated EIR was equal to (410/97 * 14.3% * 96.4%)/(488/97), or 0.11 infectious bites per person per night. For Ntaja, the estimated EIR was equal to (223/106 * 18% * 88.9%)/(618/106) or 0.06 infectious bites per person per night. Annualized EIR was 40 and 22 infectious bites/person/year in Namanolo and Ntja respectively with combined annual EIR of 0.09 translating into ~33 infectious bites/person/year. Household surveys revealed similar and high ownership rates for LLINs in the two sites (Namanolo: 92%, Ntaja: 90%, and nightly use rates (Namanolo: 75%, n = 109 households; Ntaja: 74%, n = 158 households). 67 3.5. Discussion Indoor mosquito sampling of rural houses in Namanolo and Ntaja in Balaka and Machinga Districts, respectively, of southeastern Malawi revealed three major malaria vector species. This finding was consistent with past studies in Malawi and southern Africa (Hunt et al., 2010; Mzilahowa et al., 2008; Spiers et al., 2002). The results here provide key malariologic transmission indices (HBI, EIR) that demonstrate the vulnerability of humans to bites of vector Anopheles mosquitoes, despite the presence and use of LLINs as the primary anti-malaria intervention. Although no species was numerically dominant, An. funestus (s.s.) and An. gambiae (s.s.) were relatively more common in Ntaja and An. arabiensis was more common in Namanolo. By contrast, indoor collections of mosquitoes at other locations close to both Namanolo and Ntaja, Lindblade et al., (2015) found An. funestus (s.s.) to be dominant, while An. arabiensis was next in abundance and An. gambiae (s.s.) was uncommon. These populations exhibited resistance to the synthetic pyrethroid deltamethrin, with 38% mortality in WHO bioassays for An. funestus (s.l.) and 53% mortality for An. gambiae s.l. (probably, An. arabiensis) (Lindblade et al. 2015). Despite these variations in mosquito species abundances between sites, An. funestus (s.s.) and An. gambiae (s.s.) are generally considered epidemiologically more important than An. arabiensis due to their well- documented anthropophilic and endophilic behaviors (Killeen et al., 2001; Orsborne et al., 2019, 2020; Takken & Verhulst, 2013). This study found non-host specific blood feeding of mosquitoes although high rates of feeding on human blood was observed by all three species, regardless of their variable phenotypes. These findings are more evident in the fact that human blood comprised most blood meals in unmixed conditions, regardless of species or study site, and that blood meals from other potential 68 sources (goats, dogs) were secondary, with goat blood meal being more frequent than dog. This observation is not surprising because it was commonly observed that people kept goats indoors in special rooms at night, probably for protection against theft, while dogs were left outside as guard dogs. This may explain the higher number of goat blood meals compared to dog blood meals. Killeen et al., (2001), in modeling mosquito populations of Tanzania and Kenya, demonstrated that there is a relationship between host availability and the amount of time that vectors spend seeking blood meals; by inference, hosts that require less time to locate will be fed upon more frequently. Orsborne et al., (2020), studying mosquito populations in Ghana, reached a similar conclusion, emphasizing that local host availability even for known anthropophilic malaria vectors, is a powerful driver for host selection. In Malawi, there have been no previous studies that consistently quantified relative availability of potential blood meal hosts. The high prevalence of human host blood-feeding by Anopheles species observed here is consistent with 2002 findings from southern Malawi, in which blood meals were nearly entirely from humans and secondarily from bovines (Mzilahowa et al., 2012). In northern and southern Zambia, similar high human host selection (>90%) and comparatively lower goat selection (<5%) by An. gambiae and An. funestus (s.s.) were observed (Das et al., 2017; Mharakurwa et al., 2007). In contrast, the dominant blood meal of malaria vectors around Lake Victoria in western Kenya was humans for An. gambiae (s.s.) and An. funestus (s.s.), but for An. arabiensis was predominantly bovine (Fritz et al., 2013) or equally bovine and human (Hamel et al., 2014). Through application of the “ratio of ratios” method of host selection, this study approached the problem of variation in host selection semi- quantitatively in order to assess host selection tendencies of these often behaviorally stereotyped species. 69 The high frequency of human blood meals detected in this study can be attributed to several factors, in particular bed net use practices. The higher HBI and EIR in Namanolo compared to Ntaja (96.4% vs. 88.9% and 0.11 vs. 0.06, respectively) could be due to widespread use of PBO- containing Olyset Net Plus in Ntaja, which have been shown to be more effective than convention LLINs against pyrethroid-resistant Anopheles populations (Mzilahowa et al., 2016; WHO, 2018) Lindsay et al., (2021) have suggested that the underlying mechanism of PBO-containing LLINs may simply be that they are more toxic, rather than overcoming insecticide resistance. Regardless, other randomized field trials in Tanzania and Uganda have shown significantly lower human infection prevalence where LLINs with PBO were distributed (Protopopoff et al., 2018; Staedke et al., 2020). Although the entomological mediators of these reductions were not investigated, they are likely due to reduced transmission intensity. In the present study, the lower HBI of An. arabiensis and An. gambiae (s.s.) in Ntaja than Namanolo could also be explained by the use of LLINs with PBO in Ntaja, which apparently increases their susceptibility to the insecticide as explained above (Mzilahowa et al., 2016; Ogola et al., 2017). In the only other study analyzing blood meals of Anopheles vectors in Malawi, conducted in Chikwawa district (southern Malawi) during 2002 prior to any mass distribution of insecticide- treated nets, most blood meals were from humans, with relatively few coming from bovine or mixed human-bovine feeding (Mzilahowa et al., 2012). The 2002 HBI estimates for the three dominant malaria vector species were similar to what was found in the present 2019-2020 study, despite there now being a long history of malaria control and LLIN use. The species-specific HBI estimates for 2002 vs. 2019-2020 were: An. arabiensis, 85.0% vs. 92.3%; Anopheles gambiae (s.s.), 99.2% vs. 93.5%; and An. funestus (s.s.), 99.2% vs. 96.5%. However, the estimated EIR in the present study (33 infectious bites per person per year) was lower than that reported by 70 Mzilahowa et al., (2012) (183 infectious bites per person per year). Both studies used PCR-based detection of sporozoite infection in the head-thorax of individual mosquitoes, although prevalence was lower in the 2002 investigation (4.9%) compared to the present study (16.0%). However, indoor mosquito density was lower at the present study sites, thereby reducing the EIR. Another more recent study in Chikwawa, done during the implementation of a community-based control program, showed that 4 of 91 Anopheles (4.4%) tested by PCR were positive for P. falciparum infection during the rainy season, with an estimated EIR of 13.5 infectious bites per person per year (Mburu et al., 2019), suggesting a reduced EIR in that region. Molecular-based approaches to blood meal analysis to detect vertebrate host feeding have advanced since the review of this topic (Fritz et al., 2013; Kent, 2009; Keven et al., 2020; Logue et al., 2016)). At the forefront of this advance has been development of qPCR methods using host- specific probes by either TaqMan or SYBR green detection (Keven et al., 2020; Tajadini et al., 2014). However, host species-specific probes in multiplex qPCR targeting Anopheles blood-meal hosts were developed only recently (Keven et al., 2020). The use of species-specific probes, designed within a qPCR format here, favored the detection of single and multiple (i.e., mixed) blood meals in this study. By screening all blood meals for human blood, and then analyzing by PCR, amplicon sequencing, and BLAST search matching those blood meals not reacting to the human probe, it was possible to reveal the narrow breadth of dominant hosts being utilized by the Anopheles community, and then using qPCR to reveal the extent of multiple feeding. This combinatorial approach indicated that ~12% of the blood meals were mixed feeding of human and goat (10.8%), human and dog (1%) or goat and dog (0.2%). 71 The host-selection analysis showed that, in both sites, two of the Anopheles species fed more often on goats than humans in proportion to availability of these hosts. An. arabiensis and An. gambiae (s.s.) over-selected goats and under-selected humans, while An. funestus (s.s.) selected the two hosts about equally (i.e., randomly) in proportion to their availability. These results are not surprising, although An. arabiensis is reportedly more zoophilic, while An. funestus (s.s.) is more anthropophilic (Sinka et al., 2010) plasticity and or opportunistic tendencies have been observed in various Anopheles species (Keven et al., 2017; Killeen et al., 2001; Orsborne et al., 2019, 2020; Takken & Verhulst, 2013). The explanation to the relatively higher goat feeding in indoor mosquito samples is consistent with goats being kept indoors at night, and malaria control interventions in the area (LLINs) (PMI, 2018). These two activities provide easy accessibility to goat blood meal and makes it more difficult to access human blood meal due increased mosquito- goat contact and reduced mosquito-human contact (Killeen et al., 2001). The switch in host utilization is indicated by the reduced access to human blood meal and increase in the utilization of the non-human hosts. The comparable increase in mixed blood meal may also suggest disruption in feeding either due to LLINs’ activity or otherwise, pushing the mosquito to get a full blood meal from other hosts. Either way this is one of the few studies in Malawi to report blood meal analysis including detection of mixed blood meals. This study will prompt more research in blood meal studies in Malawi to document the range of blood meal hosts, especially those involving goat blood meal which is rarely reported in literature. The findings of this investigation suggest important implications for Plasmodium transmission and malaria control. Multiple host feeding by some Anopheles females might allow for increased survival and reproduction (Logue et al., 2016; Stone & Gross, 2018). The presence of multiple malaria vector species that successfully obtain human blood meals could lead to an increased 72 Plasmodium transmission by increasing the basic reproductive number (Ro) (Das et al., 2017; Kilpatrick et al., 2006). More widespread use of LLINs, particularly with PBO, could help reduce transmission, but this intervention alone is unlikely to reduce malaria incidence in this meso- endemic setting to acceptable levels where elimination can be contemplated. Residual Plasmodium transmission and weakened intervention efforts (Cohen et al., 2012) are likely to persist into the future. 73 3.6. Conclusion This study has shown that, in southern Malawi, human blood comprises the bulk of the blood meals of the three species of Anopheles vectors, yet dog and goat blood meals are also present and commonly mixed with that of humans. Host selection analysis revealed that goats were over- selected compared to humans in proportion to host availability. This could be a direct result of LLIN usage. The presence of mixed-blood meals showed the adaptability of these vectors to switch hosts to obtain a full blood meal, possibly reducing effectiveness of malaria control interventions. The frequent use of humans as a blood meal source elevates the human blood index and consequently the entomological inoculation rate, sustaining malaria incidence. Some evidence suggests that pyrethroid-based LLINs containing PBO reduced mosquito-human contact, as the HBI was significantly lower at the site using these nets. Nonetheless, estimates of EIR remain high, indicating that transmission is well sustained despite the use of PBO-containing LLINs. Other factors, such as net durability and use may be reducing effectiveness of interventions. 74 CHAPTER 4 : GENOTYPING OF ANOPHELES MOSQUITO BLOOD MEALS REVEALS NONRANDOM HUMAN HOST SELECTION: IMPLICATIONS FOR PLASMODIUM FALCIPARUM TRANSMISSION, MALAWI Manuscript Rex B. Mbewe, John B. Keven, Charles Mangani, Mark L. Wilson, Themba Mzilahowa, Don Mathanga, Clarissa Valim, Miriam K. Laufer, Edward D. Walker, Lauren M. Cohee. 4.1. Abstract Analysis of mosquito blood meals to determine the extent of human host utilization relative to animal hosts extends to genotyping of human blood meals to assess patterns of vector-human contact and characteristics of individual human hosts. This approach has improved the understanding of parasite transmission in several vector-borne diseases systems including malaria. This study used a microsatellite-based human-genotyping method to implicate within the human population, demographic groups that are the main drivers of malaria parasite transmission from human to mosquitoes. The study was conducted in two districts of moderate to high malaria transmission in southeastern Malawi. Household surveys garnered human demographic information. Blood samples obtained by finger prick from consented participants were absorbed onto filter paper. Indoor resting, blood fed female Anopheles mosquitoes were sampled from these same houses. Genomic DNA from human blood spots and mosquito blood meals was subjected to genotyping methods to generate genetic profiles from each individual sample. Using a genotype matching algorithm written in R, the profiles from human and mosquitoes were matched to identify the unique human sources of blood meals. Polymerase chain reactions (PCR) were used to detect Plasmodium falciparum DNA 75 in human and mosquito samples. The results were used to identify the human demographic grouping which was most frequently bitten and had highest malaria infection prevalence. Anopheles females selected human hosts non-randomly and fed on more than one human in 10% of the blood meals. Few individuals contributed most of the blood meals to the Anopheles vector population, and more males than females were selected, even though males were a smaller fraction of the population. Children £ 5 years and adults ³16 were under-selected for blood meals compared to school children (6 to 15 years old). Mosquitoes that had fed upon males of the school age group had the highest P. falciparum infection rate in their abdomens. These results show that humans of the 6-15 years age group, particularly males, are drivers of Plasmodium falciparum infection from humans to mosquitoes because of the blood host selection outcome. This observation is relevant to community-based malaria control and prevention, as it indicates the need for deliberate efforts targeting males of the school age group. 76 4.2. Introduction Patterns of mosquito utilization of individual humans for blood meals, such as biases towards feeding on particular demographic groups in the human population, can have profound impacts on malaria epidemiology by allowing transmission to persist even in the presence of active control measures such as widespread distribution and utilization of long-lasting insecticidal nets (LLINs) (Dye & Hasibeder, 1986; Hasibeder & Dye, 1988; Smith et al., 2007; Woolhouse et al., 1997; Keven et al., 2021). One approach to understanding human host utilization patterns is through mosquito blood meal analysis (Borland & Kading, 2021). Mosquito blood meal analysis has been used in many studies for various reasons, including investigations of blood meal sources (especially to determine the human blood index, or fraction of the hosts that are humans) as well as determination of proportions of mosquito infections originating from different demographic groups in the human population ( Gonçalves et al., 2017; Escobar et al., 2020). In Malawi, school-age children are frequently infected with Plasmodium falciparum malaria and carry gametocytes, the gametic parasite stage required for infective human-to-mosquito- transmission, suggesting that this age group is an important reservoir of infection even when children are asymptomatic (Ali et al., 2015; Walldorf et al., 2015; Coalson et al., 2016, 2018; Cohee et al., 2021). This observation makes it imperative to conduct studies in Malawi that assess the contribution of certain demographic groups to the transmission of malaria parasites from humans to mosquitoes. Genetic profiling of mosquito blood meals has been applied elsewhere in three important ways of understanding malaria transmission that are relevant to this pressing issue: (1) to identify the most frequently bitten population group, (2) to assess the frequency distribution of mosquito biting on individuals, and (3) to estimate the proportions of multiple blood meals on 77 different human hosts (Keven et al. 2021). This genetic profiling method utilizes microsatellite genetic markers, or short tandem repeats (STR) of nucleotides, which occur at thousands of Mendelian loci in the human genome with multiple alleles operating at each locus (Willems et al., 2014). The resultant genetic variation provided by the combination of numerous loci and multiple alleles provides for numerous applications in research such as studies of population genetic structure (Rosenberg et al., 2002) and in forensic sciences (Mirghani et al., 2010; Smith et al., 2017). Human accessibility and vector preferences are factors that determine which human hosts are most frequently bitten. We hypothesized that school-age children in Malawi are the predominant sources of Anopheles blood meals. Previous studies have suggested that a greater proportion of blood meals are taken from adults and older children than young children and infants (Carnevale, Frézil, Bosseno, Le Pont, & Lancien, 1978; Muirhead-Thomson, 1951) partially because of differences in body surface area. Studies have also shown differential use of LLINs by age, with school-age children being least likely to sleep under nets in Malawi (Buchwald et al., 2016; Walldorf et al., 2015). Thus, school-age children are likely to be bitten more frequently based on body surface area and limited LLIN use. In addition, previous studies reported that Plasmodium-infected individuals are more attractive to vectors than uninfected individuals (De Moraes et al., 2014; Lacroix et al., 2005). In this study, we aim to characterize the human sub-populations responsible for driving malaria parasites into the mosquito populations thereby propagating malaria transmission in the community. This was achieved by matching human genetic profiles analyzed from mosquito blood meals to those analyzed from human blood samples. 78 We hypothesize that (1) Mosquito feeding on individual humans is nonrandom, and (2) Mosquito feeding is preferential on certain human population groups (males and 6-15 years old), classified by age and gender in the study area and these groups drive malaria transmission. 79 4.3. Methods 4.3.1. Study site The study was conducted in Machinga and Balaka districts in the southeastern part of Malawi. The catchment area in the two districts was a 10-kilometer radius around Ntaja health center in Machinga and Namanolo health center in Balaka. These districts were chosen because they have moderate to high malaria transmission throughout the year (Mbewe et al. 2021). The climate is characterized by high temperatures and seasonal rainfall. The residents of the area are mostly subsistence farmers whilst others ply trade in market centers. Malaria transmission is highest in areas of high temperature and seasonal rainfall, from October through April (Government of Malawi, 2015). 4.3.2. Sample collection and processing Household surveys. Monthly surveys of a household-based cohort were conducted to collect demographic and malariometric data. A total of 130 households participated, 73 in Namanolo and 57 in Ntaja. The head of each household was consented to participate in a questionnaire designed to gather information on number of people per household, name, sex and date-of-birth of each household member. Blood droplets were collected by finger prick from all consented household members, dried on Whatman filter paper, and stored under cool laboratory conditions. Mosquito sampling. Indoor resting, female Anopheles mosquitoes were sampled from the consented households. Households were sampled three times each period from May-June 2019, October-November 2019, and December 2019-January 2020. Beginning in February to April of 2020, only a subset of households in each site were sampled once every two weeks. Blood fed mosquitoes in the households were sampled until none were present using battery powered 80 aspirators (Model 1419 John W. Hock Company, Gainesville, Florida, USA) and breath-operated aspirators. In 2020, in addition to aspiration methods, mosquitoes were also sampled by standard miniature CDC light traps (Model 512; John W. Hock Company, Gainesville, Florida, USA), and pyrethrum spray catch (Odiere et al., 2007). DNA Extraction. Each blood fed Anopheles mosquito was bisected into head attached to thorax (hereafter, “head-thorax”), and abdomen, using sterile technique. Genomic DNA was extracted from the mosquito abdomens and mosquito head-thorax separately, and from human blood spots using the DNeasy® Blood & Tissue Kit (Cat. No. 69582; Qiagen, Valencia, CA, USA). Anopheles species identification. Mosquitoes morphologically identified as members of the An. gambiae sensu lato (s.l.) or An. funestus species complex were subjected to a polymerase chain reaction (PCR) following the method of Walker et al., (2007) to identify the species, following modifications in Mbewe et al., (2021). Plasmodium falciparum detection. Presence of Plasmodium falciparum parasites in the human blood samples and the mosquitoes’ heads-thoraces and abdomens was tested using the molecular based method described in Mbewe et al., (2021). Identification of human blood meals. DNA obtained from blood-fed mosquito abdomens were subjected to a qPCR method containing primers (forward 5′-GGCCTGTTCCTCCCTTATTT-3′, reverse 5′-TACACAGGGCTTCCGAGT-3′) and probes (FAM- ATGGAGTCTGTGTTCCCTGTGACC-QSY) that detects human DNA (Keven et al., 2020). 81 4.3.3. Microsatellite genotyping and profile matching Human-derived mosquito blood meals and human blood samples were subjected to microsatellite genotyping method (Keven et al. 2021). The following 24 well-characterized, tetranucleotide microsatellite loci were used for genotyping: D3S1358, D1S1656, D2S441, D10S1248, D13S317, D16S539, D18S51, D2S1338, CSF1PO, TH01, vWA, D21S11, D7S820, D5S818, TPOX, D8S1179, D12S391, D19S433, FGA, D22S1045, Penta E, Penta D, and DYS391, plus an X-linked amelogenin sex-determining marker (Oostdik et al., 2014). Amplification of these markers was performed using a commercially available and validated multiplex PCR kit from Promega (PowerPlex Fusion System; catalog no. DC2402) that contained locus-specific fluorescent- labelled primers (Oostdik et al., 2014). Each locus had two alleles, one from each parent. Alleles were analyzed by capillary electrophoresis (ABI 3730 Genetic Analyzer, Applied Biosystems, Foster City, CA) with LIZ 500 (Applied Biosystems, Foster City, CA) as the internal size standard. GeneMapper software version 4.1 (Applied Biosystems) was used to visualize the allelic sizes of all the loci in each sample, creating the genetic profile of the sample (Appendix 5.1). For each sample (i.e., human-fed mosquito or human blood), all observed allele sizes at each locus were listed and together served as the genetic profile (“fingerprint”) of the person. While different mosquitoes that fed on the same individual had the same genetic profile, each study participant who donated a blood sample had a unique genetic profile. The genetic profile of a mosquito blood meal from a house was compared to the genetic profile of all members of the household and the entire human survey, to determine which (if any) person was fed on by the mosquito. An example of a genetic profile generated by this method is shown in Appendix 4.2. 82 4.3.4. Data analysis Data analysis was performed using RStudio (Version 1.1.456; https://www.R-project.org/). An R code for matching genetic profiles was developed and applied in the analysis. Briefly the R script involves loop functions and conditional statements to compare the genotype of each locus in a query sequence (i.e., a genetic profile) to its corresponding locus in a subject sequence (i.e., another genetic profile). The similarity of the two genetic profiles was expressed as the proportion of identical loci (i.e., same alleles) times 100. For example, 19 identical loci divided by 24 total loci multiplied by 100 gives 79% profile similarity. In principle, genetic profiles from two blood-meal specimens that originated from a same human source should have 100% profile match. Therefore, it could be expected that match values < 100% should indicate blood meals from different individuals. However, since some blood meal specimens could yield insufficient human DNA (e.g., due to very small mosquito blood meal volume) or false mismatches due to “allele dropout” (a failure of the alleles in a locus to be detected) (Findlay et al., 1998) the ideal 100% match is not always attained. To account for these errors and to minimize their effects in obtaining a reliable comparison or match of genotypes, a value less than 100% has to be used as the criterion for establishing a match. To determine this value, pairwise percent profile match analysis was performed on the genetic profiles of individual humans in the study sites. This generated n(n-1)/2 profile match results or values, where n is the total number of humans sampled on a site. A value higher than the highest value in the pairwise match output (excluding match results of monozygotic twins which would be 100%) was the criterion below which two genetic profiles were considered different (Keven et al., 2021). The number of different human individuals in the blood-meal sample represented the number of different human individuals in the sample. The frequency of occurrence of each unique genetic 83 profile in the blood-meal sample represented the number of mosquitoes that fed on each individual human. These data were used to construct frequency distribution histograms that relate the number of different human individuals (y-axis) to the number of blood-meals they provided (x-axis). The observed frequency distributions were fitted to zero-truncated Poisson and zero-truncated negative binomial frequency distribution models using the functions zerotrunc and rootogram of the package countreg in RStudio (Kleiber & Zeileis, 2016). The fit of the two distributions was compared by chi-squared test to determine if selection of humans by mosquitos was random (Poisson) or aggregated (negative binomial). The study participants who donated their blood sample to analyze their genetic profile were classified into 3 age groups, namely those £ 5 years of age, those between 6-15 years of age, and those ³16 years of age. This age classification is commonly practiced in malaria epidemiological studies to assess risk of infection among age groups (Waldforf et al. 2015). Genetic profiles of human-fed mosquitoes were compared to the genetic profiles of human individuals to identify the person who was bitten by the mosquito. The sex of a person in the blood meal could be determined using the sex-specific genetic marker but identification of the person’s age could not be done based on a genetic marker. The age of the person in the blood meal was determined by matching the blood meal profile to the profiles of human individuals (whose age were recorded). The proportion of each sex and age group observed in the mosquito blood meals was compared with its expected proportion (the proportion of individuals of that group in the study site) using two-tailed binomial tests. 84 4.4. Results 4.4.1. Human genetic profiling Genetic profiles of 243 sampled human individuals (99 from Namanolo and 144 from Ntaja) were generated. A comparison of each human genetic profile with all other profiles to determine the degree of matching, represented as the percent profile match, resulted in 29,161 pairwise profile match values. There were 20 unique percent match values ranging from 0-79%, each with a varying frequency of occurrence (Table 4.1). The lowest value of percent match was 0% with 0.09 probability of occurrence. This result means that 9% of all the pairwise comparisons were between individuals with no identical genotype at any locus. The highest percentage match value was 79% (i.e 19/24 matched loci) with a 10-5 probability of occurrence (Table 4.1); there were only two such matches. Because it was highly unlikely (probability < 0.00007) for two individuals in the study to have matches greater than 79%, this value was used as a criterion for deciding whether two genetic profiles in blood meals originated from the same person or not. Hence matching values greater than 79% was indicative of the human source of the blood meal 85 Table 4.1. Pairwise testing, percent match and probability of having similar genetic makeup. % Match 0 4 8 12 17 21 25 29 33 38 42 46 50 54 58 62 67 71 75 79 Frequency of occurrance 2612 5161 7397 6470 3813 1989 832 376 208 133 69 47 14 12 14 8 2 1 1 2 Probability of occurance 0.090 0.177 0.254 0.222 0.131 0.068 0.029 0.013 0.007 0.005 0.002 0.00161 0.00048 0.00041 0.00048 0.00027 0.00007 0.00003 0.00003 0.00007 86 4.4.2. Genotyping human blood meals Of 501 Anopheles spp. blood meals found to contain human blood, 480 (95.8%) yielded human genetic profiles. Of these, 436 (91%) were found to contain a single human genetic profile. The remaining 44 were found to contain profiles from two or more humans. When the single-human blood meal genetic profiles were compared with the profiles of human residents (n = 243 individuals), a total of 183 blood meals matched profiles of household residents whilst 253 successfully genotyped blood meals did not match any profiles of the residents represented in the sample. The blood meals with multiple human sources could not be matched to any human profile owing to the presence of more than two alleles at many loci. There were 633 female Anopheles mosquitoes identified to mosquito species: Anopheles arabiensis (279, 44.1%), Anopheles gambiae s.s. (103, 16.2%), Anopheles funestus (212, 33.5%), Anopheles parensis (2, 0.3%), and unidentified Anopheles species (37, 5.8%). Our analysis of mosquito behavior focused on the Anopheles genus rather than species due to great variations in species representation, where other species of Anopheles mosquitoes had their blood meal profiles not matching the human profiles. 4.4.3. Frequency distribution of human blood meals The unique genetic profiles identified in the blood meal sample represented different human individuals that the mosquitoes in the sample fed upon. The frequency distribution of blood meals taken from these individual humans as reflected solely by genotyped but nonmatched blood meals, showed that some individuals were more frequently bitten than others, such that there were few blood meals on most individuals, and many blood meals on few individuals (Figure 4.1). The number of blood meals per individual person ranged from 1 to 51. Although this pattern was 87 evident for males and females, the three highest number of blood meals were from male individuals. Frequency of mosquito blood meals(bites) per person all sites combined (n=436) 80 70 Males Females 60 Frequency 50 40 30 20 10 0 1 2 3 4 5 7 8 9 10 12 15 19 51 Number of blood meals per person Figure 4.1. Frequency distribution of number of blood meals on individual male and female humans (n=436) taken by Anopheles mosquitoes sampled in Ntaja and Namanolo communities of southeastern Malawi. The frequency distribution did not fit the Poisson distribution, which would indicate a random pattern of individual human host selection; rather, it fit well the negative binomial distribution, which indicates a nonrandom and aggregated (or clumped) pattern of human host selection (Figure 4.2). 88 Poisson fit Neg. binom fit X2- = 82.396, df = 6, X2- = 9.4306, df = 9, P = 1.142e-15 P = 0.3985 Frequency Number of blood meals per person Figure 4.2. Fits of the frequency distribution of number of human blood meals taken per person from Anopheles mosquitoes sampled in houses using all data (Insert: distributions in Ntaja and Namanolo showing similar trend) in communities, southeastern Malawi. 4.4.4. Mosquito human host selection by sex and age category When the proportion of male and female humans in the mosquito blood meals was compared with their relative proportion in the village (expected proportion), the results revealed that males contributed a significantly higher proportion of blood meals and their female counterpart contributed a significantly lower proportion of blood meals than expected. Without considering their relative proportion in the village, and focusing only on the blood meal proportion, there were significantly more male-fed than female-fed blood meals (Figure 4.3). Comparison by binomial tests of the proportion of blood meals obtained from the three age groups to their expected proportion (i.e., their relative proportion in the village) showed that there were fewer blood meals from individuals £ 5 and ³16 years old. In contrast, the proportion of blood meals obtained from individuals in the 6-15 years old group was higher than expected but this difference was not statistically significant (Figure 4.4a). Comparison (Chi-square tests) of the relative proportion of the age groups in mosquito blood meals revealed that humans in the age group 6-15 years old 89 contributed a significantly high proportion of blood meals than did the younger and older age groups (Figure 4.4b). Comparing male and female proportions in human survey and mosquito blood meals, all site combined 0.7 z = -9.3, P =< 0.001 z =9.3, P = < 0.001 0.6 X2 = 9.34, P = 0.002 0.5 Proportion 0.4 0.3 0.2 0.1 0 male female survey blood meal Figure 4.3. Proportion of Anopheles blood meals (red) taken from males and females humans compared to the proportion of the two human sexes in the household survey (blue). Results of Chi-square tests comparing the proportion of males and females in the blood meals to their proportion in the household survey, and of male versus female blood meals are shown inside the plot. Note, data from both sites (Namanolo and Ntaja) were combined in this analysis. 90 (a) (b) 0.7 z = - 1.28, P = 0.201 0.7 * X2 = 16.65, P = 0.0002 0.6 0.6 0.5 0.5 z = - 4.38, P < 0.0001 0.4 0.4 Proportion 0.3 * 0.3 z = - 2.28, P= 0.023 0.2 0.2 0.1 0.1 * 0 0 <5 6-15 > 16 > <5 6-15 > 16 > survey Blood meal All blood meals Unique blood meals Figure 4.4. (a) Comparisons of the proportion of blood meals taken from humans in three age groups in relationship to the number of humans in those age groups as determined by household survey. (b) Comparison of the proportion of blood meals taken from the three human age groups along with Chi-square results of test of homogeneity of blood-meal proportion. Data from both sites (Namanolo and Ntaja) were combined in this analysis. 4.4.5. P. falciparum infection in mosquito blood meals and the human population Plasmodium falciparum DNA was detected by PCR in abdomens of blood fed Anopheles (total, N = 160, 37% positive), head-thorax of blood fed Anopheles (total, N = 85, 19 % positive), and in human blood spots (total, N = 27,11 % positive). The proportion of abdomens and head-thorax of Anopheles mosquitoes positive for P. falciparum was not significantly different between sexes of the human host as determined by genotyping the blood meals present in the abdomen (Figure 4.5a). The proportion of human blood spot samples positive for P. falciparum was not different by sex of the human source of the blood (Figure 4.5b). Interestingly, the proportions of infections were higher in the mosquitoes than in the human blood spot regardless of mosquito body part (Figure 4.6). 91 (a) (b) 0.25 0.08 0.07 0.2 0.06 0.15 0.05 Proportion 0.04 0.1 0.03 0.05 0.02 0.01 0 male female male female 0 abdomen head male female survey 2 X = 3.57, p = 0.059 2 X = 0.868, p = 0.351 X2 = 0.145, p = 0.703 Figure 4.5. Proportion of abdomens and head-thorax of Anopheles mosquitoes positive for P. falciparum classified by whether the sex of the human host in the blood meal was male or female. (b) Proportion of human blood spot samples positive for P. falciparum classified by sex of the human source of the blood. Chi-square tests of homogeneity of proportion of infections between the two sexes are shown in the plots. Data from both sites (Namanolo and Ntaja) were combined in this analysis. Pf positivity in Mosquitoes with blood meal and human Pf Pf positivity in Unique Mosquitoes with blood positivity by sex all sites combined (b) meal Vs Pf positive humans in population, all sites combined (adjusting for multiple bites) 0.3 0.3 Mosq. Pf positivity 0.25 0.25 Mosq. Pf posotivity human Pf positivity 0.2 0.2 human Pf positivity Proportion 0.15 0.15 0.1 0.1 0.05 0.05 0 0 male female male female male female male female abdomen head abdomen head Figure 4.6. The proportion of Anopheles mosquito abdomens and head-thorax body sections in relation to human blood samples positive for P. falciparum for all samples regardless of human genotype, classified by male or female. Namanolo and Ntaja communities, southeastern Malawi. 92 For all the three age groups, the proportion of Anopheles abdomens positive for P. falciparum were not significantly different from the proportion of human blood that were positive (Figure 4.7a). However, the proportions of the head-thorax positive for P. falciparum were significantly higher than were human blood for the two older age classes (Figure 4.7a). Comparisons of the proportion of Anopheles mosquito body part (abdomen with blood; head-thorax) positive for P. falciparum across human age group of the genotyped blood meal showed higher infection proportions in the 6-15 years old group compared to the £ 5 years old and ³16 years old groups (Figure 4.7b). (a) (b) X2 =0.252, X2 = 4.904, 0.08 p = 0.615 p = 0.027 0.08 0.07 0.07 X2 = 10.62, P = 0.005 0.06 0.06 0.05 0.05 Proportion X2 =0.109, 0.04 P = 0.741 X2 = 4.87, 0.04 X2 =0.245, X2 =0.506, P = 0.027 X2 = 7..587, P = 0.023 0.03 P = 0.621 0.03 P = 0.477 0.02 0.02 0.01 0.01 0.00 0 <5 6 and 15 16 > <5 6 and 15 > 16 > <5 6 and 15 16 > <5 6 and 15 >16 > abdomen head abdomen head popln Pf positivity Mosq. Pf positivity Figure 4.7. Comparisons of the proportion of Anopheles mosquito body part (abdomen with blood; head-thorax) positive for P. falciparum classified by age category and compared to the proportion of the human population positive by age category. (b) Comparisons of the proportion of Anopheles mosquito body part (abdomen with blood; head-thorax) positive for P. falciparum classified by human age group of the genotyped blood meal. 93 4.5. Discussion The results from the study have shown nonrandom pattern of mosquito feeding on individual humans and that the mosquitoes were feeding more on certain human population groups that is, males and children aged 6-15 years old. Genetic profiling of mosquito blood meals to investigate patterns of contact between human hosts and mosquito vectors of diseases, including malaria vectors, has been applied in numerous contexts (Chow-Shaffer et al., 2000; Edman et al., 2003; Guelbéogo et al., 2018; Paul et al., 2001; Scott et al., 2006; Soremekun et al., 2004; Gonçalves et al., 2017). Most of the previous studies used 10 or fewer loci in the construction of the genetic profiles and did not consider the impact of this limitation on error rates in matching genotypes. The primary limitation in using fewer number of loci is the reduction in the power to discriminate related individuals. The current study is the second to use a greater number of loci (24) in the construction of genetic profiles. The first known study to apply this method of investigation with 24 microsatellite loci to Anopheles vectors of malaria was conducted in PNG (Keven et al., 2021). The use of more microsatellite loci increases power to discriminate between genetically related individuals, and decreases the possibility of error when allele dropouts occur (Keven et al., 2021). The assessment used here is robust for these reasons. In our study we were able to identify human sources of blood meals by matching human genetic profiles to mosquito blood meal profiles, and by matching profiles from mosquito blood meals to each other. More than half of the mosquito blood meals did not match any human profile provided by blood spots in the human survey. This could possibly be due to indoor resting behavior of the mosquitoes that might have taken blood meals outdoors from non-household members or blood meals from non-participating household members. Harrington et al., (2014) found that the 94 majority of blood meals of Aedes aegypti in villages in Thailand came from nonhousehold members, a finding attributed to peddlers, visitors, and passersby in the community during the daytime hours, when Aedes aegypti tends to seek out blood hosts. We did not assess the volume of traffic in households in the households in Ntaja and Namanolo at night, in order to determine the number and diversity of people who might have been in or near the houses at night and into early morning hours when Anopheles mosquitoes seek hosts, but the blood meal genotyping data suggest that such human movement was considerable. The observation of a non-random and aggregated pattern of human host utilization emerged in other studies using a blood meal genetic profiling approach in different mosquito-borne disease systems such as those involving Anopheles, Culex, and Aedes species (Edman et al., 2003; Guelbéogo et al., 2018; Harrington et al., 2014; Paul et al., 2001). The mosquito populations in this study exhibited markedly non-random human utilization for blood meal source, apparent at both the individual and household level, meaning certain individuals and households were at greater risk to infectious Anopheles bites than were others. This finding was most likely due to variation in accessibility of the mosquitoes to individuals; and variation in mosquito access to houses due to such factors as distance from larval habitat, presence of insecticide-treated bed nets in houses, cooking inside or outside of houses, and presence of open or blocked eaves which provide or block entry of mosquitoes (McCann et al., 2017). Differences in human behavior such as bed-net usage and late-night activity may be the cause of differences in the accessibility of individuals to the mosquitoes (Buchwald et al., 2016; Walldorf et al., 2015; Bayoh et al., 2014). Also, humans are most likely to encounter female Anopheles where the mosquitoes themselves aggregate. This is because humans likely undertake particular activities during Anopheles biting 95 times, and often these activities are related to their age and sex (Rodríguez-Rodríguez et al., 2021; Smith et al., 2004). The study showed that males were proportionately over-utilized for blood meal compared to females. Further, the youngest and oldest age groups were under-selected, and the school age group was selected in higher proportion than these two groups. These results suggest that the males of school age group (6-15 years old) were the most frequently bitten population group in the study area. The disproportionate representation of this demographic group in the study area aligns with results of studies conducted elsewhere; for example, in Papua New Guinea, the Anopheles mosquitoes obtained more blood meals from males and individuals of the 15–30 years age group compared to females or other age groups. In that study, an interesting observation was the under- representation of the youngest age group (< 15 years old), which constituted a large proportion of the village censuses (52%) in the blood meals (Keven et al., 2021). In Tanzania, males and individuals ³ 20 years old were fed upon more than expected by An. funestus and An. gambiae s.s., whereas females and those < 20 years old were bitten less frequently in a village with bed nets, while in a village without bed nets, such variations were not observed (Soremekun et al., 2004). In a Kenyan study, individuals < 20 years old received more bites than expected compared to those between 20 – 50 years old, but no variation was observed between sexes (Scott et al., 2006). Gonçales et al., (2017) conducting blood meal analysis and genotyping study in areas of Burkina Faso and Kenya, found that children aged 5-15 years old were more often bitten than those of the other age groups. These variations amongst studies suggest that local conditions and study design will influence outcomes and resultant conclusions. The present study is internally consistent and compares well with recent epidemiologic studies of age-specific malaria in Malawi (Mangani et al., 2021). The common agreement in all these studies to the current 96 one, is that different population groups received proportionately different mosquito bites as reflected by blood meal analysis. In the current study the age group providing most of the blood meals was the 6 -15 years old group. The presence of non-random distribution of vector blood meal has strong epidemiological implications. Several studies on mathematical modeling of malaria transmission show that where non-random distribution of vector bites among human hosts exists, the result is an increase in the Basic Reproductive number (Ro), causing the disease to persist ( Dye & Hasibeder, 1986; Woolhouse et al., 1997; T R Burkot, 1988) even in the presence of control intervention programs such as bed nets (Smith et al., 2007). Therefore, targeted interventions focusing on those human demographic groups biasedly over-represented/selected by vector blood meals may help greatly in reducing malaria transmission and infection rates. A considerable number of the blood meals in mosquitoes from multiple individuals were also observed. The presence of multiple feeding in the mosquitoes could be due to interrupted mosquito feeding which is caused by several factors including human defensive behavior, bed net availability, bed net usage and sleeping times. The presence and use of bed nets may cause irritation or excitation to the mosquitoes due to the action of the insecticide or its repellant effect and the individual human’s intolerance to mosquito bite. Hence the mosquito may not be in a position to stay still for the duration of blood feeding. Blood meals obtained while the individuals are awake are likely to be disrupted than those obtained late at night when individuals are fast asleep. Individuals that are more intolerant of mosquito bites are more likely to disrupt the mosquito blood feeding process (Anderson & Brust, 1997; Boreham & Garrett-Jones, 1973). In 97 the current study, the proportion of multiple feeding by Anopheles mosquito species were similar to other studies. In Papua New Guinea, Burkina Faso, and Kenya the proportions of multiple blood meals ranged respectively from 6-15%, 11-18% and 14.5% (Keven et al., 2021; Burkot et al., 1988; Gonçales et al., 2017). In similar studies done in An. funestus and An. gambiae in two Kenyan villages, the proportions ranged from 2-14%, (Scott et al., 2006) and 10% in a Tanzanian village (Soremekun et al., 2004). Other studies reported similar percentages in Culex and Aedes populations, (Edman et al., 2003; Harrington et al., 2014; Paul et al., 2001). The one study that showed an exception was done for an Aedes aegypti population in Thailand where a much higher proportion about 45% was observed (Chow-Shaffer et al., 2000). In the latter case, one might expect much more interrupted feeding of a daytime biting mosquito when people are active and awake, compared to the nighttime biting Anopheles when people are inactive and sleeping. Multiple feeding has several implications in malaria transmission. In an arthropod vector of a disease affecting man, the taking of cryptic multiple meals may be expected to increase the man- biting habit, and thereby the vectorial capacity of the population. The chances of acquiring and of transmitting the disease agent would both be increased as a consequence (Boreham & Garrett- Jones, 1973). This applies where the feeding involves a number of different hosts, human or animal. But looking at human hosts alone, the number of bites per gonotrophic cycle has the pontential to raise the transmission potential, both Ro and vectorial capacity (VC) of the mosquito population above those expected without multiple feeding (Tedrow et al., 2019). According to Keven et al., (2021), Anopheles mosquitoes that feed on two human hosts per gonotrophic cycle increase both R0 and VC by two-fold or greater (Tedrow et al., 2019). This is possible because those vectors can infect more than one human if they are sporozoite-positive, and also have more 98 than one chance of obtaining an infectious (i.e., gametocytemic) blood meal in a single gonotrophic cycle. Our results have shown that the school age group was the most frequently bitten group, and that the mosquitoes biting this group had higher rate of infection in the abdomen and the head. This entails that this group was proportionately driving higher infection into the mosquitoes since a higher proportion of mosquitoes biting this age group had higher P. falciparum positives detected in their blood meal. The higher P. falciparum positivity in the abdomen of the mosquito biting this age group may suggest this group to be responsible for driving the infection into the mosquito populations. An assessment of the rate of infection in this age group as revealed in this study and in literature shows that this group has higher Plasmodium infection rate in the population (Walldorf et al., 2015; Coalson, 2015; Gonçalves et al., 2017). The higher P. falciparum positivity in the head (sporozoite) of mosquitoes biting this age group may suggest that the mosquitoes were infectious, and they could be transmitting the infection back to the population hence maintaining the transmission cycle. This is an interesting observation because it relates the point that some groups in the population are responsible for the transmission of infection to the mosquitoes while others bear the burden on the infection. This observation agrees with other studies which showed that children below 15 years of age were more likely to infect mosquitoes than adults (Goncalves et al., 2017). Thus, our study incriminates males of the school age group (6-15 years old) as drivers of infection from humans to mosquitoes and as reservoirs of Plasmodium falciparum infection in Malawi. Males of this age category can be considered “super-spreaders”, when it comes to infecting mosquitoes. These individuals who contribute most of the blood meals are more likely to infect 99 and be infected by the mosquitoes and serve as reservoirs of the parasite to which later are spread to the community population (Burkot, 1988; Cooper et al., 2019; Smith et al., 2004). The limitation of the study was the low participation from household members in the survey, which increased the rate of non-matching of genetic profiles generated from human and mosquito blood meal. Hence, the non-matching profiles were excluded from the analysis. Also, the timing of blood sample collection was not the same as the mosquito sample collection with a lag period of about a few days in between, as such it was difficult to directly relate the infections in the humans to the mosquitos. However, this limitation was overcome by considering the infection in the blood meals rather than the humans to draw conclusions. However, the P. falciparum infection proportions in the abdomen of blood fed mosquitoes (blood meal) were not significantly different from the P. falciparum infection proportions (prevalence) in the human population. Hence, we propose further research in using mosquitoes (abdomen or blood meal) in malaria studies as a tool for sampling human population for P. falciparum infection detection (prevalence) as proposed for human and animal Virus surveillance (Yang et al., 2015). The advantage of using mosquitoes as blood sampling tool include the reduction in cost associated with current sampling methods and addressing issues to do with ethical implications of using human subjects in research. A conceptual model of the results emerges from the findings of this study and allows inferences about the relative transmission potentials among sex and age groups. All observations point to age group 6-15 as being the mostly frequently bitten (contributing most blood meals), frequently bitten by infected mosquito (mosquito head infection) and most infected (high mosquito abdomen infection and human population infection). The flow of blood meals and P. falciparum infection from these observations is proposed below (Figure 4.8). 100 Plasmodium falciparum Mosquito bites Focus for Intervention infection + + + + + + + + + + + + Mosquito population 6-15 years old + + + population + + + + < 5 and 16> years old population Blood meals Figure 4.8. Proposed model of flow of blood meals and P. falciparum infection between human and mosquito populations. Age 6-15 as reservoir and contributors of P. falciparum to mosquitoes. Age group 6-15 years (mostly males) contribute more blood meal and P. falciparum infections to the mosquitoes, they also receive mosquito bites and P. falciparum infections from mosquitoes. They are both reservoirs of infection and drivers of infection into the mosquitoes. Age group £ 5 and ³16years old contributes less blood meals and few infections to the mosquitoes, while receiving fewer bites and P. falciparum infection from mosquitoes. This situation could lead to persistent residual malaria affecting even the vulnerable populations (young children and pregnant mothers). An increase in interventions focusing and incorporating more of school age children will as a result drastically reduce transmission in the vulnerable population. 101 4.6. Conclusion Mosquito population in the study area exhibit non-random human selection where school age (6- 15 years old) children (largely males) were more frequently bitten than other population groups. The availability of multiple blood meals across ages and sex increases the transmission potential from human to mosquitoes and vice versa. Why some household receive more mosquito bites than others is an observation that needs further exploration. Biases in biting different population groups based on age and sex by mosquito species was not firmly established in the study because the outcome variable was blood meal analysis, not empirically measured biting rates. Whether biting rate equates to blood meal analysis cannot be readily confirmed; for example, one could not ethically conduct mosquito biting studies on children or malaria-infected people. The probabilities of being bitten according to age and sex was high in school age children, with high prevalence of infection. Males of this age group (5-16 years old) have been incriminated as the drivers of Plasmodium infection from humans to mosquitoes. This conclusion is crucial in malaria control and prevention that deliberately target males of this age group. The current control strategies seem to be leaving out this crucial population group. We therefore propose deliberate effort to increase bed net access and usage in this group as a starting point in reducing the human to mosquito malaria transmission. 102 APPENDICES 103 APPENDIX 4.1. OUTPUT OF ALLELIC SIZE VISUALIZATION. Figure 4.9. Example of output for visualization of allelic sizes on each loci for creating genetic profiles of each individual sample. 104 APPENDEX 4.2. EXAMPLE OF GENETIC PROFILES GENERATED FROM SAMPLES Table 4.2. Example of profiles generated from human blood spot samples. Human bloodspot profiles 105 Table 4.3. Example of profiles generated from mosquito blood meal samples. Mosquito blood meal profiles Multiple feeding Allele dropout 106 CHAPTER 5 : GENERAL CONCLUSION Chapters 2 to 4 make several conclusions which were arrived at with inferences made after detailed evaluation of the data. In this final chapter the focus is on summarizing the main conclusions to cohesively address the overarching hypothesis of this dissertation. The hypothesis was that biases in mosquito human feeding could be driving malaria infection transmission in Malawi and that certain population groups are drivers of malaria infection into the mosquito population. In Chapter 2, the results showed Anopheles species composition, distribution and abundance in the study areas and their role in malaria transmission. Five anopheles mosquito species identified were An. arabiensis, An. funestus, An. gambiae, An. parensis and An. vaneedeni but An. parensis and An. vaneedeni were least in abundance. The infection rates in An. arabiensis, An. funestus and An. gambiae showed that these three species continue to pose threat of malaria transmission as main malaria vectors. The high infection rates in head-thorax and abdomen of mosquitoes point to a potential situation of residual malaria transmission. Potential secondary vectors maybe present in the study area and needs more investigation. In chapter 3 the results showed that three malaria vector mosquito species were utilizing blood meals from both human and non-human hosts and multiple hosts utilization was detected. The majority of the blood meals were mostly from humans, resulting in a high human blood index. Both HBI and EIR were considerably high suggesting active malaria transmissions. The availability of mixed blood meals shows the adaptability of the vectors to switch hosts, obtaining a full bloodmeal and potentially circumventing malaria control interventions. Finally, Chapter 4 revealed that mosquito feeding exhibited non-random human selection for blood meal source and multiple human sources (10%) of blood meal in a single mosquito exists. There were more 107 mosquito bites in certain individuals than others with males of the school going age group (6-15 years old) being the most frequently bitten (av. 47%) and had highest malaria infection. The results suggest that males of 6-15 years old are the main drivers of malaria infection from human to mosquitoes. In summary, of the five anopheles species identified in the study, An. arabiensis, An. funestus and An. gambiae continues to be dominant species posing threat of malaria transmission in Malawi. Presence of other Anopheles species in indoor collections points to potential existence of secondary malaria vectors which needs further investigation. In the human population, 6-15-years old are the most malaria infected group with males showing highest infection rates. This conclusion was confirmed by the blood meal and genotyping analysis approaches which found that mosquitoes utilize blood meals from both human and non-human hosts. Of the human population, age group 6-15 years old was the most frequently bitten category providing mosquito blood meal. Since the same age group was found to be having higher malaria infection rates, it stands to reason that this particular age group could be potential main drivers of malaria infection from human to mosquitoes. This study dissertation, therefore, incriminates males of 6-15-year-old population group as the main drivers of Plasmodium infection from humans to mosquitoes. These conclusions have several implications on malaria transmission in Malawi. One, for success to be realized in malaria control and prevention it is critical to put in place deliberate efforts targeting males of this particular age group (6-15 years old). Second, the availability of mixed blood meal shows the adaptability of the vectors to switch hosts for obtaining bloodmeal and therefore circumvent malaria control interventions. Multiple feeding in human populations has the potential of increasing malaria transmission and reducing the effectiveness of on doing 108 interventions. As way forward we propose a study intervention that targets 5-16-year-olds by giving them prophylactic drugs to reduce Plasmodium prevalence and providing more LLINs coverage to reduce mosquito-human contact. The outcome of the intervention would be measured by the reduction in mosquito blood meal and infection prevalence in this group after six months to a year. 109 APPENDIX 110 RECORD OF DEPOSITION OF VOUCHER SPECIMENS The specimens listed below have been deposited in the named museum as samples of those species or other taxa, which were used in this research. Voucher recognition labels bearing the voucher number have been attached or included in fluid preserved specimens. Voucher Number: 2021-04 Author and Title of thesis: Rex Barnett Marregah Mbewe Blood-meal host selection, malaria infection, and genotyping to delineate human to mosquito plasmodium transmission: Implication for malaria parasite infections in Malawi Museum(s) where deposited: Albert J. Cook Arthropod Research Collection, Michigan State University (MSU) Specimens: Specimens: Family Genus-Species Life Stage Quantity Preservation Culicidae Anopheles coustani adult 10 pinned Culicidae Anopheles funestus adult 10 pinned Culicidae Anopheles gambiae adult 10 pinned Culicidae Anopheles maculipulpis adult 10 pinned Culicidae Anopheles pretoriensis adult 10 pinned 111 REFERENCES 112 REFERENCES Adhikari, B., Phommasone, K., Pongvongsa, T., Soundala, X., Koummarasy, P., Henriques, G., Peto, T. J., Seidlein, L. von, White, N. J., Day, N. P. J., Dondorp, A. M., Newton, P. N., Cheah, P. Y., Mayxay, M., & Pell, C. (2018). Perceptions of asymptomatic malaria infection and their implications for malaria control and elimination in Laos. PLOS ONE, 13(12), e0208912. https://doi.org/10.1371/journal.pone.0208912 Adugna, T., Yewhelew, D., & Getu, E. (2021). Bloodmeal sources and feeding behavior of anopheline mosquitoes in Bure district, northwestern Ethiopia. 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