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

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 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.

Language: Английский

Online dashboards for SARS-CoV-2 wastewater-based epidemiology DOI
Daniele Focosi, Pietro Giorgio Spezia, Fabrizio Maggi

et al.

Future Microbiology, Journal Year: 2024, Volume and Issue: 19(9), P. 761 - 769

Published: May 23, 2024

Aim: Wastewater-based epidemiology (WBE) is increasingly used to monitor pandemics. In this manuscript, we review methods and limitations of WBE, as well their online dashboards. Materials & methods: Online dashboards were retrieved using PubMed search engines, annotated for timeliness, availability English version, details on SARS-CoV-2 sublineages, normalization by population PPMoV load, case/hospitalization count charts raw data export. Results: We 51 web portals, half them from Europe. Africa represented South only, only seven portals are available Asia. Conclusion: WBS provides near-real-time cost-effective monitoring analytes across space time in populations. However, tremendous heterogeneity still persists the WBE literature.

Language: Английский

Citations

2
Advancing Public Health Surveillance: Integrating Modeling and GIS in the Wastewater-Based Epidemiology of Viruses, a Narrative Review DOI Creative Commons
Diego F. Cuadros, Xi Chen, Jingjing Li

et al.

Pathogens, Journal Year: 2024, Volume and Issue: 13(8), P. 685 - 685

Published: Aug. 14, 2024

This review article will present a comprehensive examination of the use modeling, spatial analysis, and geographic information systems (GIS) in surveillance viruses wastewater. With advent global health challenges like COVID-19 pandemic, wastewater has emerged as crucial tool for early detection management viral outbreaks. explore application various modeling techniques that enable prediction understanding virus concentrations spread patterns systems. It highlights role analysis mapping distribution loads, providing insights into dynamics transmission within communities. The integration GIS be explored, emphasizing utility such visualizing data, enhancing sampling site selection, ensuring equitable monitoring across diverse populations. also discuss innovative combination with remote sensing data predictive offering multi-faceted approach to understand spread. Challenges quality, privacy concerns, necessity interdisciplinary collaboration addressed. concludes by underscoring transformative potential these analytical tools public health, advocating continued research innovation strengthen preparedness response strategies future threats. aims provide foundational researchers officials, fostering advancements field wastewater-based epidemiology.

Language: Английский

Citations

2
Repurposing Sewage and Toilet Systems: Environmental, Public Health, and Person‐Centered Healthcare Applications DOI Creative Commons
Defne Yigci,

Joseph Bonventre,

Aydogan Özcan

et al.

Global Challenges, Journal Year: 2024, Volume and Issue: 8(7)

Published: May 11, 2024

Abstract Global terrestrial water supplies are rapidly depleting due to the consequences of climate change. Water scarcity results in an inevitable compromise safe hygiene and sanitation practices, leading transmission water‐borne infectious diseases, preventable deaths over 800.000 people each year. Moreover, almost 500 million lack access toilets systems. Ecosystems estimated be contaminated by 6.2 tons nitrogenous products from human wastewater management practices. It is therefore imperative transform toilet sewage systems promote equitable sanitation, improve public health, conserve water, protect ecosystems. Here, integration emerging technologies networks repurpose reviewed. Potential applications these develop sustainable solutions environmental challenges, advance person‐centered healthcare discussed.

Language: Английский

Citations

0
A roadmap to account for reporting delays for public health situational awareness: a case study with COVID-19 and dengue in United States jurisdictions. DOI Creative Commons
Velma K. Lopez, Leonardo Soares Bastos, Cláudia Torres Codeço

et al.

Published: Nov. 13, 2024

Abstract Background Decision making in public health is limited by data availability where the most recent reports do not reflect actual trajectory of an epidemic. Nowcasting a modeling tool that can estimate eventual case counts accounting for reporting delays. While these tools have generated reliable predictions when designed specific use cases, several limitations exist scaling models to systems composed multiple distinct surveillance systems. We seek identify flexible application nowcasting address problems. Methods used previously developed Bayesian tool, which dynamically estimates delay probabilities up user-defined maximum using training window. tested automated approaches select and window, setting values at 90 th , 95 99 quantile distribution recently reported windows plus one week or multiplied 1.5 2.0. evaluated nowcasts 321 datasets reflecting COVID-19 cases dengue different United States jurisdictions. assessed prediction error precision via logarithmic scoring coverage metrics three weeks each nowcast. further assess why may fail compare from publicly available tools. Results Using dynamic window parameters resulted nowcast with less relative made static long historic periods. Nowcasts likely could be predicted priori width intervals permutation entropy epidemic trend. More complex significantly improve performance compared simple models. Conclusions framework. recommend parameter selection creating system suppress fail. This requires collaboration colleagues implement data-driven choices utility decision making.

Language: Английский

Citations

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

et al.

JMIR Public Health and Surveillance, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Language: Английский

Citations

0
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

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 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.

Language: Английский

Citations

0