Phylogeography as a Proxy for Population Connectivity for Spatial Modeling of Foot-and-Mouth Disease Outbreaks in Vietnam

Umanga Gunasekara, Miranda R. Bertram, Nguyen Van Long, Phan Quang Minh, Vo Dinh Chuong, Andres Perez, Jonathan Arzt, Kimberly VanderWaal

Research output: Contribution to journalArticlepeer-review

Abstract

Bayesian space–time regression models are helpful tools to describe and predict the distribution of infectious disease outbreaks and to delineate high-risk areas for disease control. In these models, structured and unstructured spatial and temporal effects account for various forms of non-independence amongst case counts across spatial units. Structured spatial effects capture correlations in case counts amongst neighboring provinces arising from shared risk factors or population connectivity. For highly mobile populations, spatial adjacency is an imperfect measure of connectivity due to long-distance movement, but we often lack data on host movements. Phylogeographic models inferring routes of viral dissemination across a region could serve as a proxy for patterns of population connectivity. The objective of this study was to investigate whether the effects of population connectivity in space–time regressions of case counts were better captured by spatial adjacency or by inferences from phylogeographic analyses. To compare these two approaches, we used foot-and-mouth disease virus (FMDV) outbreak data from across Vietnam as an example. We identified that accounting for virus movement through phylogeographic analysis serves as a better proxy for population connectivity than spatial adjacency in spatial–temporal risk models. This approach may contribute to design surveillance activities in countries lacking movement data.

Original languageEnglish (US)
Article number388
JournalViruses
Volume15
Issue number2
DOIs
StatePublished - Feb 2023

Bibliographical note

Funding Information:
This research was funded in part by the United States Department of Agriculture, Agricultural Research Service (ARS-CRIS Project 1940-32000-061-00D). Additional funding was provided by the Cooperative Biological Engagement Program of the U.S. Department of Defense, Defense Threat Reduction Agency (CBEP/DTRA/DOD).

Funding Information:
Support for this work was provided by the Department of Animal Health (DAH) Vietnam. The authors are thankful to the DAH, Vietnam Government, for providing serum samples.

Publisher Copyright:
© 2023 by the authors.

Keywords

  • Bayesian space-time models
  • FMD
  • foot-and-mouth disease virus
  • host movement
  • INLA
  • mobility
  • outbreak risk
  • phylodynamics
  • Vietnam

PubMed: MeSH publication types

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

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