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Variation in microparasite free-living survival and indirect transmission can modulate the intensity of emerging outbreaks.
Ogbunugafor, C Brandon; Miller-Dickson, Miles D; Meszaros, Victor A; Gomez, Lourdes M; Murillo, Anarina L; Scarpino, Samuel V.
  • Ogbunugafor CB; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06511, USA. brandon.ogbunu@yale.edu.
  • Miller-Dickson MD; Department of Ecology and Evolutionary Biology, Brown University, Providence, 02912, USA. brandon.ogbunu@yale.edu.
  • Meszaros VA; Center for Computational Molecular Biology, Brown University, Providence, 02912, USA. brandon.ogbunu@yale.edu.
  • Gomez LM; Department of Ecology and Evolutionary Biology, Brown University, Providence, 02912, USA.
  • Murillo AL; Department of Ecology and Evolutionary Biology, Brown University, Providence, 02912, USA.
  • Scarpino SV; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06511, USA.
Sci Rep ; 10(1): 20786, 2020 11 27.
Article in English | MEDLINE | ID: covidwho-947546
ABSTRACT
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 indirect and environmental transmission in the ecology of epidemics remains a persistent challenge. It requires accurately 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, nonlinear dynamics during infectious disease outbreaks. Summarizing, we propose that fitting alternative models with indirect transmission to real outbreak data from SARS-CoV-2 can be useful, as it highlights that indirect mechanisms may play an underappreciated role in the dynamics of infectious diseases, with implications for public health.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Language: English Journal: Sci Rep Year: 2020 Document Type: Article Affiliation country: S41598-020-77048-4

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Language: English Journal: Sci Rep Year: 2020 Document Type: Article Affiliation country: S41598-020-77048-4