Making Waves: Integrating Wastewater Surveillance with Dynamic Modeling to Track and Predict Viral Outbreaks

Details

• Personal Author:
  Brozak S ; Gitter A ; Hu T ; Ke R ; Kuang Y ; Mena KD ; Oghuan J ; Pell B ; Perelson AS ; Phan T ; Ribeiro RM ; Wu F
  More +
• Description:
  Wastewater surveillance has proved to be a valuable tool to track the COVID-19 pandemic. However, most studies using wastewater surveillance data revolve around establishing correlations and lead time relative to reported case data. In this perspective, we advocate for the integration of wastewater surveillance data with dynamic within-host and between-host models to better understand, monitor, and predict viral disease outbreaks. Dynamic models overcome emblematic difficulties of using wastewater surveillance data such as establishing the temporal viral shedding profile. Complementarily, wastewater surveillance data bypasses the issues of time lag and underreporting in clinical case report data, thus enhancing the utility and applicability of dynamic models. The integration of wastewater surveillance data with dynamic models can enhance real-time tracking and prevalence estimation, forecast viral transmission and intervention effectiveness, and most importantly, provide a mechanistic understanding of infectious disease dynamics and the driving factors. Dynamic modeling of wastewater surveillance data will advance the development of a predictive and responsive monitoring system to improve pandemic preparedness and population health. Description provided by NIOSH
• Subjects:
  • Communicable Diseases
  • Occupational Health
  • Public Health
  • Safety
  • Virus Diseases
• Keywords:
  • Water analysis
  • Surveillance
  • Viral diseases
  • Disease transmission
  • Public health
  • Infectious diseases
  • Author Keywords: Wastewater surveillance
  • Viral transmission
  • Within-host and between-host dynamics
  • Mechanistic model
  More +
• ISSN:
  0043-1354
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Arizona ; Michigan ; New Mexico ; OSHA Region 5 ; OSHA Region 6 ; OSHA Region 9 ; Texas
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  243
• NIOSHTIC Number:
  nn:20069789
• Citation:
  Water Res 2023 Sep; 243:120372
• Email:
  fuqing.wu@uth.tmc.edu
• Federal Fiscal Year:
  2023
• Performing Organization:
  University of Texas Health Science Center, Houston
• Peer Reviewed:
  True
• Start Date:
  20050701
• End Date:
  20250630
• Download URL:
  https://stacks.cdc.gov/view/cdc/208145/cdc_208145_DS1.pdf
• File Type:
  [PDF - 1.59 MB]
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:16ebbf441efa797627d60e1df0fa9dd5140de5d44d2fe65e4e549108f28e320c163d549cccd591866d0e5da4149685474348650b7911051abd2a5149c4254f72