Wastewater-based epidemiology of SARS-CoV-2 and Campylobacter: detection optimization and understanding of in-sewer decay

Wastewater-based epidemiology (WBE) is a promising approach to estimating population-wide disease prevalence by detecting various disease-related biomarkers in wastewater. Different from the untimely disease surveillance based on clinical reports, WBE surveillance detects early outbreaks of pathogens. It thus provides an early warning before pathogens are identified by healthcare systems. However, a series of uncertainties such as pathogen shedding, in-sewer transportation, and analytical methods for biomarker concentration in wastewater could induce large variances to the WEB back-estimation of disease prevalence. These knowledge gaps need to be addressed to improve the accuracy of disease surveillance using the WBE approach. This PhD thesis studied two important human pathogens, one virus (severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) and one bacterium (Campylobacter spp.). Coronavirus disease (COVID-19) caused by SARS-CoV-2 has become a public health emergency of international concern. Another human pathogen, Campylobacter spp., which is one of the leading bacterial pathogens responsible for the annual loss of 33 million lives has also caused great public concern worldwide. Molecular detection methods including qPCR, RT-qPCR, and DNA sequencing have been demonstrated as reliable detection tools for the identification of these pathogens. However, the molecular analytical methods of these two selected pathogens in wastewater samples still need to be optimized for better performance