Automatic case cluster detection using hospital electronic health record data DOI Creative Commons
Michael DeWitt, Thomas F. Wierzba

Biology Methods and Protocols, Journal Year: 2023, Volume and Issue: 8(1)

Published: Jan. 1, 2023

Case detection through contact tracing is a key intervention during an infectious disease outbreak. However, intensive process where given tracer must locate not only confirmed cases but also identify and interview known contacts. Often these data are manually recorded. During emerging outbreaks, the number of contacts could expand rapidly beyond this, when focused on individual transmission chains, larger patterns may be identified. Understanding if particular can clustered linked to common source help prioritize effects understand underlying risk factors for large spreading events. Electronic health records systems used by vast majority private healthcare across USA, providing potential way automatically detect outbreaks connect already collected data. In this analysis, we propose algorithm case clusters within community outbreak using Bayesian probabilistic linking explore how approach supplement responses; especially human resources limited.

Language: Английский

Wastewater and clinical surveillance of respiratory viral pathogens on a university campus DOI Creative Commons
Steven C. Holland,

Matthew F. Smith,

LaRinda A. Holland

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 948, P. 174981 - 174981

Published: July 23, 2024

Areas of dense population congregation are prone to experience respiratory virus outbreaks. We monitored wastewater and clinic patients for the presence viruses on a large, public university campus. Campus sewer systems were in 16 locations using next generation sequencing over 22 weeks 2023. During this period, we detected surge human adenovirus (HAdV) levels wastewater. Hence, initiated clinical surveillance at an on-campus from presenting with acute infection. From whole genome 123 throat and/or nasal swabs collected, identified outbreak HAdV, specifically HAdV-E4 HAdV-B7 genotypes overlapping time. The temporal dynamics proportions HAdV found corroborated infections. tracked specific single nucleotide polymorphisms (SNPs) sequences showed that they arose signals concordant time presentation, linking community transmission outbreak. This study demonstrates how wastewater-based epidemiology can be integrated ambulatory healthcare settings monitor areas outbreaks provide health guidance.

Language: Английский

Citations

0

Development of a wastewater based infectious disease surveillance research system in South Korea DOI Creative Commons
Yun-Tae Kim, Kyung Won Lee, Hyukmin Lee

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Oct. 19, 2024

Abstract Wastewater-based epidemiology has been used in pathogen surveillance for microorganisms at the community level. This study was conducted to determine occurrence and trends of infectious pathogens sewage from Yongin city relationships between these incidence diseases community. From December 2022 November 2023, we collected inflow water six wastewater treatment plants twice a month. The analyzed included 15 respiratory viruses, 7 pneumonia-causing bacteria, 19 acute diarrhea-causing pathogens, SARS-CoV-2, Zika virus, hepatitis A poliovirus, Mpox, measles. They were detected through real-time PCR conventional PCR. concentrations 9 among them additionally using quantitative real time correlation confirmed statistical analysis with rate detection reported by Korea Disease Control Prevention Agency. Influenza human adenovirus, rhinovirus moderately correlated (rho values 0.45 0.58). Campylobacter spp. sapovirus strong 0.62, 0.63). Enteropathogenic E. coli , coronavirus, norovirus GII very 0.86 0.92). We able identify prevalence viral infections, pneumonia, wastewater-based data. will be helpful establishing system future present sewage.

Language: Английский

Citations

0

Unveiling the silent information of wastewater-based epidemiology of SARS-CoV-2 at community and sanitary zone levels: experience in Córdoba City, Argentina DOI Creative Commons
Gisela Masachessi, Gonzalo Castro,

María de los Ángeles Marinzalda

et al.

Journal of Water and Health, Journal Year: 2024, Volume and Issue: 22(11), P. 2171 - 2183

Published: Oct. 18, 2024

ABSTRACT The emergence of COVID-19 in 2020 significantly enhanced the application wastewater monitoring for detecting SARS-CoV-2 circulation within communities. From October 2021 to 2022, we collected 406 samples weekly from Córdoba Central Pipeline Network (BG-WWTP) and six specific sewer manholes sanitary zones (SZs). Following WHO guidelines, processed detected RNA variants using real-time PCR. Monitoring at SZ level allowed development a viral activity flow map, pinpointing key areas tracking its temporal spread variant evolution. Our findings demonstrate that wastewater-based surveillance acts as sensitive indicator activity, imminent increases cases before they become evident clinical data. This study highlights effectiveness targeted both municipal levels identifying hotspots assessing community-wide circulation. Importantly, data shows environmental studies provide valuable insights into virus presence, independent case records, offer robust tool adapting future public health challenges.

Language: Английский

Citations

0

Environmental surface monitoring as a noninvasive method for SARS-CoV-2 surveillance in community settings: Lessons from a university campus study DOI
Sobur Ali, Eleonora Cella, Catherine Johnston

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 912, P. 169456 - 169456

Published: Dec. 19, 2023

Language: Английский

Citations

1

Automatic case cluster detection using hospital electronic health record data DOI Creative Commons
Michael DeWitt, Thomas F. Wierzba

Biology Methods and Protocols, Journal Year: 2023, Volume and Issue: 8(1)

Published: Jan. 1, 2023

Case detection through contact tracing is a key intervention during an infectious disease outbreak. However, intensive process where given tracer must locate not only confirmed cases but also identify and interview known contacts. Often these data are manually recorded. During emerging outbreaks, the number of contacts could expand rapidly beyond this, when focused on individual transmission chains, larger patterns may be identified. Understanding if particular can clustered linked to common source help prioritize effects understand underlying risk factors for large spreading events. Electronic health records systems used by vast majority private healthcare across USA, providing potential way automatically detect outbreaks connect already collected data. In this analysis, we propose algorithm case clusters within community outbreak using Bayesian probabilistic linking explore how approach supplement responses; especially human resources limited.

Language: Английский

Citations

0