Research priorities to fill knowledge gaps on ASF seasonality that could improve the control of ASF

Abstract

The European Commission requested EFSA to provide study designs for the investigation of four research domains according to major gaps in knowledge identified by EFSA in a report published in 2019: i) the patterns of seasonality of ASF in wild boar and domestic pigs in the EU; ii) the ASF epidemiology in wild boar; iii) ASF virus (ASFV) survival in the environment and iv) ASF transmission by vectors. In this Scientific Opinion, the first research domain on ASF seasonality is addressed. Therefore, five research objectives were proposed by the working group and broader ASF expert networks, such as ASF stop, ENETWILD, VectorNet, AHAW network and the AHAW Panel Experts. Of the five research objectives, only two were prioritised and elaborated into a general protocol/study design research proposal, namely: 1) to monitor the herd incidence of ASF outbreaks in EU Member States (MS) and 2) to investigate potential (seasonal) risk factors for ASF incursion in domestic pig herds of different herd types and/or size. To monitor the incidence in different pig herd types, it is advised to collect, besides ASF surveillance data, pig population data describing at least the following parameters per farm from the first moment of incursion in an affected MS: the numbers of pigs (e.g. number of breeding pigs sows and boars, weaners and fatteners) and the location and the type of farm (including details on the level of biosecurity implemented on the farm and the outdoor/indoor production). We suggest collecting data from all ASF‐affected MS through the SIGMA data model, which was developed for this purpose. To investigate potential risk factors for ASF incursion in domestic pig herds, we suggest a matched case–control design. Such a study design can be run either retrospectively or prospectively. The collected data on the pig herds and the ASF surveillance data in the SIGMA data model can be used to identify case and control farms.