, Volume 100, Issue 5, pp 395–405

Predicting ectotherm disease vector spread—benefits from multidisciplinary approaches and directions forward

Concepts & Synthesis

DOI: 10.1007/s00114-013-1039-0

Cite this article as:
Thomas, S.M. & Beierkuhnlein, C. Naturwissenschaften (2013) 100: 395. doi:10.1007/s00114-013-1039-0


The occurrence of ectotherm disease vectors outside of their previous distribution area and the emergence of vector-borne diseases can be increasingly observed at a global scale and are accompanied by a growing number of studies which investigate the vast range of determining factors and their causal links. Consequently, a broad span of scientific disciplines is involved in tackling these complex phenomena. First, we evaluate the citation behaviour of relevant scientific literature in order to clarify the question “do scientists consider results of other disciplines to extend their expertise?” We then highlight emerging tools and concepts useful for risk assessment. Correlative models (regression-based, machine-learning and profile techniques), mechanistic models (basic reproduction number R0) and methods of spatial regression, interaction and interpolation are described. We discuss further steps towards multidisciplinary approaches regarding new tools and emerging concepts to combine existing approaches such as Bayesian geostatistical modelling, mechanistic models which avoid the need for parameter fitting, joined correlative and mechanistic models, multi-criteria decision analysis and geographic profiling. We take the quality of both occurrence data for vector, host and disease cases, and data of the predictor variables into consideration as both determine the accuracy of risk area identification. Finally, we underline the importance of multidisciplinary research approaches. Even if the establishment of communication networks between scientific disciplines and the share of specific methods is time consuming, it promises new insights for the surveillance and control of vector-borne diseases worldwide.


Arthropod vectors Climate change Global change Species distribution model Zoonoses 

Supplementary material

114_2013_1039_MOESM1_ESM.pdf (79 kb)
ESM 1(PDF 79 kb)
114_2013_1039_MOESM2_ESM.pdf (57 kb)
ESM 2(PDF 56 kb)

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Stephanie Margarete Thomas
    • 1
  • Carl Beierkuhnlein
    • 1
  1. 1.Department of BiogeographyUniversity of BayreuthBayreuthGermany

Personalised recommendations