| Autor: |
Ogbunugafor CB; Department of Ecology and Evolutionary Biology, Yale University 06520.; Department of Ecology and Evolutionary Biology, Brown University 02912.; Center for Computational Molecular Biology, Brown University 02912., Miller-Dickson MD; Department of Ecology and Evolutionary Biology, Brown University 02912., Meszaros VA; Department of Ecology and Evolutionary Biology, Brown University 02912., Gomez LM; Department of Ecology and Evolutionary Biology, Yale University 06520.; Department of Ecology and Evolutionary Biology, Brown University 02912., Murillo AL; Department of Pediatrics, Warren Alpert Medical School at Brown University 02912.; Center for Statistical Sciences, Brown University School of Public Health 02903., Scarpino SV; Network Science Institute, Northeastern University 02115. |
| Jazyk: |
angličtina |
| Zdroj: |
MedRxiv : the preprint server for health sciences [medRxiv] 2020 Aug 01. Date of Electronic Publication: 2020 Aug 01. |
| DOI: |
10.1101/2020.05.04.20090092 |
| Abstrakt: |
Variation in free-living, microparasite survival can have a meaningful impact on the ecological dynamics of established and emerging infectious diseases. Nevertheless, resolving the importance of environmental transmission in the ecology of epidemics remains a persistent challenge, requires accurate measuring the free-living survival of pathogens across reservoirs of various kinds, and quantifying the extent to which interaction between hosts and reservoirs generates new infections. These questions are especially salient for emerging pathogens, where sparse and noisy data can obfuscate the relative contribution of different infection routes. In this study, we develop a mechanistic, mathematical model that permits both direct (host-to-host) and indirect (environmental) transmission and then fit this model to empirical data from 17 countries affected by an emerging virus (SARS-CoV-2). From an ecological perspective, our model highlights the potential for environmental transmission to drive complex, non-linear dynamics during infectious disease outbreaks. Summarizing, we propose that fitting such models with environmental transmission to real outbreak data from SARS-CoV-2 transmission highlights that variation in environmental transmission is an underappreciated aspect of the ecology of infectious disease, and an incomplete understanding of its role has consequences for public health interventions. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
|
