Interactive SARS-CoV-2 dashboard for real-time geospatial visualisation of sewage and clinical surveillance data from Dhaka, Bangladesh: a tool for public health situational awareness

Throughout the COVID-19 pandemic, many dashboards were created to visualise clinical case incidence. Other dashboards have displayed SARS-CoV-2 sewage data, largely from countries with formal sewage networks. However, very few dashboards from low-income and lower-middle-income countries integrated both clinical and sewage data sets. We created a dashboard to track in real-time both COVID-19 clinical cases and the level of SARS-CoV-2 virus in sewage in Dhaka, Bangladesh. The development of this dashboard was a collaborative iterative process with Bangladesh public health stakeholders to include specific features to address their needs. The final dashboard product provides spatiotemporal visualisations of COVID-19 cases and SARS-CoV-2 viral load at 51 sewage collection sites in 21 wards in Dhaka since 24 March 2020. Our dashboard was updated weekly for the Bangladesh COVID-19 national task force to provide supplemental data for public health stakeholders making public policy decisions on mitigation efforts. Here, we highlight the importance of working closely with public health stakeholders to create a COVID-19 dashboard for public health impact. In the future, the dashboard can be expanded to track trends of other infectious diseases as sewage surveillance is increased for other pathogens

Real-time sewage surveillance for SARS-CoV-2 in Dhaka, Bangladesh versus clinical COVID-19 surveillance: a longitudinal environmental surveillance study (Dec 2019 – Dec 2021)

Background: Clinical surveillance for COVID-19 has typically been challenging in low-middle income settings. From December 2019 to December 2021, we implemented environmental surveillance (ES) in a converging informal sewage network in Dhaka, Bangladesh, to investigate SARS-CoV-2 transmission across different income levels of the city compared to clinical surveillance. Methods: All sewage lines were mapped, and sites were selected with estimated catchment population of >1,000 individuals. We analysed 2,073 sewage samples, collected weekly from 37 sites and 648 days of case data from 8 wards with varying socio-economic statuses. We assessed the correlations between the viral load in sewage samples and clinical cases. Findings: SARS-CoV-2 was consistently detected across all wards (low to high income) despite large differences in reported clinical cases and periods of no cases. Most COVID-19 cases (60.3%, n=28,766/47,683) were reported from high-income areas with high levels of clinical testing (261-1603 monthly tests per 100,000 vs. 0-189 in lower-income areas), despite containing 25% (184,117/734,755) of the study population. Conversely, a similar quantity of SARS-CoV-2 was detected in sewage across different income levels (mean difference in high vs. low-income areas: 0.35 log10 viral copies + 1). The correlation between the mean sewage viral load (log10 viral copies + 1) and the log10 clinical cases increased with time (R=0.90 July 2021-December 2021 and R=0.59 July 2020-December 2020). Before major waves of infection, viral load quantity in sewage samples increased one to two weeks before the clinical cases. Interpretation: This study demonstrates the utility and importance of environmental surveillance for SARS-CoV-2 in a low-middle income country. We show ES provides an early warning of increases in transmission and shows evidence of persistent circulation in poorer areas where access to clinical testing is limited. Funding: Bill and Melinda Gates Foundation (INV-022699 and OPP1193124 to M Taniuchi). IM Blake acknowledges funding from the MRC Centre for Global Infectious Disease Analysis (reference MR/R015600/1), jointly funded by the UK Medical Research Council (MRC) and the UK Foreign, Commonwealth & Development Office (FCDO), under the MRC/FCDO Concordat agreement and is also part of the EDCTP2 programme supported by the European Union