The Implementation and Utilization of Wastewater-Based Epidemiology: Experiences From a Local Health Department.

Wastewater-based epidemiology has increasingly demonstrated its importance in addressing public health threats. The COVID-19 pandemic brought forth funding for public health agencies to conduct wastewater-based epidemiology. Using a team with diverse skills, a local health department utilized this funding to regularly monitor SARS-CoV-2 in wastewater on university campuses, a K-12 campus, an inpatient psychiatric facility, and a long-term care facility. Between September 2021 and May 2022, more than 760 wastewater samples were collected of which 102 (13.4%) were above a predetermined threshold. When sites exceeded that threshold, local health department staff provided testing resources. Wastewater-based epidemiology is a useful surveillance program that can be effectively conducted by local health departments when provided with funding and a skilled workforce.

Simple methods for early warnings of COVID-19 surges: Lessons learned from 21 months of wastewater and clinical data collection in Detroit, Michigan, United States.

Wastewater-based epidemiology (WBE) has drawn great attention since the Coronavirus disease 2019 (COVID-19) pandemic, not only due to its capability to circumvent the limitations of traditional clinical surveillance, but also due to its potential to forewarn fluctuations of disease incidences in communities. One critical application of WBE is to provide "early warnings" for upcoming fluctuations of disease incidences in communities which traditional clinical testing is incapable to achieve. While intricate models have been developed to determine early warnings based on wastewater surveillance data, there is an exigent need for straightforward, rapid, broadly applicable methods for health departments and partner agencies to implement. Our purpose in this study is to develop and evaluate such early-warning methods and clinical-case peak-detection methods based on WBE data to mount an informed public health response. Throughout an extended wastewater surveillance period across Detroit, MI metropolitan area (the entire study period is from September 2020 to May 2022) we designed eight early-warning methods (three real-time and five post-factum). Additionally, we designed three peak-detection methods based on clinical epidemiological data. We demonstrated the utility of these methods for providing early warnings for COVID-19 incidences, with their counterpart accuracies evaluated by hit rates. "Hit rates" were defined as the number of early warning dates (using wastewater surveillance data) that captured defined peaks (using clinical epidemiological data) divided by the total number of early warning dates. Hit rates demonstrated that the accuracy of both real-time and post-factum methods could reach 100 %. Furthermore, the results indicate that the accuracy was influenced by approaches to defining peaks of disease incidence. The proposed methods herein can assist health departments capitalizing on WBE data to assess trends and implement quick public health responses to future epidemics. Besides, this study elucidated critical factors affecting early warnings based on WBE amid the COVID-19 pandemic.