Network analysis of live pig movements in the Republic of North Macedonia in the period 2019-2020: Identification of key farms and municipalities regar­ding their role in the spread of infectious diseases

Abstract

Social network analysis could be a useful tool in the understanding of many aspects of animal movements because the movement of pigs between farms is one of the main routes for the spread of infectious diseases. Its outputs may highlight information about pig farms and areas that are highly connected and identify key players in animal traffic. The purpose of the study was to identify key farms in the live pig movement network and detect municipalities in North Macedonia which are at risk of disease transmission due to increased pig movements. To this end, completed live pig movement data in the period 2019-2020 extracted from the electronic national database in the system of identification and registration of animals, from the Food and Veterinary Agency of the Republic of North Macedonia was used. Igraph package in R programming language was used to carry out the analysis and spdep package to test spatial autocorrelation. Our findings showed that the size of the network was 320 nodes and 859 links. It was found that 215 (67.2%) farms had in-degree values in the range 1-164 and 137 (42.8%) farms had out-degree values in range of 1-166. Twenty-four farms (7.5%) showed a betweenness centrality value of 1-72, and the cut-point analysis detected 56 farms (17.5%), with most farms located in central, east, and southeastern parts of the country. Network density showed 0.008 or 0.8% and clustering coefficient (transitivity) of 0.017. Moran’s I statistic for spatial autocorrelation of municipalities with summarised in-degree showed negative value (-0.003, p=0.295) and municipalities with summarised out-degree showed positive value (0.126, p=0.031). This study identified pig farms that could influence the animal flow and their geographical location. The municipality of Veles was identified as the area with the highest arrivals and departures of pig batches. Findings may be useful to inform decision-makers to target farms and municipalities for surveillance and to organise official control and early detection of contagious swine diseases