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

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.

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

Air pollution is a serious public health issue with early childhood exposure being of high concern because of the greater risk that children might experience negative health outcomes. Industrial sources in and near communities are one potential path of exposure that children might face with greater levels of air pollution correlating with higher levels of toxicants detected in children. We compare estimated ambient air concentrations of Cadmium (Cd) to a cohort (n = 281) of 9 to 11-year old children during their early childhood years (0-5 years of age) in a mid-size city in Upstate New York. Levels of Cd air pollution are compared to children's urine-Cd levels. Urine has been shown to be a superior biomarker to blood for Cd exposure particularly for longer-term exposures. We find that participants who reside in households that faced greater Cd air pollution during the child's early years have higher urine-Cd levels. This association is stable and stronger than previously presented associations for blood-Cd. Findings support expanded use of air modelling data for risk screening to reduce the potential health burden that industrial pollution can have.

Wastewater Surveillance for Infectious Disease: A Systematic Review.

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been shown to be a valuable source of information regarding SARS-CoV-2 transmission and coronavirus disease 2019 (COVID-19) cases. Although the method has been used for several decades to track other infectious diseases, there has not been a comprehensive review outlining all of the pathogens that have been surveilled through wastewater. Herein we identify the infectious diseases that have been previously studied via wastewater surveillance prior to the COVID-19 pandemic. Infectious diseases and pathogens were identified in 100 studies of wastewater surveillance across 38 countries, as were themes of how wastewater surveillance and other measures of disease transmission were linked. Twenty-five separate pathogen families were identified in the included studies, with the majority of studies examining pathogens from the family Picornaviridae, including polio and nonpolio enteroviruses. Most studies of wastewater surveillance did not link what was found in the wastewater to other measures of disease transmission. Among those studies that did, the value reported varied by study. Wastewater surveillance should be considered as a potential public health tool for many infectious diseases. Wastewater surveillance studies can be improved by incorporating other measures of disease transmission at the population-level including disease incidence and hospitalizations.

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

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.

Wastewater monitoring, surveillance and epidemiology: a review of terminology for a common understanding.

Response to the COVID-19 (coronavirus disease 2019) pandemic saw an unprecedented uptake in bottom-up efforts to incorporate community wastewater testing to inform public health. While not a new strategy, various specialized scientific advancements were achieved to establish links between wastewater concentrations of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and public health outcomes. Maximizing public health benefit requires collaboration among a broad range of disciplinary experts, each bringing their own historical context to the central goal of protecting human health. One challenge has been a lack of shared terminology. Standardized terminology would provide common ground for this rapidly growing field. Based on the review herein, we recommend categorical usage of the term 'wastewater-based epidemiology' to describe the science of relating microbes, chemicals or other analytes in wastewater to public health. We further recommend the term 'wastewater surveillance' to describe continuous monitoring of health outcomes (either microbes or chemicals) via wastewater. We suggest that 'wastewater tracking' and 'wastewater tracing' be used in more narrow ways, specifically when trying to find the source of a health risk. Finally, we suggest that the phrase 'wastewater monitoring' be abandoned, except in rare circumstances when ensuring wastewater discharge is safe from a public health perspective.

Linking metal (Pb, Hg, Cd) industrial air pollution risk to blood metal levels and cardiovascular functioning and structure among children in Syracuse, NY.

BACKGROUND: Exposure to air pollution has been linked to individual health effects in occupational environments and communities proximate to air pollution sources. Use of estimated chemical concentrations from the Risk Screening Environmental Indicators (RSEI) model, derived from the Toxics Release Inventory, can help approximate some contributions to individual lifetime exposure to risk from air pollution and holds potential for linkages with specific health outcome data. OBJECTIVES: Our objectives were: (1) use regression modeling to test for associations between observed blood metal concentrations in children and RSEI total air concentrations of the same metals released from proximate manufacturing facilities; (2) determine the relative contribution of RSEI air pollution to blood metal concentrations; and (3) examine associations between chronic metal exposure and cardiovascular functioning and structure in study participants. METHODS: Using data synthesis methods and regression modeling we linked individual blood-based levels of lead, mercury, and cadmium(Pb, Hg, Cd) and cardiovascular functioning and structure to proximate industrial releases of the same metals captured by the Environmental Protection Agency's (EPA) RSEI geographic microdata. RESULTS: We found that RSEI-derived ground-level ambient air concentrations of Hg and Cd were a significant predictor of blood metal levels, when controlling for covariates and other exposure variables. In addition to associations with blood metal findings, RSEI concentrations also predicted cardiovascular dysfunction and risk including changes in left-ventricular mass, blood pressure, and heart rate. DISCUSSION: Right-to-know data, such as EPA's RSEI, can be linked to objective health outcomes, rather than simply serving as a non-specific risk estimate. These data can serve as a proxy for hazard exposure and should be used more widely to understand the dynamics of environmental exposure. Furthermore, since these data are both a product of and contribute to regulatory decision making, they could serve as an important link between disease risk and translation-orientated national environmental health policy.

High-throughput wastewater analysis for substance use assessment in central New York during the COVID-19 pandemic.

Wastewater entering sewer networks represents a unique source of pooled epidemiological information. In this study, we coupled online solid-phase extraction with liquid chromatography-high resolution mass spectrometry to achieve high-throughput analysis of health and lifestyle-related substances in untreated municipal wastewater during the coronavirus disease 2019 (COVID-19) pandemic. Twenty-six substances were identified and quantified in influent samples collected from six wastewater treatment plants during the COVID-19 pandemic in central New York. Over a 12 week sampling period, the mean summed consumption rate of six major substance groups (i.e., antidepressants, antiepileptics, antihistamines, antihypertensives, synthetic opioids, and central nervous system stimulants) correlated with disparities in household income, marital status, and age of the contributing populations as well as the detection frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater and the COVID-19 test positivity in the studied sewersheds. Nontarget screening revealed the covariation of piperine, a nontarget substance, with SARS-CoV-2 RNA in wastewater collected from one of the sewersheds. Overall, this proof-of-the-concept study demonstrated the utility of high-throughput wastewater analysis for assessing the population-level substance use patterns during a public health crisis such as COVID-19.

Risk-based targeting: identifying disproportionalities in the sources and effects of industrial pollution.

OBJECTIVES: I assessed the distribution of relative health risk from industrial air pollution in Milwaukee, Wisconsin, and the extent to which risk was disproportionately attributable to a minority of facilities. METHODS: I spatially linked data on airborne emissions, health risk, and sociodemographics by census tract, coupling disproportionality measurements from 2 perspectives: the health risk borne by communities and the harms produced by individual polluters. RESULTS: Of Milwaukee's 307 census tracts, 90 warranted the highest environmental justice concern. Striking variations in risk production existed between industrial polluters. Of 299 facilities with reported emissions, 30 (10%) contributed 90% of all health risk. CONCLUSIONS: This research adds to an emerging body of work connecting environmental health risk, environmental justice, and corporate responsibility. Findings support the hypothesis that relatively few heavy polluters create most environmental health risk. Environmental policy often devotes insufficient attention to such outliers, in part because of the questionable assumption that pollution is economically necessary for jobs or essential products. Increased emphasis on risk-based targeting of the worst polluters could significantly improve environmental quality and health in overburdened communities.