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Regional Level Risk Factors Associated with the Occurrence of African Swine Fever in West and East Africa Zheng Y

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Regional Level Risk Factors Associated with the Occurrence of African Swine Fever in West and East Africa Zheng Y Huang et al. Parasites & Vectors (2017) 10:16 DOI 10.1186/s13071-016-1953-z RESEARCH Open Access Regional level risk factors associated with the occurrence of African swine fever in West and East Africa Zheng Y. X. Huang1,2*, Frank van Langevelde2, Karanina J. Honer2,3, Marc Naguib3 and Willem F. de Boer2 Abstract Background: African swine fever (ASF) causes severe socio-economic impacts due to high mortality and trade restrictions. Many risk factors of ASF have been identified at farm level. However, understanding the risk factors, especially wild suid hosts, determining ASF transmission at regional level remains limited. Methods: Based on ASF outbreak data in domestic pigs during 2006–2014, we here tested, separately for West and East Africa, which risk factors were linked to ASF presence at a regional level, using generalized linear mixed models. Results: Our results show that ASF infections in the preceding year was an important predictor for ASF presence in both West and East Africa. Both pig density and human density were positively associated with ASF presence in West Africa. In East Africa, ASF outbreaks in domestic pigs were also correlated with higher percentages of areas occupied by giant forest hogs and by high-tick-risk areas. Conclusions: Our results suggest that regional ASF risk in East Africa and in West Africa were associated with different sets of risk factors. Regional ASF risk in West Africa mainly followed the domestic cycle, whereas the sylvatic cycle may influence regional ASF risk in East Africa. With these findings, we contribute to the better understanding of the risk factors of ASF occurrence at regional scales that may aid the implementation of effective control measures. Keywords: Domestic cycle, Sylvatic cycle, Wild suid, Giant forest hog, Habitat fragmentation, Ornithodoros moubata Background epidemiology of ASF is fundamental to implement African swine fever (ASF), caused by a DNA virus of the effective control measures [2, 6, 7]. genus Asfivirus, is a highly contagious disease for ASF outbreaks have been reported for many sub- domestic pigs. It can have severe socio-economic im- Saharan African countries, and the epidemiology and pacts due to high mortality and trade restrictions [1]. ecology of ASF are thought to vary between different re- ASF is considered the major limiting factor for pig pro- gions [8, 9]. Generally, it has been considered that ASF duction in many sub-Saharan African countries where a virus can circulate through two cycles in sub-Saharan significant commercial pig industry exists [1, 2]. ASF has Africa, the sylvatic cycle and the domestic cycle [2, 9, also spread outside Africa, including recently to the 10]. The sylvatic cycle has been documented in some Caucasus and Russia, posing considerable threats to the Eastern and Southern African countries [7, 9–12]. It in- global pig industry [3–6]. Because no vaccine has been volves wild suids as the host, including the common developed, a full understanding of the ecology and warthog (Phacochoerus africanus), and is spread via soft ticks (Ornithodoros moubata) to domestic pigs making the virus persistent [13]. However, in the domestic cycle * Correspondence: [email protected] ASF virus mainly spreads via direct contact between do- 1College of Life Sciences, Nanjing Normal University, 210023 Nanjing, China 2Resource Ecology Group, Wageningen University, 6708PB Wageningen, The mestic pigs or between pork products and pigs. A recent Netherlands study assessed the suitability of these two transmission Full list of author information is available at the end of the article © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Huang et al. Parasites & Vectors (2017) 10:16 Page 2 of 8 pathways in Africa and concluded that the domestic ASF occurrence in East Africa, whereas domestic pig cycle may occur throughout sub-Saharan Africa, whereas density and indicators of trade activities have a positive the sylvatic cycle might be found mainly in East, Central effect in West Africa. and Southern Africa, where warthogs are present [8]. A few studies have been conducted to investigate the Methods factors linked with ASF risk [10]. For the domestic cycle, African swine fever data the density or the herd size of domestic pigs has been Data on ASF presence/absence in domestic pigs for considered to be positively associated with ASF out- some countries in the sub-Saharan Africa from 2005 to breaks at farm level [9, 14]. Farms with traditional free- 2014 is available in the World Animal Health Informa- ranging husbandry systems typically experience higher tion (http://www.oie.int/wahis_2/public/wahid.php/ ASF risk, presumably due to low biosecurity [15]. Previ- Wahidhome/Home) from the World Organization for ous occurrence of the disease on a farm and infected Animal Health (OIE) [23], which provides data on ASF neighbouring farms has also been found to promote the outbreaks at a temporal resolution of 6 months. Some chance of ASF infection [16]. In addition to these risk African countries reported ASF outbreaks only at coun- factors, ASF spread in the domestic cycle has been try level, while other countries specified ASF outbreaks linked to trade-related factors [16, 17], such as the dens- at a smaller administrative level. The smallest adminis- ity of the road network and water bodies [14]. In fact, trative level of reporting was used as the level of analyses the movements of infected domestic pigs might be the in this study, whilst those countries reporting ASF out- most important factor for ASF spread in some regions, breaks only at country level were excluded from the especially in West Africa where the domestic cycle is study. Only the countries with “ASF history” (at least considered the only transmission pathway [7, 10, 18]. one outbreak was reported during the study period) For the sylvatic cycle, the common warthog has been were included in the analyses, as this excluded those considered the most important vertebrate host for the countries which had possibly ASF outbreaks but never circulation of ASF virus [13, 19]. Interspecific transmis- reported them, so that we avoided some false absence sion between warthogs and domestic pigs may occur in- data. Thus, we assumed that no report from a country/ad- directly through Ornithodoros ticks, especially when pigs ministrative unit that had previously reported ASF is indi- that share grazing areas with warthogs are bitten by in- cative of the absence of disease for that year. In addition, to fected ticks, or during human interference when wart- determine the effect of previous infection status, we only hog carcasses with infected ticks are transported [10]. involved the administrative areas from the countries that Bushpigs (Potamochoerus larvatus) can also spread ASF reporting ASF outbreaks in more than two consecutive to domestic pigs via ticks, but they are generally as- years. Areas without domestic pigs were excluded. The sumed less important than warthogs due to their lower data set yielded from OIE included eleven countries population densities, nocturnal habits, and limited con- (Angola, Benin, Burkina Faso, Cameroon, Ghana, tact with pigs and soft ticks [13, 20]. Finally, the red river Mozambique, Malawi, Nigeria, Rwanda, Togo, and hog (Potamochoerus porcus) and the giant forest hog Zambia). As we compared East Africa and West Africa, we (Hylochoerus meinertzhangeni) can also be infected [13]. then, according to the definition of Statistics Division of However, neither species seems to play an important the United Nations (http://millenniumindicators.un.org/ role in ASF transmission due to their limited/restricted unsd/methods/m49/m49.htm), excluded Angola and di- distributions [13]. vided the remaining ten countries into East Africa and To date, risk factors have predominantly been identi- West Africa. The final dataset (Additional file 1: Table S1, fied at farm level, whereas the influence of risk factors Figure S1) for the analyses of West Africa consisted of such as the role of wild suids and tick distribution on 1287 cases of ASF presence/absence data covering six the dynamics of ASF transmission at larger spatial scales countries and 177 administration areas, and the final data- is not well understood [8, 10]. Understanding regional set for East Africa included 394 cases of presence/absence risk factors of infectious diseases is necessary for reveal- data covering four countries and 51 administration areas. ing the underlying epidemiological processes that might lead to important implications for control at regional scales [1, 21, 22]. Therefore, the present study aims to Data of the predictors identify the risk factors that are associated with ASF oc- As the infection status of the previous year (PreInf) has currence at a regional scale in Africa. Due to the poten- been linked to ASF risk in earlier studies, we tested its tially different ASF transmission pathways, we compare effect to determine the dependency of ASF status be- the risk factors between West Africa and East Africa. tween years. We also tested for the effect of the domes- We expect that the presence of wild suids and tick dis- tic pig density (Pig) on the risk of ASF occurrence. As tribution is positively associated with the probability of indicators of trade activities, road density (Road) and Huang et al. Parasites & Vectors (2017) 10:16 Page 3 of 8 human population density (Human) were calculated for distribution and movements [13, 26].
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