Social network analysis provides insights into African swine fever epidemiology
Pig movements play a significant role in the spread of economically important infectious diseases such as the African swine fever. Characterization of movement networks between pig farms and through other types of farm and household enterprises that are involved in pig value chains can provide usefu...
| Main Authors: | , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
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Elsevier
2016
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/70222 |
| _version_ | 1855522783196348416 |
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| author | Lichoti, J.K. Davies, J. Kitala, P.M. Githigia, S.M. Okoth, Edward A. Maru, Y. Bukachi, S.A. Bishop, Richard P. |
| author_browse | Bishop, Richard P. Bukachi, S.A. Davies, J. Githigia, S.M. Kitala, P.M. Lichoti, J.K. Maru, Y. Okoth, Edward A. |
| author_facet | Lichoti, J.K. Davies, J. Kitala, P.M. Githigia, S.M. Okoth, Edward A. Maru, Y. Bukachi, S.A. Bishop, Richard P. |
| author_sort | Lichoti, J.K. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Pig movements play a significant role in the spread of economically important infectious diseases such as the African swine fever. Characterization of movement networks between pig farms and through other types of farm and household enterprises that are involved in pig value chains can provide useful information on the role that different participants in the networks play in pathogen transmission. Analysis of social networks that underpin these pig movements can reveal pathways that are important in the transmission of disease, trade in commodities, the dissemination of information and the influence of behavioural norms. We assessed pig movements among pig keeping households within West Kenya and East Uganda and across the shared Kenya-Uganda border in the study region, to gain insight into within-country and trans-boundary pig movements.Villages were sampled using a randomized cluster design. Data were collected through interviews in 2012 and 2013 from 683 smallholder pig-keeping households in 34 villages. NodeXL software was used to describe pig movement networks at village level.The pig movement and trade networks were localized and based on close social networks involving family ties, friendships and relationships with neighbours. Pig movement network modularity ranged from 0.2–0.5 and exhibited good community structure within the network implying an easy flow of knowledge and adoption of new attitudes and beliefs, but also promoting an enhanced rate of disease transmission. The average path length of 5 defined using NodeXL, indicated that disease could easily reach every node in a cluster. Cross-border boar service between Uganda and Kenya was also recorded. Unmonitored trade in both directions was prevalent. While most pig transactions in the absence of disease, were at a small scale (<5 km) and characterized by regular agistment, most pig sales during ASF outbreaks were to traders or other farmers from outside the sellers' village at a range of >10 km. The close social relationships between actors in pig movement networks indicate the potential for possible interventions to develop shared norms and mutually accepted protocols amongst smallholder pig keepers to better manage the risk of ASF introduction and transmission. |
| format | Journal Article |
| id | CGSpace70222 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace702222025-01-27T15:00:52Z Social network analysis provides insights into African swine fever epidemiology Lichoti, J.K. Davies, J. Kitala, P.M. Githigia, S.M. Okoth, Edward A. Maru, Y. Bukachi, S.A. Bishop, Richard P. swine animal diseases Pig movements play a significant role in the spread of economically important infectious diseases such as the African swine fever. Characterization of movement networks between pig farms and through other types of farm and household enterprises that are involved in pig value chains can provide useful information on the role that different participants in the networks play in pathogen transmission. Analysis of social networks that underpin these pig movements can reveal pathways that are important in the transmission of disease, trade in commodities, the dissemination of information and the influence of behavioural norms. We assessed pig movements among pig keeping households within West Kenya and East Uganda and across the shared Kenya-Uganda border in the study region, to gain insight into within-country and trans-boundary pig movements.Villages were sampled using a randomized cluster design. Data were collected through interviews in 2012 and 2013 from 683 smallholder pig-keeping households in 34 villages. NodeXL software was used to describe pig movement networks at village level.The pig movement and trade networks were localized and based on close social networks involving family ties, friendships and relationships with neighbours. Pig movement network modularity ranged from 0.2–0.5 and exhibited good community structure within the network implying an easy flow of knowledge and adoption of new attitudes and beliefs, but also promoting an enhanced rate of disease transmission. The average path length of 5 defined using NodeXL, indicated that disease could easily reach every node in a cluster. Cross-border boar service between Uganda and Kenya was also recorded. Unmonitored trade in both directions was prevalent. While most pig transactions in the absence of disease, were at a small scale (<5 km) and characterized by regular agistment, most pig sales during ASF outbreaks were to traders or other farmers from outside the sellers' village at a range of >10 km. The close social relationships between actors in pig movement networks indicate the potential for possible interventions to develop shared norms and mutually accepted protocols amongst smallholder pig keepers to better manage the risk of ASF introduction and transmission. 2016-04 2016-01-31T19:15:41Z 2016-01-31T19:15:41Z Journal Article https://hdl.handle.net/10568/70222 en Limited Access Elsevier Lichoti, J.K., Davies, J., Kitala, P.M., Githigia, S.M., Okoth, E., Maru, Y., Bukachi, S.A. and Bishop, R.P. 2016. Social network analysis provides insights into African swine fever epidemiology. Preventive Veterinary Medicine 126:1-10. |
| spellingShingle | swine animal diseases Lichoti, J.K. Davies, J. Kitala, P.M. Githigia, S.M. Okoth, Edward A. Maru, Y. Bukachi, S.A. Bishop, Richard P. Social network analysis provides insights into African swine fever epidemiology |
| title | Social network analysis provides insights into African swine fever epidemiology |
| title_full | Social network analysis provides insights into African swine fever epidemiology |
| title_fullStr | Social network analysis provides insights into African swine fever epidemiology |
| title_full_unstemmed | Social network analysis provides insights into African swine fever epidemiology |
| title_short | Social network analysis provides insights into African swine fever epidemiology |
| title_sort | social network analysis provides insights into african swine fever epidemiology |
| topic | swine animal diseases |
| url | https://hdl.handle.net/10568/70222 |
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