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1.
Sci Total Environ ; 857(Pt 1): 159165, 2023 Jan 20.
Article in English | MEDLINE | ID: covidwho-2244343

ABSTRACT

Previous studies show that SARS-CoV-2 waste shedding rates vary by community and are influenced by multiple factors; however, differences in shedding rates across multiple variants have yet to be evaluated. The purpose of this work is to build on previous research that evaluated waste shedding rates for early SARS-CoV-2 and the Delta variant, and update population level waste shedding rates for the more-recent Omicron variant in six communities. Mean SARS-CoV-2 waste shedding rates were found to increase with the predominance of the Delta variant and subsequently decrease with Omicron infections. Interestingly, the Delta stage had the highest mean shedding rates and was associated with the most severe disease symptoms reported in other clinical studies, while Omicron, exhibiting reduced symptoms, had the lowest mean shedding rates. Additionally, shedding rates were most consistent across communities during the Omicron stage. This is the first paper to identify waste shedding rates specific to the Omicron variant and fills a knowledge gap critical to disease prevalence modeling.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Wastewater , COVID-19/epidemiology
2.
Viruses ; 14(12)2022 11 30.
Article in English | MEDLINE | ID: covidwho-2143724

ABSTRACT

Background: Wastewater-based epidemiology (WBE) has the potential to inform activities to contain infectious disease outbreaks in both the public and private sectors. Although WBE for SARS-CoV-2 has shown promise over short time intervals, no other groups have evaluated how a public-private partnership could influence disease spread through public health action over time. The aim of this study was to characterize and assess the application of WBE to inform public health response and contain COVID-19 infections in a food processing facility. Methods: Over the period November 2020-March 2022, wastewater in an Arizona food processing facility was monitored for the presence of SARS-CoV-2 using Real-Time Quantitative PCR. Upon positive detection, partners discussed public health intervention strategies, including infection control reinforcement, antigen testing, and vaccination. Results: SARS-CoV-2 RNA was detected on 18 of 205 days in which wastewater was sampled and analyzed (8.8%): seven during Wild-type predominance and 11 during Omicron-variant predominance. All detections triggered the reinforcement of infection control guidelines. In five of the 18 events, active antigen testing identified asymptomatic workers. Conclusions: These steps heightened awareness to refine infection control protocols and averted possible transmission events during periods where detection occurred. This public-private partnership has potentially decreased human illness and economic loss during the COVID-19 pandemic.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , COVID-19/prevention & control , SARS-CoV-2/genetics , Wastewater-Based Epidemiological Monitoring , Wastewater , RNA, Viral/genetics , Pandemics , Mexico , Disease Outbreaks/prevention & control
3.
Sci Total Environ ; 838(Pt 4): 156535, 2022 Sep 10.
Article in English | MEDLINE | ID: covidwho-2076705

ABSTRACT

Wastewater-based epidemiology (WBE) has been utilized as an early warning tool to anticipate disease outbreaks, especially during the COVID-19 pandemic. However, COVID-19 disease models built from wastewater-collected data have been limited by the complexities involved in estimating SARS-CoV-2 fecal shedding rates. In this study, wastewater from six municipalities in Arizona and Florida with distinct demographics were monitored for SARS-CoV-2 RNA between September 2020 and December 2021. Virus concentrations with corresponding clinical case counts were utilized to estimate community-wide fecal shedding rates that encompassed all infected individuals. Analyses suggest that average SARS-CoV-2 RNA fecal shedding rates typically occurred within a consistent range (7.53-9.29 log10 gc/g-feces); and yet, were unique to each community and influenced by population demographics. Age, ethnicity, and socio-economic factors may have influenced shedding rates. Interestingly, populations with median age between 30 and 39 had the greatest fecal shedding rates. Additionally, rates remained relatively constant throughout the pandemic provided conditions related to vaccination and variants were unchanged. Rates significantly increased in some communities when the Delta variant became predominant. Findings in this study suggest that community-specific shedding rates may be appropriate in model development relating wastewater virus concentrations to clinical case counts.


Subject(s)
COVID-19 , SARS-CoV-2 , Adult , COVID-19/epidemiology , Feces , Humans , Pandemics , RNA, Viral , Wastewater , Wastewater-Based Epidemiological Monitoring
4.
Sci Total Environ ; 801: 149794, 2021 Dec 20.
Article in English | MEDLINE | ID: covidwho-1364462

ABSTRACT

Wastewater-based epidemiology (WBE) was utilized to monitor SARS-CoV-2 RNA in sewage collected from manholes specific to individual student dormitories (dorms) at the University of Arizona in the fall semester of 2020, which led to successful identification and reduction of SARS-CoV-2 transmission events. Positive wastewater samples triggered clinical testing of residents within that dorm; thus, SARS-CoV-2 infected individuals were identified regardless of symptom expression. This current study examined clinical testing data to determine the abundance of asymptomatic versus symptomatic cases in these defined communities. Nasal and nasopharyngeal swab samples processed via antigen and PCR tests indicated that 79.2% of SARS-CoV-2 infections were asymptomatic, and only 20.8% of positive cases reported COVID-19 symptoms at the time of testing. Clinical data was paired with corresponding wastewater virus concentrations, which enabled calculation of viral shedding rates in feces per infected person. Mean shedding rates averaged from positive wastewater samples across all dorms were 7.30 ± 0.67 log10 genome copies per gram of feces (gc/g-feces) based on the N1 gene. Quantification of SARS-CoV-2 fecal shedding rates from infected individuals has been the critical missing component necessary for WBE models to measure and predict SARS-CoV-2 infection prevalence in communities. The findings from this study can be utilized to create models that can be used to inform public health prevention and response actions.


Subject(s)
COVID-19 , SARS-CoV-2 , Feces , Humans , RNA, Viral , Wastewater , Wastewater-Based Epidemiological Monitoring
5.
Int J Environ Res Public Health ; 18(9)2021 04 22.
Article in English | MEDLINE | ID: covidwho-1202406

ABSTRACT

Wastewater surveillance for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging approach to help identify the risk of a coronavirus disease (COVID-19) outbreak. This tool can contribute to public health surveillance at both community (wastewater treatment system) and institutional (e.g., colleges, prisons, and nursing homes) scales. This paper explores the successes, challenges, and lessons learned from initial wastewater surveillance efforts at colleges and university systems to inform future research, development and implementation. We present the experiences of 25 college and university systems in the United States that monitored campus wastewater for SARS-CoV-2 during the fall 2020 academic period. We describe the broad range of approaches, findings, resources, and impacts from these initial efforts. These institutions range in size, social and political geographies, and include both public and private institutions. Our analysis suggests that wastewater monitoring at colleges requires consideration of local information needs, sewage infrastructure, resources for sampling and analysis, college and community dynamics, approaches to interpretation and communication of results, and follow-up actions. Most colleges reported that a learning process of experimentation, evaluation, and adaptation was key to progress. This process requires ongoing collaboration among diverse stakeholders including decision-makers, researchers, faculty, facilities staff, students, and community members.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Public Health Surveillance , Universities , Wastewater
6.
Sci Total Environ ; 779: 146408, 2021 Jul 20.
Article in English | MEDLINE | ID: covidwho-1129189

ABSTRACT

Wastewater-based epidemiology has potential as an early-warning tool for determining the presence of COVID-19 in a community. The University of Arizona (UArizona) utilized WBE paired with clinical testing as a surveillance tool to monitor the UArizona community for SARS-CoV-2 in near real-time, as students re-entered campus in the fall. Positive detection of virus RNA in wastewater lead to selected clinical testing, identification, and isolation of three infected individuals (one symptomatic and two asymptomatic) that averted potential disease transmission. This case study demonstrated the value of WBE as a tool to efficiently utilize resources for COVID-19 prevention and response. Thus, WBE coupled with targeted clinical testing was further conducted on 13 dorms during the course of the Fall semester (Table 3). In total, 91 wastewater samples resulted in positive detection of SARS-CoV-2 RNA that successfully provided an early-warning for at least a single new reported case of infection (positive clinical test) among the residents living in the dorm. Overall, WBE proved to be an accurate diagnostic for new cases of COVID-19 with an 82.0% positive predictive value and an 88.9% negative predictive value. Increases in positive wastewater samples and clinical tests were noted following holiday-related activities. However, shelter-in-place policies proved to be effective in reducing the number of daily reported positive wastewater and clinical tests. This case study provides evidence for WBE paired with clinical testing and public health interventions to effectively contain potential outbreaks of COVID-19 in defined communities.


Subject(s)
COVID-19 , Wastewater-Based Epidemiological Monitoring , Humans , RNA, Viral , SARS-CoV-2 , Wastewater
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