Ohio Coronavirus Wastewater Monitoring Network: Implementation of Statewide Monitoring for Protecting Public Health.

CONTEXT: Prior to the COVID-19 pandemic, wastewater influent monitoring for tracking disease burden in sewered communities was not performed in Ohio, and this field was only on the periphery of the state academic research community. PROGRAM: Because of the urgency of the pandemic and extensive state-level support for this new technology to detect levels of community infection to aid in public health response, the Ohio Water Resources Center established relationships and support of various stakeholders. This enabled Ohio to develop a statewide wastewater SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) monitoring network in 2 months starting in July 2020. IMPLEMENTATION: The current Ohio Coronavirus Wastewater Monitoring Network (OCWMN) monitors more than 70 unique locations twice per week, and publicly available data are updated weekly on the public dashboard. EVALUATION: This article describes the process and decisions that were made during network initiation, the network progression, and data applications, which can inform ongoing and future pandemic response and wastewater monitoring. DISCUSSION: Overall, the OCWMN established wastewater monitoring infrastructure and provided a useful tool for public health professionals responding to the pandemic.

Lessons learned from SARS-CoV-2 measurements in wastewater.

Standardized protocols for wastewater-based surveillance (WBS) for the RNA of SARS-CoV-2, the virus responsible for the current COVID-19 pandemic, are being developed and refined worldwide for early detection of disease outbreaks. We report here on lessons learned from establishing a WBS program for SARS-CoV-2 integrated with a human surveillance program for COVID-19. We have established WBS at three campuses of a university, including student residential dormitories and a hospital that treats COVID-19 patients. Lessons learned from this WBS program address the variability of water quality, new detection technologies, the range of detectable viral loads in wastewater, and the predictive value of integrating environmental and human surveillance data. Data from our WBS program indicated that water quality was statistically different between sewer sampling sites, with more variability observed in wastewater coming from individual buildings compared to clusters of buildings. A new detection technology was developed based upon the use of a novel polymerase called V2G. Detectable levels of SARS-CoV-2 in wastewater varied from 102 to 106 genomic copies (gc) per liter of raw wastewater (L). Integration of environmental and human surveillance data indicate that WBS detection of 100 gc/L of SARS-CoV-2 RNA in wastewater was associated with a positivity rate of 4% as detected by human surveillance in the wastewater catchment area, though confidence intervals were wide (ß ~ 8.99 ∗ ln(100); 95% CI = 0.90-17.08; p < 0.05). Our data also suggest that early detection of COVID-19 surges based on correlations between viral load in wastewater and human disease incidence could benefit by increasing the wastewater sample collection frequency from weekly to daily. Coupling simpler and faster detection technology with more frequent sampling has the potential to improve the predictive potential of using WBS of SARS-CoV-2 for early detection of the onset of COVID-19.

Common Ancestry Is a Poor Predictor of Competitive Traits in Freshwater Green Algae.

Phytoplankton species traits have been used to successfully predict the outcome of competition, but these traits are notoriously laborious to measure. If these traits display a phylogenetic signal, phylogenetic distance (PD) can be used as a proxy for trait variation. We provide the first investigation of the degree of phylogenetic signal in traits related to competition in freshwater green phytoplankton. We measured 17 traits related to competition and tested whether they displayed a phylogenetic signal across a molecular phylogeny of 59 species of green algae. We also assessed the fit of five models of trait evolution to trait variation across the phylogeny. There was no significant phylogenetic signal for 13 out of 17 ecological traits. For 7 traits, a non-phylogenetic model provided the best fit. For another 7 traits, a phylogenetic model was selected, but parameter values indicated that trait variation evolved recently, diminishing the importance of common ancestry. This study suggests that traits related to competition in freshwater green algae are not generally well-predicted by patterns of common ancestry. We discuss the mechanisms by which the link between phylogenetic distance and phenotypic differentiation may be broken.

Tectonic influences on ground water quality: insight from complementary methods.

A study using multiple techniques provided insight into tectonic influences on ground water systems; the results can help to understand ground water systems in the tectonically active western United States and other parts of the world. Ground water in the San Bernardino Valley (Arizona, United States and Sonora, Mexico) is the main source of water for domestic use, cattle ranching (the primary industry), and the preservation of threatened and endangered species. To improve the understanding of ground water occurrence, movement, and sustainability, an investigation was conducted using a number of complementary methods, including major ion geochemistry, isotope hydrology, analysis of gases dissolved in ground water, aquifer testing, geophysics, and an examination of surface and subsurface geology. By combining information from multiple lines of investigation, a more complete picture of the basin hydrogeology was assembled than would have been possible using fewer methods. The results show that the hydrogeology of the San Bernardino Valley is markedly different than that of its four neighboring basins in the United States. The differences include water quality, chemical evolution, storage, and residence time. The differences result from the locally unique geology of the San Bernardino Valley, which is due to the presence of a magmatically active accommodation zone (a zone separating two regions of normal faults with opposite dips). The geological differences and the resultant hydrological differences between the San Bernardino Valley and its neighboring basins may serve as a model for the distinctive nature of chemical evolution of ground water in other basins with locally distinct tectonic histories.