In the absence of pipe-borne water, many people in Africa, especially in rural communities, depend on alternative water sources such as wells, boreholes and rivers for household and personal hygiene. Poor maintenance and nearby pit latrines, however, lead to microbial pollution of these sources. We evaluated the abundance of Escherichia coli and the prevalence of pathogenic E. coli virulence genes in water from wells, boreholes and a river in a South African peri-urban community. Monthly samples were collected between August 2015 and November 2016. In all, 144 water samples were analysed for E. coli using the Colilert 18 system. Virulence genes (eagg, eaeA, stx1, stx2, flichH7, ST, ipaH, ibeA) were investigated using real-time polymerase chain reaction. Mean E. coli counts ranged between 0 and 443.1 Most Probable Number (MPN)/100 mL of water sample. Overall, 99.3% of samples were positive for at least one virulence gene studied, with flicH7 being the most detected gene (81/140; 57.6%) and the stx2 gene the least detected gene (8/140; 5.7%). Both intestinal and extraintestinal pathogenic E. coli genes were detected. The detection of virulence genes in these water sources suggests the presence of potentially pathogenic E. coli strains and is a public health concern.

This study determined whether the estuarine and freshwater environment in Beira, Mozambique, serves as a reservoir of Vibrio cholerae O1 and O139. Ninety-nine estuarine water samples were collected at 6 sites in Beira. An additional 54 samples were collected from rural areas around Beira which included 3 freshwater lake samples, 15 river, 5 pond, and 4 estuarine water samples, and an equivalent number of sediment samples, collected from the same sites as the water samples. In addition, fish scales from 5 ocean fish and 1 deep sea water sample were also collected. The samples were analysed for the presence of V. cholerae O1 and O139 using culture methods, the direct fluorescent antibody (DFA) method and polymerase chain reaction (PCR) using a single-primer pair for the ompW gene and a semi-nested PCR selecting for the ctxA gene, encoding subunit A of cholera toxin. DFA results showed 37 V. cholerae O1-and 6 O139-positive samples. Vibrio cholerae O1 and O139 were observed on the scales of 4 of the 5 fish. The findings of the study provided in situ evidence for V. cholerae O1 and O139, predominantly as viable but non-culturable cells in the aquatic environment of Beira. This is the first record of the presence of V. cholerae O139 in the estuarine environment on the coast of Africa.

Rivers support substantial populations and provide important ecosystem services. Despite the application of fecal coliform tests and other markers, we lack rapid and reproducible approaches for determining fecal contamination in rivers.

Potential exposure to water and air pollution and associated health impacts of three low-income communities in the Upper Olifants River Catchment, South Africa, was investigated through a cross-sectional epidemiological study comprising a household survey. Water samples were collected and analysed for microbial indicators and pathogens. Ambient air-monitoring included some of the criteria pollutants, as well as mercury and manganese. Associations between environmental exposure and health outcomes were analysed by means of logistic regression. Despite poor water and air quality episodes, the communities' self-perceived health was good with relatively low prevalence of reported health outcomes. Hygiene practices with respect to water collection and storage were often poor, and most likely contributed to the regularly contaminated water storage containers. Community proximity to the polluted stream was associated with increased prevalence in adverse health outcomes. This paper reports on preliminary results and additional multivariate analyses are necessary to further understand study results.

Background: The 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 LMICs Methods: Seven 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 to 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. Results: Among 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, R squared=0.59), but ranged from 0.14 to 0.87 by testing laboratory. Early warning of the 4th wave 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. Conclusion: Variation 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.