Demographic processes drive increases in wildlife disease following population reduction.
Population reduction is often used as a control strategy when managing infectious diseases in wildlife populations in order to reduce host density below a critical threshold. However, population reduction can disrupt existing social and demographic structures leading to changes in observed host behaviour that may result in enhanced disease transmission. Such effects have been observed in several disease systems, notably badgers and bovine tuberculosis. Here we characterise the fundamental properties of disease systems for which such effects undermine the disease control benefits of population reduction. By quantifying the size of response to population reduction in terms of enhanced transmission within a generic non-spatial model, the properties of disease systems in which such effects reduce or even reverse the disease control benefits of population reduction are identified. If population reduction is not sufficiently severe, then enhanced transmission can lead to the counter intuitive perturbation effect, whereby disease levels increase or persist where they would otherwise die out. Perturbation effects are largest for systems with low levels of disease, e.g. low levels of endemicity or emerging disease. Analysis of a stochastic spatial meta-population model of demography and disease dynamics leads to qualitatively similar conclusions. Moreover, enhanced transmission itself is found to arise as an emergent property of density dependent dispersal in such systems. This spatial analysis also shows that, below some threshold, population reduction can rapidly increase the area affected by disease, potentially expanding risks to sympatric species. Our results suggest that the impact of population reduction on social and demographic structures is likely to undermine disease control in many systems, and in severe cases leads to the perturbation effect. Social and demographic mechanisms that enhance transmission following population reduction should therefore be routinely considered when designing control programmes.
Disease Systems Team, SRUC, Edinburgh, United Kingdom; Biomathematics and Statistics Scotland, Edinburgh, United Kingdom; Environment Department, University of York, York, United Kingdom.
Jamie C
JC
Prentice
Biomathematics and Statistics Scotland, Edinburgh, United Kingdom.
Glenn
G
Marion
Environment Department, University of York, York, United Kingdom.
Piran C L
PC
White
Disease Systems Team, SRUC, Edinburgh, United Kingdom.
Ross S
RS
Davidson
Disease Systems Team, SRUC, Edinburgh, United Kingdom.
Michael R
MR
Hutchings
D000820:Animal Diseases / Q000453:epidemiology*; D000818:Animals; D000835:Animals, Wild; D002417:Cattle; D015233:Models, Statistical; D011157:Population Dynamics; D062206:Spatial Analysis; D013269:Stochastic Processes; D014380:Tuberculosis, Bovine / Q000401:mortality / Q000635:transmission