ABSTRACT
Community surveillance surveys offer an opportunity to obtain important and timely public health information that may help local municipalities guide their response to public health threats. The objective of this paper is to present approaches, challenges, and solutions from SARS-CoV-2 surveillance surveys conducted in different settings by 2 research teams. For rapid assessment of a representative sample, a 2-stage cluster sampling design was developed by an interdisciplinary team of researchers at Oregon State University between April 2020 and June 2021 across 6 Oregon communities. In 2022, these methods were adapted for New York communities by a team of veterinary, medical, and public health practitioners. Partnerships were established with local medical facilities, health departments, COVID-19 testing sites, and health and public safety staff. Field staff were trained using online modules, field manuals describing survey methods and safety protocols, and in-person meetings with hands-on practice. Private and secure data integration systems and public awareness campaigns were implemented. Pilot surveys and field previews revealed challenges in survey processes that could be addressed before surveys proceeded. Strong leadership, robust trainings, and university-community partnerships proved critical to successful outcomes. Cultivating mutual trust and cooperation among stakeholders is essential to prepare for the next pandemic.
ABSTRACT
BACKGROUND: Positive correlations have been reported between wastewater SARS-CoV-2 concentrations and a community's burden of infection, disease or both. However, previous studies mostly compared wastewater to clinical case counts or nonrepresentative convenience samples, limiting their quantitative potential. OBJECTIVES: This study examined whether wastewater SARS-CoV-2 concentrations could provide better estimations for SARS-CoV-2 community prevalence than reported cases of COVID-19. In addition, this study tested whether wastewater-based epidemiology methods could identify neighborhood-level COVID-19 hotspots and SARS-CoV-2 variants. METHODS: Community SARS-CoV-2 prevalence was estimated from eight randomized door-to-door nasal swab sampling events in six Oregon communities of disparate size, location, and demography over a 10-month period. Simultaneously, wastewater SARS-CoV-2 concentrations were quantified at each community's wastewater treatment plant and from 22 Newport, Oregon, neighborhoods. SARS-CoV-2 RNA was sequenced from all positive wastewater and nasal swab samples. Clinically reported case counts were obtained from the Oregon Health Authority. RESULTS: Estimated community SARS-CoV-2 prevalence ranged from 8 to 1,687/10,000 persons. Community wastewater SARS-CoV-2 concentrations ranged from 2.9 to 5.1 log10 gene copies per liter. Wastewater SARS-CoV-2 concentrations were more highly correlated (Pearson's r=0.96; R2=0.91) with community prevalence than were clinically reported cases of COVID-19 (Pearson's r=0.85; R2=0.73). Monte Carlo simulations indicated that wastewater SARS-CoV-2 concentrations were significantly better than clinically reported cases at estimating prevalence (p<0.05). In addition, wastewater analyses determined neighborhood-level COVID-19 hot spots and identified SARS-CoV-2 variants (B.1 and B.1.399) at the neighborhood and city scales. DISCUSSION: The greater reliability of wastewater SARS-CoV-2 concentrations over clinically reported case counts was likely due to systematic biases that affect reported case counts, including variations in access to testing and underreporting of asymptomatic cases. With these advantages, combined with scalability and low costs, wastewater-based epidemiology can be a key component in public health surveillance of COVID-19 and other communicable infections. https://doi.org/10.1289/EHP10289.
Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Humans , Oregon/epidemiology , Prevalence , RNA, Viral/genetics , Reproducibility of Results , SARS-CoV-2/genetics , Wastewater , Wastewater-Based Epidemiological MonitoringABSTRACT
Water scarcity afflicts societies worldwide. Anticipating water shortages is vital because of water's indispensable role in social-ecological systems. But the challenge is daunting due to heterogeneity, feedbacks, and water's spatial-temporal sequencing throughout such systems. Regional system models with sufficient detail can help address this challenge. In our study, a detailed coupled human-natural system model of one such region identifies how climate change and socioeconomic growth will alter the availability and use of water in coming decades. Results demonstrate how water scarcity varies greatly across small distances and brief time periods, even in basins where water may be relatively abundant overall. Some of these results were unexpected and may appear counterintuitive to some observers. Key determinants of water scarcity are found to be the cost of transporting and storing water, society's institutions that circumscribe human choices, and the opportunity cost of water when alternative uses compete.
Subject(s)
Climate Change , Conservation of Natural Resources/methods , Ecosystem , Water Resources/supply & distribution , Water Supply/statistics & numerical data , Forests , Humans , Models, Theoretical , WaterABSTRACT
Persistent stress from anthropogenic metal deposition in lotic ecosystems is a global concern. This long-term selective pressure shapes hyporheic microbial assemblages and influences ecosystem functional integrity. We hypothesized that, even after 100 years of adaptation opportunity, ecosystem function remains inhibited by sediment-associated metal stress and that the Resazurin Resorufin Smart Tracer can be used to quantify this impact. The Resazurin Resorufin Smart Tracer system is applied here in a novel capacity as an indicator of ecosystem function by quantifying ecosystem respiration of microbial communities. Hyporheic microbial communities exposed to differing magnitudes of chronic metal stress were compared to pristine reference sites in controlled column experiments. A Markov chain Monte Carlo technique was developed to solve the inverse smart tracer transport equation to derive community respiration data. Results suggest metals inhibit respiration by 13-30% relative to reference sites and this inhibition is directly related to the level of in situ metal stress. We demonstrate the first application of a hydrologic smart tracer as a functional indicator of ecological integrity within anthropogenically influenced flowing water systems and provide data suggesting resilience is limited in hyporheic ecosystems even after more than a century of microbial adaption to chronic pollutants.
Subject(s)
Bacteria/metabolism , Environmental Monitoring/methods , Metals/metabolism , Oxazines/metabolism , Water Pollutants, Chemical/metabolism , Xanthenes/metabolism , Heterotrophic Processes , Markov Chains , Metals/analysis , Water Microbiology , Water Pollutants, Chemical/analysisABSTRACT
Solute transport displaying mass transfer behavior (i.e., tailing) occurs in many aquifers and soils. Spatial patterns of hydraulic conductivity may play a role because of both advection and diffusion through isolated low conductivity areas. We demonstrated such processes in laboratory experiments designed to visualize solute transport through a thin chamber (40 cm x 20 cm x 0.64 cm thick) packed with glass beads and containing circular emplacements of smaller glass beads with lower conductivity. The experiments used three different contrasts of conductivity between the large-bead matrix and the emplacements, targeting three different regimes of solute transport: low contrast, targeting macrodispersion; intermediate contrast, targeting advection-dominated mass transfer between the high-conductivity regions and the emplacements; and high contrast, targeting diffusion-dominated mass transfer. Use of a strong light source, a high-resolution CCD camera, and a colorimetric dye produced images with a spatial resolution of about 400 microm and a concentration range of approximately 2 orders of magnitude. These images confirm the existence of the three different regimes, and we observed tailing driven by both advection and diffusion. Outflow concentration measured by spectrophotometer achieved 3 orders of magnitude in concentration range and showed good agreement with known models in the case of dispersion and diffusive mass transfer, with estimated parameters close to a priori predictions. Existing models for diffusive mass transfer did notfitthe breakthrough curves from the intermediate-contrast chamber, but a model of slow advection through cylinders did. Thus, both breakthrough curves and chamber images confirm that different contrasts in small-scale K lead to different regimes of solute transport and thus require different models of upscaled solute transport.