The Risk of Infection by African Swine Fever Virus in European Swine Through Boar Movement and Legal Trade of Pigs and Pig Meat

Abstract

African swine fever (ASF) is currently spreading westwards throughout Europe and eastwards into China, with cases occurring in both wild boar and domestic pigs. A generic risk assessment framework is used to determine the probability of first infection with ASF virus (ASFV) at a fine spatial scale across European Union Member States. The framework aims to assist risk managers across Europe with their ASF surveillance and intervention activities. Performing the risk assessment at a fine spatial scale allows for hot-spot surveillance, which can aid risk managers by directing surveillance or intervention resources at those areas or pathways deemed most at risk, and hence enables prioritization of limited resources. We use 2018 cases of ASF to estimate prevalence of the disease in both wild boar and pig populations and compute the risk of initial infection for 2019 at a 100 km² cell resolution via three potential pathways: legal trade in live pigs, natural movement of wild boar, and legal trade in pig meat products. We consider the number of pigs, boar and amount of pig meat entering our area of interest, the prevalence of the disease in the origin country, the probability of exposure of susceptible pigs or boar in the area of interest to introduced infected pigs, boar, or meat from an infected pig, and the probability of transmission to susceptible animals. We provide maps across Europe indicating regions at highest risk of initial infection. Results indicate that the risk of ASF in 2019 was predominantly focused on those regions which already had numerous cases in 2018 (Poland, Lithuania, Hungary, Romania, and Latvia). The riskiest pathway for ASFV transmission to pigs was the movement of wild boar for Eastern European countries and legal trade of pigs for Western European countries. New infections are more likely to occur in wild boar rather than pigs, for both the pig meat and wild boar movement pathways. Our results provide an opportunity to focus surveillance activities and thus increase our ability to detect ASF introductions earlier, a necessary requirement if we are to successfully control the spread of this devastating disease for the pig industry.

Keywords: European Union (EU); disease hotspot; disease transmission; pork product; risk assessment; riskiest pathway; swine disease; wild boars.

Figure 1

The generic framework for calculating risk of infection spatially, as seen in Taylor et al. (34). There are five steps in the framework: Entry, Detection, Survival, Contact, and Transmission to address the risk question “What is the risk of infection of a pathogen in Area B due to the presence of that pathogen in Area A?” The term “unit” in Step 1 addresses the fact that it could be infected animals or products or contaminated items entering.

Figure 2

Risk pathway for the risk of ASFV infection in pigs and wild boar via the legal trade of meat products pathway. Probabilities or inputs considered for each step are outlined in green ovals, and the outputs along the pathway as rectangles. On the left, the boxes indicate how this framework fits within the more generic framework in Figure 1. The dashed lines indicate that the converse to the statement can also lead to meat products at a rubbish disposal.

Figure 3

The probability of at least one infection with ASFV in (A) wild boar or (B) pigs in 2019, plotted at a 100 km² cell level across Europe. Countries in gray have insufficient data to compute the risk.

Figure 4

The probability of at least one infection of ASFV in pigs in 2019 from trade of live pigs at a farm level. In (A) all of Europe is plotted while in (B) the map is zoomed in to the dotted rectangle in (A) and in (C) the map is zoomed in to the dashed rectangle in (A). All farms indicated by a circle imported at least one infected animal in at least one simulation and the color indicates the probability that one or more susceptible pigs became infected. Countries in gray have insufficient data to complete the risk assessment. All farms in the regions with negligible risk either did not import any pigs or did not import any infected pigs. ^©EuroGeographics for the administrative boundaries.

Figure 5

The probability of at least one infection of ASFV in 2019 in boar (A) and pigs (B) due to wild boar movement is plotted at a 100 km² cell level across Europe. Prevalence in wild boar is estimated from reported cases in 2018.

Figure 6

The probability of at least one infection of ASFV in boar in 2019 due to wild boar movement at a 100 km² cell level. We zoom in to three regions where there were cases in 2018 (A) Belgium; (B) Poland, Lithuania, and Latvia; and (C) Hungary, Czech Republic, and Romania. Countries are indicated by their ISO3 code.

Figure 7

The probability of at least one infection of ASFV in 2019 in (A) wild boar and (B) pigs, via trade in legal pig meat products, plotted at a 100 km² cell level across Europe. Countries in gray have insufficient data to complete the risk assessment.

Figure 8

The pathway which has the highest risk of infection of ASFV for (A) wild boar and (B) pigs is plotted at a 100 km² cell level across Europe. Countries in gray have insufficient data to complete the risk assessment.

Figure 9

The effect of uncertain parameters in the legal trade of pig meat products pathway on hotspots of disease risk across Europe. In (A,B) the number of 100 km² cells which are hotspots for wild boar infection and domestic pig infection are plotted, respectively, for the baseline and sensitivity parameters. In (C,D) the distribution of the probability of infection across 100 km² cells which are hotspots in Europe for wild boar and pig infection, respectively, for the baseline and sensitivity parameters. The baseline results, as shown in Figure 7, are denoted by Base. The sensitivity parameters are: WA, duration of waste availability for boar; WP, proportion of food that goes to waste; SF, the probability of illegal swill-feeding; BA, the probability that boar are able to access waste; and FC, the proportion of food that is cooked sufficiently to kill the virus.