TY - JOUR
T1 - Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland
AU - Li, Sen
AU - Gilbert, Lucy
AU - Harrison, Paula A.
AU - Rounsevell, Mark D A
PY - 2016/3/30
Y1 - 2016/3/30
N2 - 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.
AB - 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.
KW - Agent-based model
KW - Borrelia burgdorferi sensu lato
KW - Climate warming
KW - Environmental health hazard
KW - Ixodes ricinus
KW - Spatio-temporal dynamics
UR - http://www.scopus.com/inward/record.url?scp=84962821284&partnerID=8YFLogxK
U2 - 10.1098/rsif.2016.0140
DO - 10.1098/rsif.2016.0140
M3 - Article
AN - SCOPUS:84962821284
SN - 1742-5689
VL - 13
JO - Journal of the Royal Society. Interface
JF - Journal of the Royal Society. Interface
IS - 116
M1 - 20160140
ER -