Abstract
Geographical maps indicating the value of the basic reproduction number, R 0 , can be used to identify areas of higher risk for an outbreak after an introduction. We develop a methodology to create R 0 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 R 0 . We illustrate the method with three applications for bluetongue virus in the Netherlands: 1) a simple R 0 map for the situation in September 2006, 2) species-specific R 0 maps based on satellite-data derived predictions, and 3) monthly R 0 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.
| Original language | English |
|---|---|
| Pages (from-to) | 153-161 |
| Number of pages | 9 |
| Journal | Epidemics |
| Volume | 1 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2009 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 13 Climate Action
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SDG 15 Life on Land
Keywords
- Emerging diseases
- Infectious diseases
- Epidemiology
- Risk maps
- Climate change
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