Determining the Impact of Socioeconomic Conditions on Sars-Cov-2 Burden of Disease in the Gauteng Province, South Africa Using Wastewater-Based Epidemiology

Abstract

Background & aims: Wastewater-based epidemiology emerged as a complementary tool to monitor trends in disease during the SARS-CoV-2 pandemic. Studies (including ours) demonstrated a correlation between wastewater levels and laboratory-confirmed SARS-CoV-2 cases. However, the degree to which socioeconomic factors affect this relationship is unknown. We aimed to describe and quantify the relationship between laboratory-confirmed SARS-CoV-2 cases, SARS-CoV-2 viral load in wastewater, and quality of life in two cities in Gauteng Province from 1 March-31 December 2021.  

Methods & results:  With permission and ethical approval, we obtained official geolocated, anonymised laboratory-confirmed line lists of SARS-CoV-2 cases and SARS-CoV-2 viral load from wastewater for Gauteng from the National Institute for Communicable Diseases. From the Gauteng City-Region Observatory, we obtained results of the Quality of Life Survey (2020/2021), a large household-based survey of adults representative across Gauteng. Using spatial data and wastewater reticulation networks from the cities of Tshwane and Ekurhuleni, we defined population demographics, quality of life, and laboratory-confirmed cases for persons resident in catchments of two wastewater treatment plants (Daspoort and Olifantsfontein). We calculated and compared demographics, quality of life, cumulative incidence rates, and Spearman’s correlations between cities and catchments for the period 1 March-31 December 2021.  

Of the approximate 2.9 million and 4 million people in Tshwane and Ekurhuleni respectively, 245,935 and 940,762 people lived in the Daspoort and Olifantsfontein wastewater catchments. The number (and cumulative incidence) of laboratory-confirmed SARS-CoV-2 cases was 49,489 (13,367.6/100,000) and 29,412 (3,126.4/100,000) in Tshwane and Ekurhuleni. On average, quality of life was higher in the Tshwane catchment compared to the Ekurhuleni catchment (64 vs 57). There were high correlations between laboratory-confirmed cases and wastewater levels in Tshwane (correlation coefficient (r)=0.8, p-value<0.001) and Ekurhuleni (r=0.7, p-value=0.002). Restricting analyses to data from wastewater catchments, the correlation was slightly lower in both Tshwane (r=0.6, p-value<0.001) and Ekurhuleni (r=0.6, p-value=0.014).

Implications: Higher quality of life and better access to testing in Tshwane may have contributed to a stronger correlation between laboratory-confirmed cases and wastewater levels compared with Ekurhuleni. Findings indicate that wastewater surveillance may be useful to support clinical surveillance, particularly in more vulnerable communities.

Note: This conference abstract was presented at the 9th International Conference on Infectious Disease Dynamics organized by the journal Epidemics. This abstract has not been screened by SSRN for potential for public harm and should not be used to inform any clinical decision making. No competing interests or funding statements have been declared.