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

• Published in: Epidemics Vol. 1; no. 3; pp. 153 - 161
• Main Authors: Hartemink, N.A, Purse, B.V, Meiswinkel, R, Brown, H.E, de Koeijer, A, Elbers, A.R.W, Boender, G.-J, Rogers, D.J, Heesterbeek, J.A.P
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.09.2009
• Subjects: Animals; Bluetongue - epidemiology; Bluetongue - transmission; Bluetongue virus - growth & development; Bluetongue virus - physiology; Cattle; Cattle Diseases - epidemiology; Cattle Diseases - transmission; Cattle Diseases - virology; Ceratopogonidae - virology; Climate change; CVI - Divisie Virologie; CVI - Division Virology; Ecosystem; Emerging diseases; Epidemiology; Fourier Analysis; Geographic Information Systems; Infectious Disease; Infectious diseases; Insect Vectors - virology; Internal Medicine; Maps as Topic; Netherlands - epidemiology; Risk Factors; Risk maps; Seasons; Sheep; WIAS; Netherlands; Risk maps; Climate change; Infectious diseases; Emerging diseases; Epidemiology
• ISSN: 1755-4365; 1878-0067
• DOI: 10.1016/j.epidem.2009.05.004

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.