Statistical Relationship Between Wastewater Data and Case Notifications for COVID-19 Surveillance in the United States, 2020-2023: A Bayesian Hierarchical Model (Preprint) DOI Creative Commons
Masahiko Haraguchi, Fayette Klaassen, Ted Cohen

и другие.

JMIR Public Health and Surveillance, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 1, 2024

During the COVID-19 pandemic, several US jurisdictions began to regularly report levels of SARS-CoV-2 in wastewater as a proxy for incidence. Despite promise this approach improving situational awareness, degree which surveillance data agree with other has varied, and better evidence is needed understand situations track closely traditional data. In study, we quantified statistical relationship between case-based multiple jurisdictions. We collated on RNA case reports from July 2020 March 2023 107 counties representing range terms geographic location, population size, urbanicity. For these counties, used Bayesian hierarchical regression modeling estimate reported cases, allowing variation across counties. compared different model structural approaches assessed how strength estimated relationships varied settings over time. Our analyses revealed strong positive cases majority locations, median correlation coefficient observed predicted 0.904 (IQR 0.823-0.943). total, 23/107 (21.5%) had coefficients below 0.8, 3/107 (2.8%) values 0.6. Across rate associated given level concentration declined study period. Counties greater size (P<.001) higher urbanicity stronger concordance cases. Measures fit, were robust sensitivity time period analysis sample fitting. close found be where routine are less reliable, may local incidence trends.

Язык: Английский

Research agenda for transmission prevention within the Veterans Health Administration, 2024–2028 DOI Creative Commons
Matthew Smith, Christopher J. Crnich, Curtis J. Donskey

и другие.

Infection Control and Hospital Epidemiology, Год журнала: 2024, Номер 45(8), С. 913 - 922

Опубликована: Апрель 11, 2024

An abstract is not available for this content. As you have access to content, full HTML content provided on page. A PDF of also in through the 'Save PDF' action button.

Язык: Английский

Процитировано

2

Multisite community-scale monitoring of respiratory and enteric viruses in the effluent of a nursing home and in the inlet of the local wastewater treatment plant DOI
Catherine Manoha,

Anne-Laure Dequiedt,

Lucie Théry

и другие.

Applied and Environmental Microbiology, Год журнала: 2024, Номер 90(11)

Опубликована: Окт. 10, 2024

ABSTRACT The aim of this study was to evaluate whether community-level monitoring respiratory and enteric viruses in wastewater can provide a comprehensive picture local virus circulation. Wastewater samples were collected weekly at the treatment plant (WWTP) inlet outlet nearby nursing home (NH) Burgundy, France, during winter period 2022/2023. We searched for pepper mild mottle as an indicator fecal content well main [severe acute syndrome coronavirus 2 (SARS-CoV-2), influenza, syncytial virus] (rotavirus, sapovirus, norovirus, astrovirus, adenovirus). Samples analyzed using real-time reverse transcription PCR-based methods. SARS-CoV-2 most frequently detected virus, with 66.7% positive from WWTP 28.6% NH. Peaks consistent chronological incidence infections recorded sentinel surveillance hospital databases. number lower NH than three viruses. Enteric detected, often sapovirus norovirus genogroup II, accounting both 77.8% 57.1% 37%, respectively, large circulation unexpected particular Combined simple optimized methods be valuable tool viral may serve suitable early warning system identifying outbreaks onset epidemics. These results encourage application wastewater-based (WBS) SARS-CoV2, sapovirus. IMPORTANCE WBS provides information on spread epidemic environment appropriate sensitive detection By PCR retirement (connected same collective sewer network), we aimed demonstrate that implementing combined key community sites allows effective occurrence (influenza, SARS-CoV-2) (norovirus, rotavirus, sapovirus) within given population. This analysis localized scale provided new two different sites. Implementing monitor or emergence infectious diseases is important means alerting authorities improving public health management. could participate actively humans, animals, environment.

Язык: Английский

Процитировано

2

Statistical relationship between wastewater data and case notifications for COVID-19 surveillance in the United States, 2020-2023: a Bayesian hierarchical model. DOI Creative Commons
Masahiko Haraguchi, Fayette Klaassen, Ted Cohen

и другие.

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Окт. 21, 2024

Abstract During the COVID-19 pandemic a number of jurisdictions in United States began to regularly report levels SARS-CoV-2 wastewater for use as proxy incidence. Despite promise this approach improving situational awareness, degree which viral track with other outcome data has varied, and better evidence is needed understand situations surveillance tracks closely traditional data. In study, we quantified relationship between case-based multiple jurisdictions. To do so, collated on RNA case reports from July 2020 March 2023, employed Bayesian hierarchical regression modeling estimate statistical reported cases, allowing variation across counties. We compared different model structural approaches assessed how strength estimated relationships varied settings over time. These analyses revealed strong positive cases majority locations, median correlation coefficient observed predicted 0.904 (interquartile range 0.823 – 0.943). Across rate associated given level concentration declined study period. Counties higher population size urbanicity had stronger concordance cases. Ideally, decision-making should be based an understanding their local historical performance.

Язык: Английский

Процитировано

0

Statistical Relationship Between Wastewater Data and Case Notifications for COVID-19 Surveillance in the United States, 2020-2023: A Bayesian Hierarchical Model (Preprint) DOI Creative Commons
Masahiko Haraguchi, Fayette Klaassen, Ted Cohen

и другие.

JMIR Public Health and Surveillance, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 1, 2024

During the COVID-19 pandemic, several US jurisdictions began to regularly report levels of SARS-CoV-2 in wastewater as a proxy for incidence. Despite promise this approach improving situational awareness, degree which surveillance data agree with other has varied, and better evidence is needed understand situations track closely traditional data. In study, we quantified statistical relationship between case-based multiple jurisdictions. We collated on RNA case reports from July 2020 March 2023 107 counties representing range terms geographic location, population size, urbanicity. For these counties, used Bayesian hierarchical regression modeling estimate reported cases, allowing variation across counties. compared different model structural approaches assessed how strength estimated relationships varied settings over time. Our analyses revealed strong positive cases majority locations, median correlation coefficient observed predicted 0.904 (IQR 0.823-0.943). total, 23/107 (21.5%) had coefficients below 0.8, 3/107 (2.8%) values 0.6. Across rate associated given level concentration declined study period. Counties greater size (P<.001) higher urbanicity stronger concordance cases. Measures fit, were robust sensitivity time period analysis sample fitting. close found be where routine are less reliable, may local incidence trends.

Язык: Английский

Процитировано

0