Abstract
SummaryBackgroundThe World Health Organisation recommends wastewater based epidemiology (WBE) for SARS-CoV-2 as a complementary tool for monitoring population-level epidemiological features of the COVID-19 pandemic. Yet, uptake of WBE in low-to-middle income countries (LMIC) is low. We report on findings from SARS-CoV-2 WBE surveillance network in South Africa, and make recommendations regarding implementation of WBE in LMICsMethodsSeven laboratories using different test methodology, quantified influent wastewater collected from 87 wastewater treatment plants (WWTPs) located in all nine South African provinces for SARS-CoV-2 from 01 June 2021 – 31 May 2022 inclusive, during the 3rd and 4th waves of COVID-19. Regression analysis with district laboratory-confirmed SARS-CoV-2 case loads, controlling for district, size of plant and testing frequency was determined. The sensitivity and specificity of ‘rules’ based on WBE data to predict an epidemic wave based on SARS-CoV-2 wastewater levels were determined.FindingsAmong 2158 wastewater samples, 543/648 (85%) samples taken during a wave tested positive for SARS-CoV-2 compared with 842 positive tests from 1512 (55%) samples taken during the interwave period. Overall, the regression-co-efficient was 0,66 (95% confidence interval=0,6-0,72, R2=0.59), but ranged from 0.14-0.87 by testing laboratory. Early warning of the 4thwave of SARS-CoV-2 in Gauteng Province in November-December 2021 was demonstrated. A 50% increase in log-copies SARS-CoV-2 compared with a rolling mean over the previous 5 weeks was the most sensitive predictive rule (58%) to predict a new wave.InterpretationVariation in the strength of correlation across testing laboratories, and redundancy of findings across co-located testing plants, suggests that test methodology should be standardised and that surveillance networks may utilise a sentinel site model without compromising the value of WBE findings for public health decision-making. Further research is needed to identify optimal test frequency and the need for normalisation to population size, so as to identify predictive and interpretive rules to support early warning and public health action. Our findings support investment in WBE for SARS-CoV-2 surveillance in low and middle-income countries.Research in ContextEvidence before this studyWastewater-based epidemiology (WBE) has long been used to track community disease burden within communities. This approach has become increasingly popular for monitoring the SARS-CoV-2 virus since the beginning of the COVID-19 pandemic. We searched PubMed up until May 2022 using these keywords “SARS-CoV-2”, “COVID”, “wastewater-based epidemiology”, “WBE”, combining them with relevant Boolean operators. We found that majority studies were mostly conducted in high income settings. Huge gap exists for such studies in low and middle income countries, particularly, sub-Saharan Africa. Furthermore, given that WBE of COVID-19 is still in its early stages, more studies are required not only quantify SARS-CoV-2 RNA in wastewater but to also assess the relationship between SARS-CoV-2 in wastewater and clinical case load. Such studies are required to showcase the usefulness of WBE, strengthen the surveillance of COVID-19 and also to improve uptake of these findings by public health officials for decision making.Added value of this studyThis is the first study to test a large number of (87) wastewater treatment plants across major cities on a national scale in an African country. Our study not only demonstrates the added value of wastewater-based epidemiology as a great surveillance tool to aid disease control in our setting and similar settings, but it also demonstrates the feasibility of this type of testing. Our research findings are critical for policymakers in South Africa and other low and middle-income countries.Implications of all the available evidenceThis study shows that indeed wastewater surveillance can be used to assess the level of disease burden within populations in developing country, especially where there are little or no clinical testing which in turn can inform prompt public health decision. This finding also implies that other infectious diseases which disproportionately affect many low and middle income countries can be monitored using the same approach.
Publisher
Cold Spring Harbor Laboratory