Where Does Wastewater-Based Epidemiology Fall in Medical Student Education?

Doctors are well-trained in the collection, analysis, and interpretation of individual stool or urine sample data; however, wastewater-based epidemiology (WBE) combines the excretion of many community members into an anonymous health sample tied to a geographic location. We advocate for the inclusion of WBE in medical education. WBE offers physicians an opportunity to better care for patients with diseases seen at health clinics and doctors' offices, customize and inform treatment, and accept positive results as true positives, backed by the contextual information provided by wastewater findings. It is also a tool to combat biased or misinformed risk perceptions. Medical education should include how to evaluate wastewater information presented, detect inconsistencies, and determine applicability; just as medical students are taught to do with data from other sources.

Dynamic SARS-CoV-2 surveillance model combining seroprevalence and wastewater concentrations for post-vaccine disease burden estimates.

BACKGROUND: Despite wide scale assessments, it remains unclear how large-scale severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination affected the wastewater concentration of the virus or the overall disease burden as measured by hospitalization rates. METHODS: We used weekly SARS-CoV-2 wastewater concentration with a stratified random sampling of seroprevalence, and linked vaccination and hospitalization data, from April 2021-August 2021 in Jefferson County, Kentucky (USA). Our susceptible ( S ), vaccinated ( V ), variant-specific infected ( I 1 and I 2 ), recovered ( R ), and seropositive ( T ) model ( S V I 2 R T ) tracked prevalence longitudinally. This was related to wastewater concentration. RESULTS: Here we show the 64% county vaccination rate translate into about a 61% decrease in SARS-CoV-2 incidence. The estimated effect of SARS-CoV-2 Delta variant emergence is a 24-fold increase of infection counts, which correspond to an over 9-fold increase in wastewater concentration. Hospitalization burden and wastewater concentration have the strongest correlation (r = 0.95) at 1 week lag. CONCLUSIONS: Our study underscores the importance of continuing environmental surveillance post-vaccine and provides a proof-of-concept for environmental epidemiology monitoring of infectious disease for future pandemic preparedness.

It is unclear how large-scale COVID-19 vaccination impacts wastewater concentration or overall disease burden. Here, we developed a mathematical surveillance model that allows estimation of overall vaccine impact based on the amount of SARS-CoV-2 in wastewater, seroprevalence and the number of cases admitted to hospitals between April 2021­August 2021 in Jefferson County, Kentucky USA. We found that a 64% vaccination coverage correlated to a 61% decrease in COVID-19 cases. The emergence of the SARS-CoV-2 Delta variant during the time of the surveillance directly correlated with a sharp increase in infection incidence as well as viral counts in wastewater. The hospitalization burden was closely reflected by the viral count found in the wastewater, indicating that post-vaccine environmental surveillance can be an effective method of estimating changing disease prevalence in future pandemics.

Vibrio cholerae and Salmonella Typhi culture-based wastewater or non-sewered sanitation surveillance in a resource-limited region.

BACKGROUND: In resource-limited regions, relying on individual clinical results to monitor community diseases is sometimes not possible. Establishing wastewater and non-sewered sanitation surveillance systems can offer opportunities to improve community health. OBJECTIVE: We provide our experience of establishing a wastewater and non-sewered sanitation surveillance laboratory in Malawi, a resource-limited region, for Vibrio cholerae and Salmonella serotype Typhi. METHODS: Three locations (inclusive of 8 discrete sample collection sites in total) in the Blantyre District were studied for nine weeks, from September 6 to November 1, 2022. Grab samples were collected weekly. We piloted locally available culture-based medical diagnostic methods for V. cholerae and S. Typhi in wastewater, followed by confirmation analysis of the isolates using reverse transcription polymerase chain reaction (RT-PCR). RESULTS: Bacterial counts ranged from up to 106 colony-forming units/mL for V. cholerae and up to 107 colony-forming units/mL for S. Typhi. RT-PCR of the isolates showed that the available culture-based medical diagnostic methods were successful in detecting V. cholerae but were less accurate for S. Typhi in wastewater. IMPACT STATEMENT: This experience serves as a catalyst for the development and validation of alternative wastewater surveillance analytical methods that are not dependent solely on RT-PCR. In this field trial conducted in Africa, new data-driven approaches were developed to promote early-level wastewater research and expand analysis options in resource-limited settings. Although culture-based methods are labor-intensive and have some limitations, we suggest initially leveraging the overlap with the locally available medical testing capacity for V. cholerae, whereas S. Typhi with RT-PCR may still be required. Wastewater analysis may be acceptable for V. cholerae and S. Typhi, which have a high degree of clinical case underreporting, fecal shedding, short incubation periods, and clear outbreak trends, predominantly in low- and middle-income countries.

Predictive power of wastewater for nowcasting infectious disease transmission: A retrospective case study of five sewershed areas in Louisville, Kentucky.

BACKGROUND: Epidemiological nowcasting traditionally relies on count surveillance data. The availability and quality of such count data may vary over time, limiting representation of true infections. Wastewater data correlates with traditional surveillance data and may provide additional value for nowcasting disease trends. METHODS: We obtained SARS-CoV-2 case, death, wastewater, and serosurvey data for Jefferson County, Kentucky (USA), between August 2020 and March 2021, and parameterized an existing nowcasting model using combinations of these data. We assessed the predictive performance and variability at the sewershed level and compared the effects of adding or replacing wastewater data to case and death reports. FINDINGS: Adding wastewater data minimally improved the predictive performance of nowcasts compared to a model fitted to case and death data (Weighted Interval Score (WIS) 0.208 versus 0.223), and reduced the predictive performance compared to a model fitted to deaths data (WIS 0.517 versus 0.500). Adding wastewater data to deaths data improved the nowcasts agreement to estimates from models using cases and deaths data. These findings were consistent across individual sewersheds as well as for models fit to the aggregated total data of 5 sewersheds. Retrospective reconstructions of epidemiological dynamics created using different combinations of data were in general agreement (coverage >75%). INTERPRETATION: These findings show wastewater data may be valuable for infectious disease nowcasting when clinical surveillance data are absent, such as early in a pandemic or in low-resource settings where systematic collection of epidemiologic data is difficult.

Wastewater-Informed Digital Advertising as a COVID-19 Geotargeted Neighborhood Intervention: Jefferson County, Kentucky, 2021-2022.

We sought to deliver a geotargeted digital health advertising intervention. We assessed risk of community infection through an integrated public health and wastewater rubric and delivered advertisements between November 2021 and April 2022 in Louisville, Kentucky. The average daily click-through rates for the campaigns were 0.19%, 0.15%, and 0.13%. Results show potential for digital public health interventions that are geographically anchored to subcity sewersheds and community interest and willingness to engage with targeted wastewater-themed public health messaging. (Am J Public Health. 2024;114(1):34-37. https://doi.org/10.2105/AJPH.2023.307439).

What is the functional reach of wastewater surveillance for respiratory viruses, pathogenic viruses of concern, and bacterial antibiotic resistance genes of interest?

BACKGROUND: Despite a clear appreciation of the impact of human pathogens on community health, efforts to understand pathogen dynamics within populations often follow a narrow-targeted approach and rely on the deployment of specific molecular probes for quantitative detection or rely on clinical detection and reporting. MAIN TEXT: Genomic analysis of wastewater samples for the broad detection of viruses, bacteria, fungi, and antibiotic resistance genes of interest/concern is inherently difficult, and while deep sequencing of wastewater provides a wealth of information, a robust and cooperative foundation is needed to support healthier communities. In addition to furthering the capacity of high-throughput sequencing wastewater-based epidemiology to detect human pathogens in an unbiased and agnostic manner, it is critical that collaborative networks among public health agencies, researchers, and community stakeholders be fostered to prepare communities for future public health emergencies or for the next pandemic. A more inclusive public health infrastructure must be built for better data reporting where there is a global human health risk burden. CONCLUSIONS: As wastewater platforms continue to be developed and refined, high-throughput sequencing of human pathogens in wastewater samples will emerge as a gold standard for understanding community health.

Addressing the challenges of establishing quality wastewater or non-sewered sanitation-based surveillance, including laboratory and epidemiological considerations, in Malawi.

Learning from clinical laboratories, wastewater or environmental (including non-sewered sanitation) environmental microbiology laboratories can be established in resource-limited settings that focus on pathogen detection and pandemic prevention. Transparent discussions on the laboratory challenges and adaptations required for this can help meet the future requirements of health research and surveillance. This report aims to describe the challenges encountered when setting up a wastewater or environmental laboratory for multipathogen surveillance in Malawi, a resource-limited setting, as well as the lessons learnt. We identified nine unifying themes: what to monitor, human resource capacity, indicators of data quality, equipment availability, supply of consumable goods, ongoing operation and maintenance of the laboratory, application of localised guidelines for laboratory operations, lack of real-time clinical correlation for calibration and localised ethical considerations. Over our 6-month timeline, only Salmonella typhi, Vibrio cholerae and severe acute respiratory syndrome coronavirus 2 analyses were set-up. However, we were unable to set-up measles and tuberculosis analyses owing largely to supply delays. By establishing this system at a public higher education academic laboratory in Malawi, we have ensured that ongoing capacity building and piloting of public health work is conducted in the country, rather than relying on non-governmental organisations or reference laboratory support beyond national borders. This work is not intended to replace clinical testing but rather demonstrates the potential for adapting higher education academic laboratory infrastructure to add wastewater or environmental (including non-sewered sanitation) samples, where appropriate, as additive epidemiological data for better pandemic preparedness.

Wastewater-based epidemiology for comprehensive communitywide exposome surveillance: A gradient of metals exposure.

Community wastewater surveillance is an established means to measure health threats. Exposure to toxic metals as one of the key environmental contaminants has been attracting public health attention as exposure can be related to contamination across air, water, and soil as well as associated with individual factors. This research uses Jefferson County, Kentucky, as an urban exposome case study to analyze sub-county metal concentrations in wastewater as a possible indicator of community toxicant exposure risk, and to test the feasibility of using wastewater to identify potential community areas of elevated metals exposure. Variability in wastewater metal concentrations were observed across the county; 19 of the 26 sites had one or more metal results greater than one standard deviation above the mean and were designated areas of concern. Additionally, thirteen of the nineteen sites were of increased concern with levels greater than two standard deviations above the mean. This foundational research found variability in several instances between smaller nested upstream contributing neighborhood sewersheds when measured in the associated downstream treatment plant. Wastewater provides an opportunity to look at integrated toxicology to complement other toxicology data, looking at where people live and what toxicants need to be focused on to protect the health of people in that area.

Using wastewater to overcome health disparities among rural residents.

The SARS-CoV-2 pandemic highlighted the need for novel tools to promote health equity. There has been a historical legacy around the location and allocation of public facilities (such as health care) focused on efficiency, which is not attainable in rural, low-density, United States areas. Differences in the spread of the disease and outcomes of infections have been observed between urban and rural populations throughout the COVID-19 pandemic. The purpose of this article was to review rural health disparities related to the SARS-CoV-2 pandemic while using evidence to support wastewater surveillance as a potentially innovative tool to address these disparities more widely. The successful implementation of wastewater surveillance in resource-limited settings in South Africa demonstrates the ability to monitor disease in underserved areas. A better surveillance model of disease detection among rural residents will overcome issues around the interactions of a disease and social determinants of health. Wastewater surveillance can be used to promote health equity, particularly in rural and resource-limited areas, and has the potential to identify future global outbreaks of endemic and pandemic viruses.

Generative AI as a Tool for Environmental Health Research Translation.

One valuable application for generative artificial intelligence (AI) is summarizing research studies for non-academic readers. We submitted five articles to Chat Generative Pre-trained Transformer (ChatGPT) for summarization, and asked the article's author to rate the summaries. Higher ratings were assigned to more insight-oriented activities, such as the production of eighth-grade reading level summaries, and summaries highlighting the most important findings and real-world applications. The general summary request was rated lower. For the field of environmental health science, no-cost AI technology such as ChatGPT holds the promise to improve research translation, but it must continue to be improved (or improve itself) from its current capability.

Beyond COVID-19: Designing Inclusive Public Health Surveillance by Including Wastewater Monitoring.

Wastewater-based epidemiology is a promising and expanding public health surveillance method. The current wastewater testing trajectory to monitor primarily at community wastewater treatment plants was necessitated by immediate needs of the pandemic. Going forward, specific consideration should be given to monitoring vulnerable and underserved communities to ensure inclusion and rapid response to public health threats. This is particularly important when clinical testing data are insufficient to characterize community virus levels and spread in specific locations. Now is a timely call to action for equitably protecting health in the United States, which can be guided with intentional and inclusive wastewater monitoring.

Stratified Simple Random Sampling Versus Volunteer Community-Wide Sampling for Estimates of COVID-19 Prevalence.

Objectives. To evaluate community-wide prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using stratified simple random sampling. Methods. We obtained data for the prevalence of SARS-CoV-2 in Jefferson County, Kentucky, from adult random (n = 7296) and volunteer (n = 7919) sampling over 8 waves from June 2020 through August 2021. We compared results with administratively reported rates of COVID-19. Results. Randomized and volunteer samples produced equivalent prevalence estimates (P < .001), which exceeded the administratively reported rates of prevalence. Differences between them decreased as time passed, likely because of seroprevalence temporal detection limitations. Conclusions. Structured targeted sampling for seropositivity against SARS-CoV-2, randomized or voluntary, provided better estimates of prevalence than administrative estimates based on incident disease. A low response rate to stratified simple random sampling may produce quantified disease prevalence estimates similar to a volunteer sample. Public Health Implications. Randomized targeted and invited sampling approaches provided better estimates of disease prevalence than administratively reported data. Cost and time permitting, targeted sampling is a superior modality for estimating community-wide prevalence of infectious disease, especially among Black individuals and those living in disadvantaged neighborhoods. (Am J Public Health. 2023;113(7):768-777. https://doi.org/10.2105/AJPH.2023.307303).

Online dashboards for SARS-CoV-2 wastewater data need standard best practices: An environmental health communication agenda.

The COVID-19 pandemic has highlighted the benefits of wastewater surveillance to supplement clinical data. Numerous online information dashboards have been rapidly, and typically independently, developed to communicate environmental surveillance data to public health officials and the public. In this study, we review dashboards presenting SARS-CoV-2 wastewater data and propose a path toward harmonization and improved risk communication. A list of 127 dashboards representing 27 countries was compiled. The variability was high and encompassed aspects including the graphics used for data presentation (e.g., line/bar graphs, maps, and tables), log versus linear scale, and 96 separate ways of labeling SARS-CoV-2 wastewater concentrations. Globally, dashboard presentations also differed by region. Approximately half of the dashboards presented clinical case data, and 25% presented variant monitoring. Only 30% of dashboards provided downloadable source data. While any single dashboard is likely useful in its own context and locality, the high variation across dashboards at best prevents optimal use of wastewater surveillance data on a broader geographical scale and at worst could lead to risk communication issues and the potential for public health miscommunication. There is a great opportunity to improve scientific communication through the adoption of uniform data presentation conventions, standards, and best practices in this field.

Generative AI as a Tool for Environmental Health Research Translation.

Generative artificial intelligence, popularized by services like ChatGPT, has been the source of much recent popular attention for publishing health research. Another valuable application is in translating published research studies to readers in non-academic settings. These might include environmental justice communities, mainstream media outlets, and community science groups. Five recently published (2021-2022) open-access, peer-reviewed papers, authored by University of Louisville environmental health investigators and collaborators, were submitted to ChatGPT. The average rating of all summaries of all types across the five different studies ranged between 3 and 5, indicating good overall content quality. ChatGPT’s general summary request was consistently rated lower than all other summary types. Whereas higher ratings of 4 and 5 were assigned to the more synthetic, insight-oriented activities, such as the production of a plain language summaries suitable for an 8 th grade reading level and identifying the most important finding and real-world research applications. This is a case where artificial intelligence might help level the playing field, for example by creating accessible insights and enabling the large-scale production of high-quality plain language summaries which would truly bring open access to this scientific information. This possibility, combined with the increasing public policy trends encouraging and demanding free access for research supported with public funds, may alter the role journal publications play in communicating science in society. For the field of environmental health science, no-cost AI technology such as ChatGPT holds the promise to improve research translation, but it must continue to be improved (or improve itself) from its current capability.

Wastewater and seroprevalence for pandemic preparedness: variant analysis, vaccination effect, and hospitalization forecasting for SARS-CoV-2, in Jefferson County, Kentucky.

Despite wide scale assessments, it remains unclear how large-scale SARS-CoV-2 vaccination affected the wastewater concentration of the virus or the overall disease burden as measured by hospitalization rates. We used weekly SARS-CoV-2 wastewater concentration with a stratified random sampling of seroprevalence, and linked vaccination and hospitalization data, from April 2021-August 2021 in Jefferson County, Kentucky (USA). Our susceptible (S), vaccinated (V), variant-specific infected I1 and I2, recovered (R), and seropositive (T) model SVI2RT tracked prevalence longitudinally. This was related to wastewater concentration. The 64% county vaccination rate translated into about 61% decrease in SARS-CoV-2 incidence. The estimated effect of SARS-CoV-2 Delta variant emergence was a 24-fold increase of infection counts, which corresponded to an over 9-fold increase in wastewater concentration. Hospitalization burden and wastewater concentration had the strongest correlation (r = 0.95) at 1 week lag. Our study underscores the importance of continued environmental surveillance post-vaccine and provides a proof-of-concept for environmental epidemiology monitoring of infectious disease for future pandemic preparedness.

The Detection of Periodic Reemergence Events of SARS-CoV-2 Delta Strain in Communities Dominated by Omicron.

Despite entering an endemic phase, SARS-CoV-2 remains a significant burden to public health across the global community. Wastewater sampling has consistently proven utility to understanding SARS-CoV-2 prevalence trends and genetic variation as it represents a less biased assessment of the corresponding communities. Here, we report that ongoing monitoring of SARS-CoV-2 genetic variation in samples obtained from the wastewatersheds of the city of Louisville in Jefferson county Kentucky has revealed the periodic reemergence of the Delta strain in the presence of the presumed dominant Omicron strain. Unlike previous SARS-CoV-2 waves/emergence events, the Delta reemergence events were geographically restricted in the community and failed to spread into other areas as determined by wastewater analyses. Moreover, the reemergence of the Delta strain did not correlate with vaccination rates as communities with lower relative vaccination have been, to date, not affected. Importantly, Delta reemergence events correlate with increased public health burdens, as indicated by increased daily case rates and mortality relative to non-Delta wastewatershed communities. While the underlying reasons for the reemergence of the Delta variant remain unclear, these data reaffirm the ongoing importance of wastewater genomic analyses towards understanding SARS-CoV-2 as it enters the endemic phase.

Nationwide public perceptions regarding the acceptance of using wastewater for community health monitoring in the United States.

To assess the levels of infection across communities during the coronavirus disease 2019 pandemic, researchers have measured severe acute respiratory syndrome coronavirus 2 RNA in feces dissolved in sewer water. This activity is colloquially known as sewer monitoring and is referred to as wastewater-based epidemiology in academic settings. Although global ethical principles have been described, sewer monitoring is unregulated for health privacy protection when used for public health surveillance in the United States. This study used Qualtrics XM, a national research panel provider, to recruit participants to answer an online survey. Respondents (N = 3,083) answered questions about their knowledge, perceptions of what is to be monitored, where monitoring should occur, and privacy concerns related to sewer monitoring as a public health surveillance tool. Furthermore, a privacy attitude questionnaire was used to assess the general privacy boundaries of respondents. Participants were more likely to support monitoring for diseases (92%), environmental toxins (92%), and terrorist threats (88%; e.g., anthrax). Two-third of the respondents endorsed no prohibition on location sampling scale (e.g., monitoring single residence to entire community was acceptable); the most common location category respondents wanted to prohibit sampling was at personal residences. Sewer monitoring is an emerging technology, and our study sheds light on perceptions that could benefit from educational programs in areas where public acceptance is comparatively lower. Respondents clearly communicated guard rails for sewer monitoring, and public opinion should inform future policy, application, and regulation measures.

Quantifying the relationship between sub-population wastewater samples and community-wide SARS-CoV-2 seroprevalence.

Robust epidemiological models relating wastewater to community disease prevalence are lacking. Assessments of SARS-CoV-2 infection rates have relied primarily on convenience sampling, which does not provide reliable estimates of community disease prevalence due to inherent biases. This study conducted serial stratified randomized samplings to estimate the prevalence of SARS-CoV-2 antibodies in 3717 participants, and obtained weekly samples of community wastewater for SARS-CoV-2 concentrations in Jefferson County, KY (USA) from August 2020 to February 2021. Using an expanded Susceptible-Infected-Recovered model, the longitudinal estimates of the disease prevalence were obtained and compared with the wastewater concentrations using regression analysis. The model analysis revealed significant temporal differences in epidemic peaks. The results showed that in some areas, the average incidence rate, based on serological sampling, was 50 % higher than the health department rate, which was based on convenience sampling. The model-estimated average prevalence rates correlated well with the wastewater (correlation = 0.63, CI (0.31,0.83)). In the regression analysis, a one copy per ml-unit increase in weekly average wastewater concentration of SARS-CoV-2 corresponded to an average increase of 1-1.3 cases of SARS-CoV-2 infection per 100,000 residents. The analysis indicates that wastewater may provide robust estimates of community spread of infection, in line with the modeled prevalence estimates obtained from stratified randomized sampling, and is therefore superior to publicly available health data.