Managing African Swine Fever: Assessing the Potential of Camera Traps in Monitoring Wild Boar Occupancy Trends in Infected and Non-infected Zones, Using Spatio-Temporal Statistical Models

Abstract

The recent spreading of African swine fever (ASF) over the Eurasian continent has been acknowledged as a serious economic threat for the pork industry. Consequently, an extensive body of research focuses on the epidemiology and control of ASF. Nevertheless, little information is available on the combined effect of ASF and ASF-related control measures on wild boar (Sus scrofa) population abundances. This is crucial information given the role of the remaining wild boar that act as an important reservoir of the disease. Given the high potential of camera traps as a non-invasive method for ungulate trend estimation, we assess the effectiveness of ASF control measures using a camera trap network. In this study, we focus on a major ASF outbreak in 2018-2020 in the South of Belgium. This outbreak elicited a strong management response, both in terms of fencing off a large infected zone as well as an intensive culling regime. We apply a Bayesian multi-season site-occupancy model to wild boar detection/non-detection data. Our results show that (1) occupancy rates at the onset of our monitoring period reflect the ASF infection status; (2) ASF-induced mortality and culling efforts jointly lead to decreased occupancy over time; and (3) the estimated mean total extinction rate ranges between 22.44 and 91.35%, depending on the ASF infection status. Together, these results confirm the effectiveness of ASF control measures implemented in Wallonia (Belgium), which has regained its disease-free status in December 2020, as well as the usefulness of a camera trap network to monitor these effects.

Keywords: African swine fever; Bayesian inference; Stan; camera traps; occupancy; spatio-temporal.

Figure 1

Map of the study area with the overlaying hexagonal grids. Camera deployments are indicated by the black dots. Black lines represent fences. Colors represent the African swine fever management zones; ASF-infected (red), non-infected (turquoise) and excluded (gray). The inset map (bottom) shows the study area within Belgium.

Figure 2

Monthly posterior mean occupancy estimates (dots) and 95% highest posterior density intervals (vertical lines) per ASF management zone (A). Cumulative number of wild boar culled per km² in function of the observation month. Trend lines derived from ordinary least squares regression estimation (B).

Figure 3

Posterior mean occupancy of wild boar in the ASF-infected (enclosed by the black line) and non-infected (non-enclosed) zone in Wallonia (Belgium). Panels ranging from March 2019 until May 2020.