Phylogeographic analysis of foot-and-mouth disease virus serotype O dispersal and associated drivers in East Africa

Anna Munsey, Frank Norbert Mwiine, Sylvester Ochwo, Lauro Velazquez-Salinas, Zaheer Ahmed, Francois Maree, Luis L. Rodriguez, Elizabeth Rieder, Andres Perez, Simon Dellicour, Kimberly VanderWaal

Research output: Contribution to journalArticlepeer-review

Abstract

The continued endemicity of foot and mouth disease virus (FMDV) in East Africa has significant implications for livestock production and poverty reduction, yet its complex epidemiology in endemic settings remains poorly understood. Identifying FMDV dispersal routes and drivers of transmission is key to improved control strategies. Environmental heterogeneity and anthropogenic drivers (e.g., demand for animal products) can impact viral spread by influencing host movements. Here, we utilized FMDV serotype O VP1 genetic sequences and corresponding spatiotemporal data in order to (i) infer the recent dispersal history, and (II) investigate the impact of external factors (cattle density, human population density, proximity to livestock markets, and drought) on dispersal velocity, location, and direction of FMDV serotype O in East Africa. We identified statistical evidence of long-distance transmission events, and we found that FMDV serotype O tends to remain circulating in areas of high cattle density, high human population density, and in close proximity to livestock markets. The latter two findings highlight the influence of anthropogenic factors on FMDV serotype O spread in this region. These findings contribute to the understanding of FMDV epidemiology in East Africa and can help guide improved control measures.

Original languageEnglish (US)
Pages (from-to)3815-3825
Number of pages11
JournalMolecular ecology
Volume30
Issue number15
DOIs
StatePublished - Aug 2021

Bibliographical note

Funding Information:
Cooperative Biological Engagement Program of the United States Department of Defense, Defense Threat Reduction Agency [agreement #8802]; Agricultural Research Service, United States Department of Agriculture [CRIS project #1940-32000-061-00D]; AM was supported by the National Institute of Food and Agriculture, United States Department of Agriculture [grant #2016-38420-25288]. SD is supported by the Fonds National de la Recherche Scientifique (FNRS, Belgium) The authors thank Shinichiro Maruyama for assistance with TreeTrimmer and Ehud (Udi) Elnekave for assistance with the beast analysis.

Funding Information:
Cooperative Biological Engagement Program of the United States Department of Defense, Defense Threat Reduction Agency [agreement #8802]; Agricultural Research Service, United States Department of Agriculture [CRIS project #1940‐32000‐061‐00D]; AM was supported by the National Institute of Food and Agriculture, United States Department of Agriculture [grant #2016‐38420‐25288]. SD is supported by the Fonds National de la Recherche Scientifique (FNRS, Belgium)

Publisher Copyright:
© 2021 John Wiley & Sons Ltd

Keywords

  • Bayesian inference
  • disease ecology
  • environmental factors
  • landscape phylogeography
  • molecular epidemiology
  • spatial analysis

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

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