Mapping the basic reproduction number (R₀) for vector-borne diseases: a case study on bluetongue virus

Epidemics. 2009 Sep;1(3):153-61. doi: 10.1016/j.epidem.2009.05.004. Epub 2009 Jun 6.

Abstract

Geographical maps indicating the value of the basic reproduction number, R₀, can be used to identify areas of higher risk for an outbreak after an introduction. We develop a methodology to create R₀ maps for vector-borne diseases, using bluetongue virus as a case study. This method provides a tool for gauging the extent of environmental effects on disease emergence. The method involves integrating vector-abundance data with statistical approaches to predict abundance from satellite imagery and with the biologically mechanistic modelling that underlies R₀. We illustrate the method with three applications for bluetongue virus in the Netherlands: 1) a simple R₀ map for the situation in September 2006, 2) species-specific R₀ maps based on satellite-data derived predictions, and 3) monthly R₀ maps throughout the year. These applications ought to be considered as a proof-of-principle and illustrations of the methods described, rather than as ready-to-use risk maps. Altogether, this is a first step towards an integrative method to predict risk of establishment of diseases based on mathematical modelling combined with a geographic information system that may comprise climatic variables, landscape features, land use, and other relevant factors determining the risk of establishment for bluetongue as well as of other emerging vector-borne diseases.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Bluetongue / epidemiology*
  • Bluetongue / transmission
  • Bluetongue virus / growth & development
  • Bluetongue virus / physiology*
  • Cattle
  • Cattle Diseases / epidemiology*
  • Cattle Diseases / transmission
  • Cattle Diseases / virology
  • Ceratopogonidae / virology*
  • Ecosystem
  • Fourier Analysis
  • Geographic Information Systems
  • Insect Vectors / virology*
  • Maps as Topic
  • Netherlands / epidemiology
  • Risk Factors
  • Seasons
  • Sheep