Monitoring SARS-CoV-2 RNA in wastewater from a shared septic system and sub-sewershed sites to expand COVID-19 disease surveillance.

Wastewater-based epidemiology has expanded as a tool for collecting COVID-19 surveillance data, but there is limited information on the feasibility of this form of surveillance within decentralized wastewater systems (e.g., septic systems). This study assessed SARS-CoV-2 RNA concentrations in wastewater samples from a septic system servicing a mobile home park (66 households) and from two pumping stations serving a similarly sized (71 households) and a larger (1,000 households) neighborhood within a nearby sewershed over 35 weeks in 2020. Also, raw wastewater from a hospital in the same sewershed was sampled. The mobile home park samples had the highest detection frequency (39/39 days) and mean concentration of SARS-CoV-2 RNA (2.7 × 107 gene copies/person/day for the N1) among the four sampling sites. N1 gene and N2 gene copies were highly correlated across mobile home park samples (Pearson's r = 0.93, p < 0.0001). In the larger neighborhood, new COVID-19 cases were reported every week during the sampling period; however, we detected SARS-CoV-2 RNA in 12% of the corresponding wastewater samples. The results of this study suggest that sampling from decentralized wastewater infrastructure can be used for continuous monitoring of SARS-CoV-2 infections.

Timing and Trends for Municipal Wastewater, Lab-Confirmed Case, and Syndromic Case Surveillance of COVID-19 in Raleigh, North Carolina.

Objectives. To compare 4 COVID-19 surveillance metrics in a major metropolitan area. Methods. We analyzed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater influent and primary solids in Raleigh, North Carolina, from April 10 through December 13, 2020. We compared wastewater results with lab-confirmed COVID-19 cases and syndromic COVID-like illness (CLI) cases to answer 3 questions: (1) Did they correlate? (2) What was the temporal alignment of the different surveillance systems? (3) Did periods of significant change (i.e., trends) align? Results. In the Raleigh sewershed, wastewater influent, wastewater primary solids, lab-confirmed cases, and CLI were strongly or moderately correlated. Trends in lab-confirmed cases and wastewater influent were observed earlier, followed by CLI and, lastly, wastewater primary solids. All 4 metrics showed sustained increases in COVID-19 in June, July, and November 2020 and sustained decreases in August and September 2020. Conclusions. In a major metropolitan area in 2020, the timing of and trends in municipal wastewater, lab-confirmed case, and syndromic case surveillance of COVID-19 were in general agreement. Public Health Implications. Our results provide evidence for investment in SARS-CoV-2 wastewater and CLI surveillance to complement information provided through lab-confirmed cases. (Am J Public Health. 2023;113(1):79-88. https://doi.org/10.2105/AJPH.2022.307108).

Factors Influencing Risk for COVID-19 Exposure Among Young Adults Aged 18-23 Years - Winnebago County, Wisconsin, March-July 2020.

On May 13, 2020, the Wisconsin Supreme Court declared the state's Safer at Home Emergency Order (https://evers.wi.gov/Documents/COVID19/EMO28-SaferAtHome.pdf) "unlawful, invalid, and unenforceable,"* thereby increasing opportunities for social and business interactions. By mid-June, Winnebago County,† Wisconsin experienced an increase in the number of infections with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), with the largest increase among persons aged 18-23 years (young adults) (1). This age group§ accounts for 12.5% of the population in the county. To identify factors that influence exposure to COVID-19 among young adults in Winnebago County, characteristics of COVID-19 cases and drivers of behaviors in this age group were examined. During March 1-July 18, 2020, 240 young adults received positive SARS-CoV-2 test results, accounting for 32% of all Winnebago County cases. In 30 key informant interviews, most interviewees reported exposure to misinformation, conflicting messages, or opposing views about the need for and effectiveness of masks. Thirteen young adults described social or peer pressure to not wear a mask and perceived severity of disease outcome for themselves as low but high for loved ones at risk. Having low perceived severity of disease outcome might partly explain why, when not in physical contact with loved ones at risk, young adults might attend social gatherings or not wear a mask (2). Exposure to misinformation and unclear messages has been identified as a driver of behavior during an outbreak (3,4), underscoring the importance of providing clear and consistent messages about the need for and effectiveness of masks. In addition, framing communication messages that amplify young adults' responsibility to protect others and target perceived social or peer pressure to not adhere to public health guidance might persuade young adults to adhere to public health guidelines that prevent the spread of COVID-19.

Development and performance of a machine learning-based tool that predicts influent flow to a WRF 72 h in advance and integrates with existing wet weather nutrient management protocols.

Influent flow to the 75 mgd Neuse River Resource Recovery Facility (NRRRF) was modeled using machine learning. The trained model can predict hourly flow 72 h in advance. This model was deployed in July 2020, and has been in operation over two and a half years. The model's mean absolute error in training was 2.6 mgd, and mean absolute error has ranged from 10 to 13 mgd in deployment for any point during the wet weather event when predicting 12 h in advance. As a result of this tool, plant staff have optimized the use of their 32 MG wet weather equalization basin, using it approximately 10 times and never exceeding its volume. PRACTITIONER POINTS: A machine learning model was developed to predict influent flow to a WRF 72 h in advance. Selecting the appropriate model, variables, and properly characterizing the system are important considerations in machine learning modeling. This model was developed using free open source software/code (Python) and deployed securely using an automated Cloud-based data pipeline. This tool has been in operation for over 30 months and continues to make accurate predictions. Machine learning combined with subject matter expertise can greatly benefit the water industry.

Effects of COVID-19 on Overdose Risk Behaviors Among People Who Inject Drugs in Wisconsin.

BACKGROUND: The United States is currently experiencing the worst epidemic of drug overdose in the country's history. We sought to understand whether changes in drug use behavior and access to prevention services during the COVID-19 pandemic may have contributed to increased drug overdose. METHODS: We recruited adults with a history of injection drug use to complete an online survey during March through June 2021 to assess whether overdose experiences, drug use behaviors, and access to prevention services changed due to the pandemic. RESULTS: Diminished social support during the pandemic was correlated with reporting disrupted access to harm reduction services (P = 0.006) and experiencing an overdose (P = 0.005). Disrupted access to harm reduction services also was correlated with being female (P = 0.03) and reporting feeling pressure to share drugs or equipment (P = 0.01), worrying about withdrawal (P = 0.03), and changes to how and where individuals got their drugs, drug price and availability, with whom and where drugs were used, and the quantity or properties of drugs purchased (all P < 0.01). DISCUSSION: The cumulative impact of COVID-19-related disruptions may have resulted in heightened risk for overdose, as these findings suggest that, in many cases, experiencing one risk factor was suggestive of experiencing several risk factors.

Low diversity and microdiversity of comammox bacteria in wastewater systems suggest specific adaptations within the Ca. Nitrospira nitrosa cluster.

Studies have found Ca. Nitrospira nitrosa-like bacteria to be the principal or sole comammox bacteria in nitrogen removal systems for wastewater treatment. In contrast, multiple populations of strict ammonia and nitrite oxidizers co-exist in similar systems. This apparent lack of diversity is surprising and could impact the feasibility of leveraging comammox bacteria for nitrogen removal. We used full-length 16S rRNA gene sequencing and genome-resolved metagenomics to compare the species-level diversity of comammox bacteria with that of strict nitrifiers in full-scale wastewater treatment systems and assess whether this comparison is consistent or diverged at the strain-level. Full-length 16S rRNA gene sequencing indicated that Nitrosomonas-like bacteria exhibited higher species-level diversity in comparison with other nitrifying bacteria, while the strain-level diversity (also called microdiversity) of most Nitrospira-like bacteria were higher than Nitrosomonas-like bacteria with few exceptions (one Nitrospira lineage II population). Comammox bacterial metagenome assembled genomes (MAGs) were associated with Ca. Nitrospira nitrosa. The average amino acid identity between principal comammox bacterial MAGs (93% ± 3) across systems was significantly higher than that of the Nitrosomonas-like ammonia oxidizers (73% ± 8), the Nitrospira_A-like nitrite oxidizer (85% ± 4), and the Nitrospira_D-like nitrite oxidizer (83% ± 1). This demonstrated the low species-level diversity of comammox bacteria compared with strict nitrifiers and further suggests that the same comammox population was detected in all systems. Comammox bacteria (Nitrospira lineage II), Nitrosomonas and, Nitrospira_D (Nitrospira lineage II) MAGs were significantly less microdiverse than the Nitrospira_A (lineage I) MAGs. Interestingly, strain-resolved analysis also indicates that different nitrogen removal systems harbor different comammox bacterial strains within the Ca. Nitrospira nitrosa cluster. These results suggest that comammox bacteria associated with Ca. Nitrospira nitrosa have low species- and strain-level diversity in nitrogen removal systems and may thus harbor specific adaptations to the wastewater ecosystem.

Voice and Lifestyle Behaviors of Student Actors: Impact of History Gathering Method on Self-Reported Data.

OBJECTIVES: This study described voice use and lifestyle information about student actors and assessed whether different information is reported at study intake compared to data extracted from a 3-week voice Log. METHODS: Twenty-five student actors estimated 14 voice and life style parameters at the start of the study. These included daily speaking time, performance time, vocal warm-up, and cool-down time; intake of water, caffeine, and alcohol; perceived voice effort (speaking and performance), among other items. The same parameters were tracked by the actor for 21 consecutive days. Nonparametric statistical comparisons of the estimates at intake to the median estimate from 21 days were applied. RESULTS: Student actors reported frequent yelling (48%), frustration, anxiety, and depression about their voice (52%, 48%, and 16%), issues with breath support (56%), vocal fatigue (36%), and mild-moderate effort in the speaking (24%) and performance voice (70%). Estimates at study intake statistically overestimated daily speaking, performance, and vocal warm-up time compared to the 3-week Log. Intake reporting underestimated perceived effort in the speaking voice. Intake reporting of vocal fatigue and voice quality did not closely correspond to the Log data. CONCLUSION: Student actors reported a number of voice use and lifestyle behaviors that may increase their risk for voice problems. Additionally, the method of soliciting the history altered the information reported by the students for several parameters. The findings highlight the need to develop history gathering or other methods that optimize accuracy and reliability of the information sought.

Long solids retention times and attached growth phase favor prevalence of comammox bacteria in nitrogen removal systems.

The discovery of the complete ammonia oxidizing (comammox) bacteria overturns the traditional two-organism nitrification paradigm which largely underpins the design and operation of nitrogen removal during wastewater treatment. Quantifying the abundance, diversity, and activity of comammox bacteria in wastewater treatment systems is important for ensuring a clear understanding of the nitrogen biotransformations responsible for ammonia removal. To this end, we conducted a yearlong survey of 14 full-scale nitrogen removal systems including mainstream conventional and simultaneous nitrification-denitrification and side-stream partial nitrification-anammox systems with varying process configurations. Metagenomics and genome-resolved metagenomics identified comammox bacteria in mainstream conventional and simultaneous nitrification-denitrification systems, with no evidence for their presence in side-stream partial nitrification-anammox systems. Further, comammox bacterial diversity was restricted to clade A and these clade A comammox bacteria were detected in systems with long solids retention times (>10 days) and/or in the attached growth phase. Using a newly designed qPCR assay targeting the amoB gene of clade A comammox bacteria in combination with quantitation of other canonical nitrifiers, we show that long solids retention time is the key process parameter associated with the prevalence and abundance of comammox bacteria. The increase in comammox bacterial abundance was not associated with concomitant decrease in the abundance of canonical nitrifiers; however, systems with comammox bacteria showed significantly better and temporally stable ammonia removal compared to systems where they were not detected. Finally, in contrast to recent studies, we do not find any significant association of comammox bacterial prevalence and abundance with dissolved oxygen concentrations in this study.

Healthcare Quality Improvement Requires Many Approaches.

It is a pleasure to respond to the commentaries and we thank the authors for the thought, time and effort they so obviously put into their writing. We are excited that documenting our experience has resulted in such a wide range of opinion.