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Modeling habitat suitability for occurrence of highly pathogenic avian influenza virus H5N1 in domestic poultry in Asia: A spatial multicriteria decision analysis approach

  • Kim B. Stevens*
  • , Marius Gilbert
  • , Dirk U. Pfeiffer
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Risk maps are one of several sources used to inform risk-based disease surveillance and control systems, but their production can be hampered by lack of access to suitable disease data. In such situations, knowledge-driven spatial modeling methods are an alternative to data-driven approaches. This study used multicriteria decision analysis (MCDA) to identify areas in Asia suitable for the occurrence of highly pathogenic avian influenza virus (HPAIV) H5N1 in domestic poultry. Areas most suitable for H5N1 occurrence included Bangladesh, the southern tip and eastern coast of Vietnam, parts of north-central Thailand and large parts of eastern China. The predictive accuracy of the final model, as determined by the area under the receiver operating characteristic curve (ROC AUC), was 0.670 (95% CI 0.667-0.673) suggesting that, in data-scarce environments, MCDA provides a reasonable alternative to the data-driven approaches usually used to inform risk-based disease surveillance and control strategies. © 2012.
Original languageEnglish
Pages (from-to)1-14
JournalSpatial and Spatio-temporal Epidemiology
Volume4
Issue number1
DOIs
Publication statusPublished - Mar 2013
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Keywords

  • Emerging infectious diseases
  • Influenza in birds
  • Knowledge-driven spatial modeling
  • Model validation
  • Poultry diseases
  • Risk factors

Policy Impact

  • Cited in Policy Documents

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