Integrating Wastewater-Based Epidemiology (WBE) With Predictive Analytics For Tracking Non-Communicable Diseases (Ncds) In Urban Populations

Abstract

Convergence of Wastewater-Based Epidemiology (WBE) and predictive analytics, opens up to new approaches to public health surveillance. WBE has been practiced throughout history as a tool to trace infectious diseases and monitor the community's health via biomarkers identified in the wastewater. The potential in future research regarding WBE escalates exponentially considering the COVID-19 pandemic has come to show what a low-cost, non-invasive tool gives real-time information about disease dynamics at the level of the community. In this parallel, it will be huge data analytics as predictive analytics, applied to track health trends along with resource allotment with a public health intervention. Such an integrated framework will emerge if these methodologies are integrated together; it could be used for NCD surveillance, which is yet one of the major challenges in global health. The integrated approach could find a biomarker for NCDs, monitor lifestyle factors, and predict prevalence to allow timely interventions. Data standardization, privacy concerns, and methodological differences create challenges toward its equitable and effective implementation. In this regard, this review would discuss how the synergy of WBE with predictive analytics can support applications in monitoring NCD, highlight the application fields, and focus on operational and ethical issues regarding this integration. Public health systems can, therefore, improve disease surveillance and public health outcomes by leveraging the strengths of both disciplines to better address urban health disparities.