{"title":"Integrating agent-based disease, mobility and wastewater models for the study of the spread of communicable diseases.","authors":"Néstor DelaPaz-Ruíz, Ellen-Wien Augustijn, Mahdi Farnaghi, Sheheen A Abdulkareem, Raul Zurita Milla","doi":"10.4081/gh.2025.1326","DOIUrl":null,"url":null,"abstract":"<p><p>Wastewater-based epidemiology was utilized during the COVID-19 outbreak to monitor the circulation of SARS-CoV-2, the virus causing this disease. However, this approach is limited by the need for additional methods to accurately translate virus concentrations in wastewater to disease-positive human counts. Combined modelling of COVID-19 disease cases and the concentration of its causative virus, SARS-CoV-2, in wastewater will necessarily deepen our understanding. However, this requires addressing the technical differences between disease, population mobility and wastewater models. To that end, we developed an integrated Agent-Based Model (ABM) that facilitates analysis in space and time at various temporal resolutions, including disease spread, population mobility and wastewater production, while also being sufficiently generic for different types of infectious diseases or pathogens. The integrated model replicates the epidemic curve for COVID-19 and can estimate the daily infections at the household level, enabling the monitoring of the spatial patterns of infection intensity. Additionally, the model allows monitoring the estimated production of infected wastewater over time and spatially across the sewage and treatment plant. The model addresses differences between resolutions and can potentially support Early Warning Systems (EWS) for future pandemics.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geospatial Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4081/gh.2025.1326","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Wastewater-based epidemiology was utilized during the COVID-19 outbreak to monitor the circulation of SARS-CoV-2, the virus causing this disease. However, this approach is limited by the need for additional methods to accurately translate virus concentrations in wastewater to disease-positive human counts. Combined modelling of COVID-19 disease cases and the concentration of its causative virus, SARS-CoV-2, in wastewater will necessarily deepen our understanding. However, this requires addressing the technical differences between disease, population mobility and wastewater models. To that end, we developed an integrated Agent-Based Model (ABM) that facilitates analysis in space and time at various temporal resolutions, including disease spread, population mobility and wastewater production, while also being sufficiently generic for different types of infectious diseases or pathogens. The integrated model replicates the epidemic curve for COVID-19 and can estimate the daily infections at the household level, enabling the monitoring of the spatial patterns of infection intensity. Additionally, the model allows monitoring the estimated production of infected wastewater over time and spatially across the sewage and treatment plant. The model addresses differences between resolutions and can potentially support Early Warning Systems (EWS) for future pandemics.
期刊介绍:
The focus of the journal is on all aspects of the application of geographical information systems, remote sensing, global positioning systems, spatial statistics and other geospatial tools in human and veterinary health. The journal publishes two issues per year.