Localized wastewater surveillance showed correlation but no early warning during Bengaluru’s Omicron wave

Wastewater surveillance is an effective tool for monitoring the spread of infectious diseases such as COVID-19. In August 2021, a citywide surveillance effort was initiated in Bengaluru to analyze viral loads from 28 sewage treatment plants (STPs). The study found a strong correlation between aggregated viral loads and citywide COVID-19 case counts. However, the lack of localized clinical data limited the ability to assess infection trends at the STP level. In this follow-up study, we incorporate granular clinical data from 198 administrative units in the city. We find similar trends between viral loads at individual STPs and the cases in their catchment areas. A typical confidence interval for the Pearson correlation between clinical cases and wastewater viral loads at an STP is approximately 0.56–1.00, based on the median bounds across the STPs; at the city-level it is 0.67–1.00. However, our analysis shows no reliable indication of a lead or early warning—the viral loads and reported cases rise simultaneously. It is important to note that our study is limited to the first Omicron wave of the pandemic. To quantify lead time, we used correlation and change-point analysis. These results underscore the potential of localized wastewater surveillance for real-time monitoring but highlight its limitation in early outbreak detection.Author summary: We aimed to assess the effectiveness of wastewater surveillance in detecting COVID-19 trends at localized scales within Bengaluru during the first Omicron wave. To enable this localized study, we undertook two key tasks: first, we mapped the catchment areas supplying wastewater to the sewage treatment plants (STPs), and second, we incorporated clinical data from 198 administrative units, for the time period when SARS-CoV-2 viral loads were monitored. This mapping of catchment areas and integration of granular clinical data was not done in previous studies. We find that viral loads closely mirrored infection trends at a localized level; however, they did not provide an advance indication of cases, as they rose concurrently with reported infections.