Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland

Sen Li*, Lucy Gilbert, Paula A. Harrison, Mark D A Rounsevell

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Lyme disease is the most prevalent vector-borne disease in the temperate Northern Hemisphere. The abundance of infected nymphal ticks is commonly used as a Lyme disease risk indicator. Temperature can influence the dynamics of disease by shaping the activity and development of ticks and, hence, altering the contact pattern and pathogen transmission between ticks and their host animals. A mechanistic, agent-based model was developed to study the temperature-driven seasonality of Ixodes ricinus ticks and transmission of Borrelia burgdorferi sensu lato across mainland Scotland. Based on 12-year averaged temperature surfaces, our model predicted that Lyme disease risk currently peaks in autumn, approximately sixweeks after the temperature peak. The risk was predicted to decrease with increasing altitude. Increases in temperaturewere predicted to prolong the duration of the tick questing season and expand the risk area to higher altitudinal and latitudinal regions. These predicted impacts on tick population ecology may be expected to lead to greater tick-host contacts under climate warming and, hence, greater risks of pathogen transmission. The model is useful in improving understanding of the spatial determinants and system mechanisms of Lyme disease pathogen transmission and its sensitivity to temperature changes.

Original languageEnglish
Article number20160140
JournalJournal of the Royal Society, Interface
Volume13
Issue number116
DOIs
Publication statusPublished - 30 Mar 2016

Keywords

  • Agent-based model
  • Borrelia burgdorferi sensu lato
  • Climate warming
  • Environmental health hazard
  • Ixodes ricinus
  • Spatio-temporal dynamics

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