Estimating the effective reproduction number from wastewater (Rt): A methods comparison

Epidemics · 2025-06-18 · 9 citations

The effective reproduction number (R t ) is a dynamic indicator of current disease spread risk. Wastewater measurements of viral concentrations are known to correlate with clinical measures of diseases and have been incorporated into methods for estimating the R t . We review wastewater-based methods to estimate the R t for SARS-CoV-2 based on similarity to the reference case-based R t , ease of use, and computational requirements. Using wastewater data collected between August 1, 2022, and February 20, 2024, from 200 wastewater treatment plants across New York State, we fit eight wastewater R t models identified from the literature. Each model is compared to the R t estimated from case data for New York at the sewershed (wastewater treatment plant catchment area), county, and state levels. We find a high degree of similarity across all eight methods despite differences in model parameters and approach. Further, two methods based on the common measures of percent change and linear fit reproduced the R t from case data very well and a GLM accurately predicted case data. Model output varied between spatial scales with some models more closely estimating sewershed R t values than county R t values. Similarity to clinical models was also highly correlated with the proportion of the population served by sewer in the surveilled communities (r = 0.77). While not all methods that estimate R t from wastewater produce the same results, they all provide a way to incorporate wastewater concentration data into epidemic modeling. Our results show that straightforward measures like the percent change can produce similar results of more complex models. Based on the results, researchers and public health officials can select the method that is best for their situation. • Eight R t estimation methods are reviewed and the best ones identified • R t estimates from wastewater are dependent on sewershed size, spatial aggregation • Simple models estimate R t from wastewater accurately and are easier to compute • Wastewater R t methods are suitable for many infectious diseases • Methods that integrate viral shedding data are highly accurate

Estimating the effective reproduction number from wastewater (R _t ): A methods comparison

medRxiv · 2024-11-07

Abstract Background The effective reproduction number (R t ) is a dynamic indicator of current disease spread risk. Wastewater measurements of viral concentrations are known to correlate with clinical measures of diseases and have been incorporated into methods for estimating the R t . Methods We review wastewater-based methods to estimate the R t for SARS-CoV-2 based on similarity to the reference case-based R t , ease of use, and computational requirements. Using wastewater data collected between August 1, 2022 and February 20, 2024 from 200 wastewater treatment plants across New York State, we fit eight wastewater R t models identified from the literature. Each model is compared to the R t estimated from case data for New York at the sewershed (wastewater treatment plant catchment area), county, and state levels. Results We find a high degree of similarity across all eight methods despite differences in model parameters and approach. Further, two methods based on the common measures of percent change and linear fit reproduced the R t from case data very well and a GLM accurately predicted case data. Model output varied between spatial scales with some models more closely estimating sewershed R t values than county R t values. Similarity to clinical models was also highly correlated with the proportion of the population served by sewer in the surveilled communities (r = 0.77). Conclusions While not all methods that estimate R t from wastewater produce the same results, they all provide a way to incorporate wastewater concentration data into epidemic modeling. Our results show that straightforward measures like the percent change can produce similar results of more complex models. Based on the results, researchers and public health officials can select the method that is best for their situation. Key messages Wastewater data has been used to estimate the R t in different ways but the relative strengths and weaknesses of each method were unknown. R t estimation results from wastewater data are influenced by sewershed population size and geographic aggregation making selection of the best method dependent on the study location and available data. Estimating the R t from wastewater is desirable because wastewater data are anonymous, comprehensive, and efficient for measuring disease burden.

Wastewater Surveillance Provides 10-Days Forecasting of COVID-19 Hospitalizations Superior to Cases and Test Positivity: A Prediction Study

SSRN Electronic Journal · 2023-01-01 · 4 citations

Operationalizing an open-source dashboard for communicating results of wastewater-based epidemiology

2023-03-03 · 1 citations

COVID-19 saw the expansion of public health communication tools to manage and inform the pandemic as it evolved. While the utility of these tools is important in and of itself, it was also the case that during this time experts honed the effectiveness in a near real-time fashion. One tool that saw extensive use was the public health dashboard, web-based visualization tools that communicate information to users in quick and easy to read graphics. Dashboards were widely used prior to the pandemic in many fields, but COVID-19 saw expanded use and increased development. To date, dashboards have become an important and part of many public health surveillance programs around the world helping decisionmakers use data on a wide variety of topics including, but not limited to caseloads, hospitalizations, and to find out environmental surveillance results from testing wastewater. Wastewater surveillance provides community-based and spatially relevant data on disease transmission and trends within communities, making it an excellent candidate for dashboard development to improve understanding and use of the data to inform disease dynamics. We developed a dashboard for New York State’s wastewater surveillance program using open-source, reproducible web programming software. In just two months from September 2022 and November 2022, our dashboard received over 8,000 unique visitors with visits lasting an average of less than two minutes each. The dashboard we developed has been useful for informing COVID-19 response in New York and our methods can be adapted to other programs and pathogens. We provide descriptions of how the dashboard was developed and maintained, in addition to specific guidance for reproducing our dashboard in other areas and for other pathogens. The dashboard methods we present use the open-source program R, however, the methods can be used in other programs by researchers and institution seeking to develop public health communication tools.

Airborne levels of cadmium are correlated with urinary cadmium concentrations among young children living in the New York state city of Syracuse, USA

Environmental Research · 2023-02-09 · 20 citations

Operationalizing an open-source dashboard for communicating results of wastewater-based surveillance

MethodsX · 2023-07-27 · 6 citations

COVID-19 saw the expansion of public health tools to manage the pandemic. One tool that saw extensive use was the public health dashboard, web-based visualization tools that communicate information to users in easy-to-read graphics. Dashboards were widely used prior to the pandemic, but COVID-19 saw expanded use and development. To date, dashboards have become an important part of public health surveillance programs around the world helping decisionmakers use data to evaluate different public health metrics including caseloads, hospitalizations, and environmental surveillance results from testing wastewater. Wastewater surveillance provides community-based, spatially relevant data on disease trends within communities to assess the scale of infection in a region, which makes it an excellent candidate for dashboard development to improve public health. We developed a dashboard for New York State's wastewater surveillance program using open-source, reproducible web programming. The dashboard we developed has been used for the COVID-19 response in New York, and our methods can be adapted to other programs and pathogens. We provide:•descriptions of how the dashboard was developed and maintained•specific guidance for reproducing our dashboard in other areas and for other pathogens•fully reproducible code with step-by-step instructions for researchers and professionals to make their own data dashboards.

Wastewater surveillance provides 10-days forecasting of COVID-19 hospitalizations superior to cases and test positivity: A prediction study

Infectious Disease Modelling · 2023-10-31 · 35 citations

Background: The public health response to COVID-19 has shifted to reducing deaths and hospitalizations to prevent overwhelming health systems. The amount of SARS-CoV-2 RNA fragments in wastewater are known to correlate with clinical data including cases and hospital admissions for COVID-19. We developed and tested a predictive model for incident COVID-19 hospital admissions in New York State using wastewater data. Methods: Using county-level COVID-19 hospital admissions and wastewater surveillance covering 13.8 million people across 56 counties, we fit a generalized linear mixed model predicting new hospital admissions from wastewater concentrations of SARS-CoV-2 RNA from April 29, 2020 to June 30, 2022. We included covariates such as COVID-19 vaccine coverage in the county, comorbidities, demographic variables, and holiday gatherings. Findings: Wastewater concentrations of SARS-CoV-2 RNA correlated with new hospital admissions per 100,000 up to ten days prior to admission. Models that included wastewater had higher predictive power than models that included clinical cases only, increasing the accuracy of the model by 15%. Predicted hospital admissions correlated highly with observed admissions (r = 0.77) with an average difference of 0.013 hospitalizations per 100,000 (95% CI = [0.002, 0.025]). Interpretation: Using wastewater to predict future hospital admissions from COVID-19 is accurate and effective with superior results to using case data alone. The lead time of ten days could alert the public to take precautions and improve resource allocation for seasonal surges.

Competition, Chromium, and Contracts: The Interaction Between Bidding Intensity and Toxic Waste Releases

Society & Natural Resources · 2023-08-28

AbstractThe public procurement sector has a high impact on the environment including pollution from manufacturing. Competition is the primary way that the United States government ensures that the most efficient facilities receive contracts, but whether this competition leads to more, or less, pollution is unknown. We explore the impact of competition for contracts on contractor pollution in sectors that handle chromium, a toxic, yet necessary, component in many goods. We find that competition alone has negligible impact on overall chromium releases among contractors; however, the way chromium is used in the manufacturing process does. Contractors that use chromium as a component report higher releases of chromium waste than contractors that only use chromium in non-incorporative ways. However, when contractors face higher competition for contracts, pollution levels significantly decrease. This suggests that both competition and the use of the metal are important. Findings support a complex association between competition and pollution generation.Keywords: Bayesian modelbidsindustrial pollutionporter hypothesisprocurementrace to the bottom Additional informationFundingThe research presented here was supported by the SUNY College of Environmental Science and Forestry (ESF) Graduate Program in Environmental Science, The Environmental Studies Program at SUNY-ESF, and the SUNY Discovery Challenge. Additional support came from the National Science Foundation Grant no. 1534976. Methods used in this paper were supported by training received at the National Socio-Environmental Synthesis Center (National Science Foundation award DBI-1639145 to the University of Maryland). Portions of this article were originally published in the dissertation work of author Dustin Hill (Hill, D.T. 2021. Toxic Procurement: An Examination of United States Federal Government Contracts, Disproportionality, and Firm Environmental Performance, 2001-2012. State University of New York College of Environmental Science and Forestry. ProQuest Dissertations Publishing, 2021. 29053154.).

Coupling freedom from disease principles and early warning from wastewater surveillance to improve health security

PNAS Nexus · 2022-03-01 · 27 citations

Abstract Infectious disease surveillance is vitally important to maintaining health security, but these efforts are challenged by the pace at which new pathogens emerge. Wastewater surveillance can rapidly obtain population-level estimates of disease transmission, and we leverage freedom from disease principles to make use of nondetection of SARS-CoV-2 in wastewater to estimate the probability that a community is free from SARS-CoV-2 transmission. From wastewater surveillance of 24 treatment plants across upstate New York from May through December of 2020, trends in the intensity of SARS-CoV-2 in wastewater correlate with trends in COVID-19 incidence and test positivity (⍴ > 0.5), with the greatest correlation observed for active cases and a 3-day lead time between wastewater sample date and clinical test date. No COVID-19 cases were reported 35% of the time the week of a nondetection of SARS-CoV-2 in wastewater. Compared to the United States Centers for Disease Control and Prevention levels of transmission risk, transmission risk was low (no community spared) 50% of the time following nondetection, and transmission risk was moderate or lower (low community spread) 92% of the time following nondetection. Wastewater surveillance can demonstrate the geographic extent of the transmission of emerging pathogens, confirming that transmission risk is either absent or low and alerting of an increase in transmission. If a statewide wastewater surveillance platform had been in place prior to the onset of the COVID-19 pandemic, policymakers would have been able to complement the representative nature of wastewater samples to individual testing, likely resulting in more precise public health interventions and policies.

Targeted pollution management can significantly reduce toxic emissions while limiting adverse effects on employment in US manufacturing

Environmental Science & Policy · 2022-11-11 · 9 citations

Analyzing the relationship between employment and toxic emissions at over 25,000 US manufacturing facilities between 1998 and 2012 demonstrates that significant reductions in toxic pollution can be achieved without causing equivalent reductions in employment. Three simulations provide a comparison of the combined effects on toxic releases and employment of management strategies targeted at major polluters versus strategies that encompass a random or median subset of facilities or industries. Targeted strategies are effective because toxic emissions are highly disproportionally distributed. A handful of facilities and industries account for the majority of toxic hazard released in the US manufacturing sector. Moreover, these highly polluting facilities and industries do not employ significantly more workers than peer, lower polluting facilities and industries. The research challenges the narrative that protecting the environment must come at a significant cost to economic activity. Rather, targeting egregious polluters can offer an important inroad for significantly reducing industrial pollution while limiting adverse effects on employment.