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New tools for the risk assessment and modelling of African swine fever in backyard predominant settings

Abstract

The Food and Agricultural Organization of the United Nations (FAO) has classified African swine fever (ASF) as one of the most serious transboundary animal diseases (TADs) currently impacting the world due to its high lethality for pigs and crippling socio-economic consequences. ASF is a re-emergent viral hemorrhagic disease affecting domestic and wild suids. Until 2007, ASF was an exclusive problem of South Saharan African countries and the Italian island of Sardinia. However, since its introduction to Eastern Europe and the Caucasus region in 2007, ASF has continued a slow but steady spread north and westward, establishing itself in the wild boar populations of Europe and the Russian Federation, with numerous outbreaks in domestic pigs, primarily in backyard settings. In August 2018, ASF was introduced into China, and has since rapidly spread throughout Southeastern Asia, leaving economic devastation and millions of dead and/or culled pigs across more than 16 countries. In July of 2021, ASF was reported in the Western Hemisphere for the first time in 40 years, with outbreaks ongoing across the island of Hispaniola. The current spread of ASF is far from being controlled, and it is likely that new countries and regions will become infected during this ASF pandemic. Countries across the world are updating their surveillance programs and response planning based on the high risk of a potential ASF introduction. This work focused on North Macedonia, a country in the Balkan region of Europe, which is currently bordered to the north and east by countries with active ASF outbreaks. Working with FAO and the local Veterinary Authority, this work aimed to better understand the risk of ASF introduction and spread in North Macedonia’s predominantly backyard pig sector. The first chapter of this work described the pork value chain, husbandry and biosecurity practices, and ASF awareness, in North Macedonia’s swine industry as defined by a semi-structured questionnaire administered to more than 450 farmers. These data were used to calculate a biosecurity risk score for each farm, and multiple correspondence analysis (MCA) was used to evaluate patterns in farm practices that may predict a farm’s risk for disease introduction/spread. The eastern regions of the country were identified as being at highest risk for ASF introduction. Improvements in isolation of new pigs and basic sanitary practices, particularly among smallholder farms, was recommended. Chapter 2 described 2016-2020 swine census data and used 2017-2019 live pig movement data to conduct a network analysis to better understand pig movement patterns in the country. Census data revealed the improved identification and reporting of pig farms and numbers. Network analysis identified farms with consistently high rates of shipments and receipt of pigs for targeted intervention. Smallholder farms demonstrated a large amount of turnover, contributing to network instability in this subgroup. Live pig movement data showed that movements to slaughter predominated (85.6%), with movements between farms (5.4%) and movements to market (5.8%) playing a lesser role. Fragmentation of the 2019 network in comparison to previous years may aid in response planning. This information may be used to inform risk-based surveillance and interventions to prevent and better control disease spread, and to support business continuity in the country. Chapter 3 implemented an agent-based model to simulate the spread of ASF based on the live pig movement network and underlying farm, pig, and wild boar population densities. This model demonstrated that disease introduction into family and commercial farms resulted in larger and more widespread outbreaks. Outbreaks starting in backyard farms are expected to increase the probability of infection through the Eastern and Southeastern regions, while introductions into family and commercial farms result in more widespread outbreaks impacting the Vardar and Northeastern regions. Increasing surveillance was able to reduce the cumulative number of outbreaks over 18 months by up to 80%, while movement restrictions resulted in a 62% decrease. Overall, this work contributes to a better understanding of disease risk and transmission dynamics in backyard predominant settings and has provided practical information to the North Macedonian Veterinary Authority on the current practices and biosecurity gaps in their swine industry. These results will inform targeted outreach and education campaigns, and risk-based mitigations to ideally prevent the introduction of ASF. These approaches can be broadly applied to countries working to improve their preparedness strategies for a variety of swine diseases and TADs.

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