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This paper is in the following e-collection/theme issue:

Surveillance Systems (521) Public (e)Health, Digital Epidemiology and Public Health Informatics (1113) Early Results from COVID-19 Studies (371) Outbreak and Pandemic Preparedness and Management (1849) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1546) Innovative Methods in Public Health and Surveillance (404) Statistical Methods for Surveillance and Population Health (196) Environmental Health (139)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/68213, first published .
Statistical Relationship Between Wastewater Data and Case Notifications for COVID-19 Surveillance in the United States From 2020 to 2023: Bayesian Hierarchical Modeling Approach

Statistical Relationship Between Wastewater Data and Case Notifications for COVID-19 Surveillance in the United States From 2020 to 2023: Bayesian Hierarchical Modeling Approach

Statistical Relationship Between Wastewater Data and Case Notifications for COVID-19 Surveillance in the United States From 2020 to 2023: Bayesian Hierarchical Modeling Approach

Authors of this article:

Masahiko Haraguchi1 Author Orcid Image ;   Fayette Klaassen1 Author Orcid Image ;   Ted Cohen2 Author Orcid Image ;   Joshua A Salomon3 Author Orcid Image ;   Nicolas A Menzies1 Author Orcid Image
Article Authors Cited by (5) Tweetations Metrics

Journals

  1. Wang W, Li R, Chen S, Chen L, Jiang Y, Xiang J, Wu J, Li J, Chen Z, Wu C. Wastewater-Based Surveillance of SARS-CoV-2 and Modeling of COVID-19 Infection Trends. Tropical Medicine and Infectious Disease 2025;10(9):264 View
  2. Hamza I, Mao K, Gao C, Hamza H, Zhang H. Elements of Viral Outbreak Preparedness: Lessons, Strategies, and Future Directions. Viruses 2025;18(1):50 View
  3. Jeon M, Kim Y. The Role of Fear, Hope, Message Fatigue, and Message Shocking Value in Promoting the Public’s Understanding and Support Toward COVID-19 Wastewater Monitoring: Experimental Study. JMIR Formative Research 2026;10:e83060 View
  4. Tang X, Memedi M, Sun S, Hiyoshi A, Montgomery S, Cao Y. Machine learning-based 4-domain framework for evaluating COVID-19 policy responses: a counterfactual analysis of 27 European OECD countries. International Journal of Infectious Diseases 2026;166:108528 View
  5. Phillips V, Saber L, Kennedy S, Akiyama M, Spaulding A. Budget impact of wastewater surveillance for COVID-19 in a large urban jail: an activity-based cost analysis. Frontiers in Public Health 2026;14 View