Spatiotemporal analysis of African swine fever outbreaks on South African smallholder farms, 1993–2018

Authors

Keywords:

space-time, distribution, ASF, space-time K function, Kulldorff’s spatial scan statistic, South Africa

Abstract

African swine fever (ASF) is a contagious viral disease of swine worldwide. ASF in South Africa has for many years been confined to a controlled area in the northeast of the country that was proclaimed in 1935. Since 2012, outbreaks are more likely to occur in the historically ASF-free area. This study aimed to analyse the spatial and spatiotemporal structure of ASF outbreaks in South Africa between 1993 and 2018. Global space-time clustering of ASF outbreaks was investigated by the Diggle space-time K-function while Kulldorff’s spatial scan statistic was applied to detect local cluster of ASF outbreaks. Globally, ASF outbreaks exhibit statistically significant spatial clustering. They have shown a significant negative space-time interaction at month scale (p = 0.003) but no
significant space-time interaction at year scale (p = 0.577), revealing strong evidence that ASF cases that are close in space occur in months which are close and vice versa. In studying local area space-time clustering at both month and year scale, three significant local clusters associated with high-rate were detected. These clusters are localised in both the ASF-controlled area and outside the controlled area with radius varying from 60.84 km up to 271.43 km and risk ratio varying from 6.61 up to 17.70. At month scale, clusters with more outbreaks were observed between June 2017 and August 2017 and involved 22 outbreaks followed by the cluster that involved 13 outbreaks in January 2012. These results show the need to maintain high biosecurity standards on pig farms in both inside and outside the ASF-controlled areas.

Author Biographies

C A Mushagalusa, University of Pretoria

Department of Veterinary Tropical Diseases, Faculty of Veterinary Science, University of Pretoria, South Africa and Department of Animal Production, Faculty of Agriculture, Université Evangélique en Afrique, Democratic Republic of Congo and Laboratoire de Biomathématiques et d’Estimations Forestières (LABEF), Faculté des Sciences Agronomiques (FSA), Université d’Abomey-Calavi, Benin

M-L Penrith, University of Pretoria

Department of Veterinary Tropical Diseases, Faculty of Veterinary Science, University of Pretoria, South Africa

E M C Etter, University of Pretoria

Department of Production Animal Studies, Faculty of Veterinary Sciences, University of Pretoria, South Africa and CIRAD, UMR Animal, Santé, Territoires, Risque et Ecosystèmes (ASTRE), Petit-Bourg, Guadeloupe, and ASTRE, University of Montpellier, CIRAD, INRA, Montpellier, France

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Published

2022-06-16

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Section

Original Research