Abstract: Wastewater-based epidemiology has traditionally focused on sampling at treatment plants, assuming this provides a representative sample of all individuals within the sewershed. This approach has several limitations in outbreak detectability and prevention of disease transmission into targeted high-risk population areas. This dissertation presents methods for spatio-temporal dashboards to detect outbreaks amid declining clinical testing. It also explores environmental, demographic and methodological factors affecting biomarker concentrations in wastewater, which is key to disease trend estimation. The final chapter introduces a mechanistic model assessing viral decay, dilution and shedding rates. These findings support future disease prediction models and optimize sub-sewershed sampling for early hotspot detection.