In the recent decades we have witnessed numerous outbreaks worldwide, resulting in millions of infections and deaths. Examples include the 1918 H1N1 virus, the 1968 H3N2 virus, the 2003 SARS coronavirus, the 2012 MERS-CoV, and the 2019 SARS-CoV-2. Factors including rapid population growth, escalating climate change crisis, recurring natural disasters, booming immigration and globalization, and concomitant sanitation and wastewater management challenges are anticipated to exacerbate the frequencies of disease outbreaks in the years to come. The traditional disease detection system primarily relies on the diagnostic analysis of specimens collected from infected individuals in clinical settings. This approach has significant limitations in predicting and providing early warnings for impending disease outbreaks. Infected individuals are often tested only after the development of symptoms, and health authorities are usually notified following the inception of a disease surge. Consequently, health authorities respond reactively instead of taking proactive measures during a pandemic. Additionally, clinical data collected by traditional disease surveillance systems often fail to accurately reflect actual infections in communities when asymptomatic infections are dominating, clinical testing is incapable to capture comprehensive infections, limitations in testing supplies and accessibility, and patients’ testing behaviors. Environmental surveillance, especially wastewater surveillance or wastewater-based epidemiology, allows analyses of environmental community composite samples. Municipal wastewater samples are composite biological samples of an entire community that represent a snapshot of the disease burden of the population covered by the corresponding sewer-shed. Collecting and analyzing untreated wastewater samples from centralized wastewater treatment plants and neighborhood manholes for specific viral and bacterial targets at a regular cadence can reveal the trends of pathogen concentrations in wastewater. These trends represent the viral and bacterial loads shed by infected individuals, whether they are symptomatic or asymptomatic. Based on measured wastewater concentrations of disease pathogens and other available datasets such as clinical and demographic datasets, researchers can establish models to predict disease incidences before clinical reporting and develop tools to provide early warnings of upcoming surges of diseases. This crucial information can help public health officials in making informed decisions regarding the implementation of preparedness measures and the allocation of resources. The primary objective of this dissertation is to develop comprehensive laboratorial, technological, and translational methodologies for forecasting viral and bacterial outbreaks through wastewater-based epidemiology.
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