Search

African Swine Fever (ASF) represents the main threat to swine production, with heavy economic consequences for both farmers and the food industry. The spread of the virus that causes ASF through Europe raises the issues of identifying transmission routes and assessing their relative contributions in order to provide insights to stakeholders for adapted surveillance and control measures. A simulation model was developed to assess ASF spread over the commercial swine network in France. The model was designed from raw movement data and actual farm characteristics. A metapopulation approach was used, with transmission processes at the herd level potentially leading, through a reaction-diffusion process, to external spread to epidemiologically connected herds. Three transmission routes were considered: local transmission (e.g. fomites, material exchange), movement of animals from infected to susceptible sites, and transit of trucks without physical animal exchange. Surveillance was based on prevalence and mortality detection thresholds, which triggered control measures based on movement ban for detected herds and epidemiologically related herds. The time from infection to detection varied between 8 and 21 days, depending on the detection criteria, but was also dependent on the types of herds in which the infection was introduced. Movement restrictions effectively reduced the transmission between herds, but local transmission was nevertheless observed in higher proportions highlighting the need of global awareness of all actors of the swine industry to mitigate the risk of local spread. Raw movement data were directly used to build a dynamic network on a realistic time-scale. This approach allows for a rapid update of input data without any pre-treatment, which could be important in terms of reactivity, should an introduction occur., Comment: 26 pages; 7 figures

The spread of African swine fever (ASF) poses a grave threat to the global swine industry. Understanding transmission dynamics, such as through mechanistic modeling, is critical for designing effective control strategies. Articles were examined across multiple epidemiological and model characteristics. Model filiation was determined through creation of a neighbor-joined tree using phylogenetic software. Of 34 four articles qualifying for inclusion, four main modelling objectives were identified: estimating transmission parameters (11 studies), assessing determinants of transmission (7), examining consequences of hypothetical outbreaks (5), and assessing alternative control strategies (11). Estimated transmission parameters varied widely as did parameter assumptions between models. Uncertainties on epidemiological and ecological parameters were usually accounted for to assess the impact on the modeled infection trajectory. Almost all models are host specific, being developed for either domestic pigs or wild boar despite the fact that spillover events between domestic pigs and wild boar are evidenced to play an important role in ASF outbreaks. The development of models incorporating such transmission routes is crucial. All compared control strategies were defined a priori, and future models should be built to identify optimal contributions across many control methods. Further, control strategies were examined in competition, opposed to how they would be synergistically implemented. While comparing strategies is beneficial for identifying a rank-order efficacy of control methods, this structure does not necessarily determine the most effective combination of all available strategies. In order for ASFV models to effectively support decision-making in controlling ASFV globally, these modelling limitations need to be addressed., Comment: 19 pages, 3 figures, 4 tables. Accepted to Preventive Veterinary Medicine. Revised from previous preprint to include models published through Dec 2020