Wastewater-based monitoring for SARS-CoV-2 at individual building-level could be an efficient, passive means of early detection of new cases in congregate living settings, but this approach has not been validated. Preliminary samples were collected from a hospital and a local municipal wastewater treatment plant. Molecular diagnostic methods were compared side-by-side to assess feasibility, performance and sensitivity. Refined sample collection and processing protocols were then used to monitor two occupied dormitory complexes (n = 105 and 66) over eight weeks. Wastewater results were validated using known case counts from external clinical testing of building occupants. Results confirm that ultracentrifugation from a 24 hour composite collection had a sensitivity of 96.2% and a specificity of 100%. However, the method could not distinguish new infectious cases from persistent convalescent shedding of SARS-CoV-2 RNA. If the detection of convalescent shedding is considered a false positive, then the sensitivity is 100% and specificity drops to 45%. It was determined that the proposed approach constitutes a highly sensitive wastewater surveillance method for detecting SARS-CoV-2, but it could not distinguish new infectious cases from persistent convalescent shedding. Future work must focus on approaches to distinguish new infections from convalescent shedding to fully realize the potential of building wastewater as a surveillance tool for congregate living. Importance Some of the most severe outbreaks of COVID-19 have taken place in places where persons live together, such as a nursing homes. Wastewater testing from individual buildings could be used for frequent pooled surveillance of virus from all occupants, including those who are contagious with or without symptoms. This work provides a sensitive practical method for detecting infected individuals, as validated in two building complexes housing occupants who underwent frequent clinical testing performed by external entities. Although this sensitive method could be deployed now for pooled surveillance as an early warning system to limit outbreaks, the study shows that the approach will require further refinement to differentiate between contagious newly infected individuals from persons who have persistent viral fragments shedding in their stool outside the contagious period.

Wastewater-based monitoring for SARS-CoV-2 holds promise as tool to inform public health-decision making. Testing at individual building-level could be an efficient, passive means of preventing early detection of new cases in congregate living settings, but this approach has not been validated. Sample collection protocols were developed and refined during preliminary sampling from a hospital and a local municipal wastewater treatment plant. Molecular diagnostic methods were compared side-by-side to assess feasibility, performance and sensitivity. Optimized sample collection and processing protocols were then used to monitor two occupied dormitory complexes (n=105 and 66) over eight weeks. Wastewater results were validated using known case counts from external clinical testing of building occupants. Results confirm that ultracentrifugation from a 24 hour composite collection had a sensitivity of 95% and a specificity of 100%. However, if the detection of convalescent shedding is considered a false positive then the sensitivity would be 95.2% but the specificity would drop to 52%. We determined a highly sensitive method for detecting SARS-CoV-2 shedding in building wastewater however our methods could not distinguish new infectious cases from persistent convalescent shedding of SARS-CoV-2 RNA. Future work must focus on methods to distinguish new infections from convalescent shedding to widely deploy this promising wastewater surveillance tool.

The possibility of reoccurring waves of the novel coronavirus that triggered the 2020 pandemic makes it critical to identify underlying policy-relevant factors that could be leveraged to decrease future COVID-19 death rates. We examined variation in a number of underlying, policyrelevant, country-level factors and COVID-19 death rates across countries. We found three such factors that significantly impact the survival probability of patients infected with COVID-19. In order of impact, these are universal TB (BCG) vaccination, air pollution deaths and a healthrelated expenditure. We quantify each probability change by age and sex. To deal with small sample size and high correlations, we use an information-theoretic inferential method that also allows us to introduce priors constructed from independent SARS data.