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A novel wastewater-based epidemiology indexing method predicts SARS-CoV-2 disease prevalence across treatment facilities in metropolitan and regional populations.

ABSTRACT: There is a need for wastewater based epidemiological (WBE) methods that integrate multiple, variously sized surveillance sites across geographic areas. We developed a novel indexing method, Melvin's Index, that provides a normalized and standardized metric of wastewater pathogen load for qPCR assays that is resilient to surveillance site variation. To demonstrate the utility of Melvin's Index, we used qRT-PCR to measure SARS-CoV-2 genomic RNA levels in influent wastewater from 19 municipal wastewater treatment facilities (WWTF's) of varying sizes and served populations across the state of Minnesota during the Summer of 2020. SARS-CoV-2 RNA was detected at each WWTF during the 20-week sampling period at a mean concentration of 8.5 × 10⁴ genome copies/L (range 3.2 × 10²-1.2 × 10⁹ genome copies/L). Lag analysis of trends in Melvin's Index values and clinical COVID-19 cases showed that increases in indexed wastewater SARS-CoV-2 levels precede new clinical cases by 15-17 days at the statewide level and by up to 25 days at the regional/county level. Melvin's Index is a reliable WBE method and can be applied to both WWTFs that serve a wide range of population sizes and to large regions that are served by multiple WWTFs.

SUBMITTER: Melvin RG

PROVIDER: S-EPMC8560786 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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A novel wastewater-based epidemiology indexing method predicts SARS-CoV-2 disease prevalence across treatment facilities in metropolitan and regional populations.

Melvin Richard G RG Hendrickson Emily N EN Chaudhry Nabiha N Georgewill Onimitein O Freese Rebecca R Schacker Timothy W TW Simmons Glenn E GE

Scientific reports 20211101 1

There is a need for wastewater based epidemiological (WBE) methods that integrate multiple, variously sized surveillance sites across geographic areas. We developed a novel indexing method, Melvin's Index, that provides a normalized and standardized metric of wastewater pathogen load for qPCR assays that is resilient to surveillance site variation. To demonstrate the utility of Melvin's Index, we used qRT-PCR to measure SARS-CoV-2 genomic RNA levels in influent wastewater from 19 municipal waste ...[more]

PMID: 34725394

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Project description:BackgroundWastewater-based epidemiology provides an opportunity for near real-time, cost-effective monitoring of community-level transmission of SARS-CoV-2. Detection of SARS-CoV-2 RNA in wastewater can identify the presence of COVID-19 in the community, but methods for estimating the numbers of infected individuals on the basis of wastewater RNA concentrations are inadequate.MethodsThis is a wastewater-based epidemiology study using wastewater samples that were collected weekly or twice a week from three sewersheds in South Carolina, USA, between either May 27 or June 16, 2020, and Aug 25, 2020, and tested for SARS-CoV-2 RNA. We developed a susceptible-exposed-infectious-recovered (SEIR) model based on the mass rate of SARS-CoV-2 RNA in the wastewater to predict the number of infected individuals, and have also provided a simplified equation to predict this. Model predictions were compared with the number of confirmed cases identified by the Department of Health and Environmental Control, South Carolina, USA, for the same time period and geographical area.FindingsWe plotted the model predictions for the relationship between mass rate of virus release and numbers of infected individuals, and we validated this prediction on the basis of estimated prevalence from individual testing. A simplified equation to estimate the number of infected individuals fell within the 95% confidence limits of the model. The rate of unreported COVID-19 cases, as estimated by the model, was approximately 11 times that of confirmed cases (ie, ratio of estimated infections for every confirmed case of 10·9, 95% CI 4·2-17·5). This rate aligned well with an independent estimate of 15 infections for every confirmed case in the US state of South Carolina.InterpretationThe SEIR model provides a robust method to estimate the total number of infected individuals in a sewershed on the basis of the mass rate of RNA copies released per day. This approach overcomes some of the limitations associated with individual testing campaigns and thereby provides an additional tool that can be used to inform policy decisions.FundingClemson University, USA.

Project description:Wastewater-based epidemiology (WBE) has emerged as a valuable approach for forecasting disease outbreaks in developed countries with a centralized sewage infrastructure. On the other hand, due to the absence of well-defined and systematic sewage networks, WBE is challenging to implement in developing countries like Bangladesh where most people live in rural areas. Identification of appropriate locations for rural Hotspot Based Sampling (HBS) and urban Drain Based Sampling (DBS) are critical to enable WBE based monitoring system. We investigated the best sampling locations from both urban and rural areas in Bangladesh after evaluating the sanitation infrastructure for forecasting COVID-19 prevalence. A total of 168 wastewater samples were collected from 14 districts of Bangladesh during each of the two peak pandemic seasons. RT-qPCR commercial kits were used to target ORF1ab and N genes. The presence of SARS-CoV-2 genetic materials was found in 98% (165/168) and 95% (160/168) wastewater samples in the first and second round sampling, respectively. Although wastewater effluents from both the marketplace and isolation center drains were found with the highest amount of genetic materials according to the mixed model, quantifiable SARS-CoV-2 RNAs were also identified in the other four sampling sites. Hence, wastewater samples of the marketplace in rural areas and isolation centers in urban areas can be considered the appropriate sampling sites to detect contagion hotspots. This is the first complete study to detect SARS-CoV-2 genetic components in wastewater samples collected from rural and urban areas for monitoring the COVID-19 pandemic. The results based on the study revealed a correlation between viral copy numbers in wastewater samples and SARS-CoV-2 positive cases reported by the Directorate General of Health Services (DGHS) as part of the national surveillance program for COVID-19 prevention. The findings of this study will help in setting strategies and guidelines for the selection of appropriate sampling sites, which will facilitate in development of comprehensive wastewater-based epidemiological systems for surveillance of rural and urban areas of low-income countries with inadequate sewage infrastructure.

Dataset Information

A novel wastewater-based epidemiology indexing method predicts SARS-CoV-2 disease prevalence across treatment facilities in metropolitan and regional populations.

Publications

A novel wastewater-based epidemiology indexing method predicts SARS-CoV-2 disease prevalence across treatment facilities in metropolitan and regional populations.

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