Fiona Els

Inferring epidemic trajectories of viral infections from wastewater data can be a useful addition to clinical-based surveillance, as it provides low cost, population-level data that includes both symptomatic and asymptomatic individuals who contribute to the sewer system. However, methods for analyzing wastewater data have been primarily applied to high-resource settings. It remains an open question to what extent epidemic dynamics can also be estimated from wastewater data in low-resource settings, where measurements are less frequent and the underlying catchment population is not clearly characterized. We used SARS-CoV-2 wastewater data from the Gauteng Province in South Africa (June 2021 to March 2022). We used the R packages EpiSewer and EpiNow2 to estimate the effective reproduction number (Rt) from wastewater data and geographically matched clinical surveillance data, respectively. The comparison between wastewater and clinical Rt showed that the observed trends are not perfectly aligned. Despite these differences, wastewater and clinical Rt estimates identified similar transmission patterns, which were similar to the trend seen directly from the recorded data. Maximum wastewater Rt of 1.38 (95% CI: 1.17–1.44) was observed in early November 2021, whilst clinical Rt was 1.18 (90% CI: 0.85–1.27) in June 2021. The change in Rt aligned with an increase or decrease in recorded cases. Our findings demonstrate that, even with limited data, estimating epidemic trajectories is feasible, providing valuable insights for informing public health recommendations. However, whenever possible, we recommend using wastewater surveillance as a complementary tool for clinical surveillance.

Measles outbreaks have surged globally in recent years, but current surveillance systems have limited capacity to monitor measles virus (MeV) transmission and evolution at population scale. Although MeV can be detected in wastewater, the public health potential of wastewater genomic surveillance for MeV remains largely unexplored. Here, we deploy sensitive, low-cost MeV wastewater genomic surveillance combining virus concentration, whole-genome amplicon sequencing, and bioinformatic analysis alongside routine clinical genomic surveillance during the 2024-25 outbreak in South Africa. Integrated phylogenetic analyses of wastewater and clinical MeV genomes revealed previously undetected interprovincial spread and transmission links not captured by standard N450 sequencing. Our findings demonstrate that wastewater-integrated whole-genome surveillance expands the coverage and resolution of routine MeV monitoring and provides a scalable tool to advance measles control and elimination efforts.

Wastewater and environmental surveillance has been promoted as a communicable disease surveillance tool because it overcomes inherent biases in laboratory-based communicable disease surveillance. Yet, little empirical evidence exists to support this notion, and it remains largely an intuitive, though highly plausible hypothesis. Our interdisciplinary study uses WES data to show evidence for underreporting of SARS-CoV-2 in the context of measurable and statistically significant associations between economic conditions and SARS-CoV-2 incidence and testing rates. We obtained geolocated, anonymised, laboratory-confirmed SARS-CoV-2 cases, wastewater SARS-CoV-2 viral load data and socio-demographic data for Gauteng Province, South Africa. We spatially located all data to create a single dataset for sewershed catchments served by two large wastewater treatment plants. We conducted epidemiological, persons infected and principal component analysis to explore the relationships between variables. Overall, we demonstrate the co-contributory influences of socio-economic indicators on access to SARS-CoV-2 testing and cumulative incidence, thus reflecting that apparent incidence rates mirror access to testing and socioeconomic considerations rather than true disease epidemiology. These analyses demonstrate how WES provides valuable information to contextualise and interpret laboratory-based epidemiological data. Whilst it is useful to have these associations established for SARS-CoV-2, the implications beyond SARS-CoV-2 are legion for two reasons, namely that biases inherent in clinical surveillance are broadly applicable across pathogens and all pathogens infecting humans will find their way into wastewater albeit in varying quantities. WES should be implemented to strengthen surveillance systems, especially where economic inequalities limit interpretability of conventional surveillance data.

Background: Adherence to COVID-19 prevention and control measures is related to people’s knowledge, attitudes and practices. Setting: In Thabo Mofutsanyana District, the proportion of reported community COVID-19-related deaths was higher than in-facility reported deaths. Aim: To assess knowledge, attitudes and practices of the community towards COVID-19. Methods: A survey was conducted among consenting adults from 28 February 2022 to 4 March 2022. An interviewer-administered questionnaire was used for data collection. Descriptive statistics was used to describe the responses and logistic regression used to assess factors associated with poor knowledge towards COVID-19. Results: A total of 551 participants’ data were analysed, most of whom were < 40 years (63%) and female (68%). Despite 43.4% having education levels below high school, 89% knew that anyone could contract COVID-19, mainly through television and/or radio (74%) and social media (53%). The majority practiced mask-wearing (84%) and social distancing (80%), while 65% indicated they will use home remedies if there was severe COVID-19 infection. Older age group (OR = 2.40; 95% CI 1.17-4.89; p = 0.015), higher education level (OR = 0.59; 95% CI 0.39–0.87; p = 0.009) and higher monthly income were each associated with poor knowledge towards COVID-19 but the significance did not remain in multivariate model. Conclusion: Participants had good knowledge of COVID-19; however, a high proportion supported the use of home remedies in severe COVID-19 infections. This underscores the need to enhance the health-seeking behaviour of communities through health education and community engagement, using television and/or radio and social media. Contribution: Study findings are useful to inform preparedness and response strategies in communities.

Wastewater surveillance is useful for monitoring the prevalence of hepatitis A virus (HAV). We developed and optimized HAV detection and quantification methods for wastewater samples, and applied them to samples collected through a national wastewater surveillance program. Previously identified 5’-untranslated region-targeting primers and probes were used to develop the assay. Serial dilutions of HAV-positive clinical samples were used to validate and determine limits of quantification (LOQ). Retrospective testing of weekly wastewater samples collected through the SARS-CoV-2 wastewater surveillance program at 26 sites in Gauteng (August 2021 to March 2024) were undertaken using ultrafiltration-based concentration, and nucleic acids were extracted using the KingFisher Flex purification system with a wastewater isolation kit. A digital PCR assay was used for HAV detection and quantification (as genome copies/μL). Clinical data from the Surveillance Database Warehouse of the National Health Laboratory Service were compared with wastewater data, epidemiological week-wise and district-wise, to determine correlations between the datasets. Based on the validation results, one partition on the digital PCR (dPCR) platform was equivalent to an LOQ of 0.4 genome copies/μL. In total, 2013 wastewater samples were tested, of which 349 were positive for HAV (17.3%), wherein the majority (304, 87.1%) had the lowest HAV concentration (2.0-2.7 gc/μL, 1-5 partitions), followed by 20 samples (5.7%) with concentrations of 2.8-3.0 gc/μL (6-10 partitions). HAV was detected in 17.1% (241/1170) of the Gauteng samples, and a 26.1% correlation between anti-HAV IgM in clinical samples and HAV in wastewater samples was detected. We successfully developed and optimized a dPCR method to detect and quantify HAV in wastewater samples, and determined its LOQ. Further analysis is required to compare the wastewater data with clinical surveillance data to facilitate appropriate interpretation of the results.

Wastewater and environmental surveillance has been promoted as a communicable disease surveillance tool because it overcomes inherent biases in laboratory-based communicable disease surveillance. Yet, little empirical evidence exists to support this notion, and it remains largely an intuitive, though highly plausible hypothesis. Our interdisciplinary uses WES data to show evidence for underreporting of SARS-CoV-2 in the context of measurable and statistically significant associations between economic conditions and SARS-CoV-2 incidence and testing rates. We obtained geolocated, anonymised, laboratory-confirmed SARS-CoV-2 cases, wastewater SARS-CoV-2 viral load data and socio-demographic data for Gauteng Province, South Africa. We spatially located all data to create a single dataset for sewershed catchments served by two large wastewater treatment plants. We conducted epidemiological, persons infected and principal component analysis to explore the relationships between variables. Overall, we demonstrate the co-contributory influences of socio-economic indicators on access to SARS-CoV-2 testing and cumulative incidence, thus reflecting that apparent incidence rates mirror access to testing and socioeconomic considerations rather than true disease epidemiology. These analyses demonstrate how WES provides valuable information to contextualise and interpret laboratory-based epidemiological data. Whilst it is useful to have these associations established for SARS-CoV-2, the implications beyond SARS-CoV-2 are legion for two reasons, namely that biases inherent in clinical surveillance are broadly applicable across pathogens and all pathogens infecting humans will find their way into wastewater albeit in varying quantities. WES should be implemented to strengthen surveillance systems, especially where economic inequalities limit interpretability of conventional surveillance data.

Background Sensitive clinical surveillance and high vaccination coverage are required to meet the WHO 2030 measles elimination target. Whilst wastewater and environmental surveillance (WES) has proven usefulness in polio surveillance, it has not been applied to measles control. We describe the development of digital RT-PCR (RT-dPCR) for detection and quantification of measles virus (MeV) in wastewater, and application to retained concentrated samples obtained from 28 national sentinel SARS-CoV-2 wastewater surveillance sites and 19 localised collection points in a single province before, during and after a measles outbreak of over 2,000 laboratory-confirmed cases. Methods We validated a RT-dPCR assay incorporating WHO-recommended primers for detection and differentiation of wild-type and vaccine genotypes. We applied this to retained wastewater samples concentrated by ultrafiltration and stored at −20°C. We compared wastewater findings by district and epidemiological weeks with laboratory-confirmed measles case data obtained from national fever-rash surveillance for districts with adequate surveillance indicators (>2/100,000 non-measles cases) Findings Amongst 2,149 wastewater concentrates obtained between 16 February 2021 and 08 March 2024, we identified 43 (2%) samples containing MeV RNA in concentrations ranging from 2,04-6,11 genome copies/mL. MeV genotype A (vaccine strain) was co-detected in wastewater in 6 instances along with non-A (wild-type) genotypes. Comparison of wastewater and clinical fever-rash surveillance data by epidemiological week and district identified 27 district-time instances where at least one positive wastewater sample was identified, of which 14 (52%) districts reported at least one laboratory-confirmed clinical case in that same epidemiological week. Amongst districts with positive wastewater samples, wastewater surveillance detected MeV in 13/27 (48%) time-district pairs when clinical surveillance failed to detect cases. Amongst district-time instances where at least one laboratory-confirmed measles case was detected (N=127), MeV was detected in at least one wastewater sample collected in that same epidemiological week in 14 (11%) districts Interpretation Wastewater surveillance may be a useful complementary surveillance tool for identification of districts with ongoing measles circulation. MeV detection rates may be improved by real-time testing to limit RNA degradation and improved concentration and nucleic acid extraction processes. Ongoing wastewater surveillance for MeV should be conducted in order to understand the role of WES in measles control and elimination. Funding This work was funded by BMGF (INV-049271)