TY  - JOUR
A1  - Scherer, Cedric
A1  - Radchuk, Viktoriia
A1  - Staubach, Christoph
A1  - Mueller, Sophie
A1  - Blaum, Niels
A1  - Thulke, Hans-Hermann
A1  - Kramer-Schadt, Stephanie
T1  - Seasonal host life-history processes fuel disease dynamics at different spatial scales
JF  - Journal of animal ecology : a journal of the British Ecological Society
N2  - Understanding the drivers underlying disease dynamics is still a major challenge in disease ecology, especially in the case of long-term disease persistence. Even though there is a strong consensus that density-dependent factors play an important role for the spread of diseases, the main drivers are still discussed and, more importantly, might differ between invasion and persistence periods. Here, we analysed long-term outbreak data of classical swine fever, an important disease in both wild boar and livestock, prevalent in the wild boar population from 1993 to 2000 in Mecklenburg-Vorpommern, Germany. We report outbreak characteristics and results from generalized linear mixed models to reveal what factors affected infection risk on both the landscape and the individual level. Spatiotemporal outbreak dynamics showed an initial wave-like spread with high incidence during the invasion period followed by a drop of incidence and an increase in seroprevalence during the persistence period. Velocity of spread increased with time during the first year of outbreak and decreased linearly afterwards, being on average 7.6 km per quarter. Landscape- and individual-level analyses of infection risk indicate contrasting seasonal patterns. During the persistence period, infection risk on the landscape level was highest during autumn and winter seasons, probably related to spatial behaviour such as increased long-distance movements and contacts induced by rutting and escaping movements. In contrast, individual-level infection risk peaked in spring, probably related to the concurrent birth season leading to higher densities, and was significantly higher in piglets than in reproductive animals. Our findings highlight that it is important to investigate both individual- and landscape-level patterns of infection risk to understand long-term persistence of wildlife diseases and to guide respective management actions. Furthermore, we highlight that exploring different temporal aggregation of the data helps to reveal important seasonal patterns, which might be masked otherwise.
KW  - classical swine fever
KW  - disease invasion
KW  - infection risk
KW  - pathogen persistence
KW  - seasonality
KW  - Sus scrofa
KW  - wild boar
KW  - wildlife disease
Y1  - 2019
U6  - https://doi.org/10.1111/1365-2656.13070
SN  - 0021-8790
SN  - 1365-2656
VL  - 88
IS  - 11
SP  - 1812
EP  - 1824
PB  - Wiley
CY  - Hoboken
ER  -