Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period
African swine fever (ASF) is a notifiable viral pig disease with high mortality and serious socio-economic consequences. Since ASF emerged in Georgia in 2007 the disease has spread to several neighbouring countries and cases have been detected in areas bordering the European Union (EU). It is uncert...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
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Elsevier
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/27700 |
| _version_ | 1855525452527960064 |
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| author | Nigsch, A. Costard, Solenne Jones, B.A. Pfeiffer, Dirk U. Wieland, Barbara |
| author_browse | Costard, Solenne Jones, B.A. Nigsch, A. Pfeiffer, Dirk U. Wieland, Barbara |
| author_facet | Nigsch, A. Costard, Solenne Jones, B.A. Pfeiffer, Dirk U. Wieland, Barbara |
| author_sort | Nigsch, A. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | African swine fever (ASF) is a notifiable viral pig disease with high mortality and serious socio-economic consequences. Since ASF emerged in Georgia in 2007 the disease has spread to several neighbouring countries and cases have been detected in areas bordering the European Union (EU). It is uncertain how fast the virus would be able to spread within the unrestricted European trading area if it were introduced into the EU. This project therefore aimed to develop a model for the spread of ASF within and between the 27 Member States (MS) of the EU during the high risk period (HRP) and to identify MS that would most likely contribute to ASF spread (“super-spreaders”) or MS that would most likely receive cases from other MS (“super-receivers”). A stochastic spatio-temporal state-transition model using simulated individual farm records was developed to assess silent ASF virus spread during different predefined HRPs of 10–60 days duration. Infection was seeded into farms of different pig production types in each of the 27 MS. Direct pig-to-pig transmission and indirect transmission routes (pig transport lorries and professional contacts) were considered the main pathways during the early stages of an epidemic. The model was parameterised using data collated from EUROSTAT, TRACES, a questionnaire sent to MS, and the scientific literature. Model outputs showed that virus circulation was generally limited to 1–2 infected premises per outbreak (95% IQR: 1–4; maximum: 10) with large breeder farms as index case resulting in most infected premises. Seven MS caused between-MS spread due to intra-Community trade during the first 10 days after seeding infection. For a HRP of 60 days from virus introduction, movements of infected pigs will originate at least once from 16 MS, with 6 MS spreading ASF in more than 10% of iterations. Two thirds of all intra-Community spread was linked to six trade links only. Denmark, the Netherlands, Lithuania and Latvia were identified as “super-spreaders”; Germany and Poland as “super-receivers”. In the sensitivity analysis, the total number of premises per country involved in intra-Community trade was found to be a key determinant for the between-MS spread dynamic and needs to be further investigated. It was concluded that spread during the HRP is likely to be limited, especially if the HRP is short. This emphasises the importance of having good disease awareness in all MS for early disease detection. |
| format | Journal Article |
| id | CGSpace27700 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2013 |
| publishDateRange | 2013 |
| publishDateSort | 2013 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace277002024-01-17T12:58:34Z Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period Nigsch, A. Costard, Solenne Jones, B.A. Pfeiffer, Dirk U. Wieland, Barbara animal diseases swine African swine fever (ASF) is a notifiable viral pig disease with high mortality and serious socio-economic consequences. Since ASF emerged in Georgia in 2007 the disease has spread to several neighbouring countries and cases have been detected in areas bordering the European Union (EU). It is uncertain how fast the virus would be able to spread within the unrestricted European trading area if it were introduced into the EU. This project therefore aimed to develop a model for the spread of ASF within and between the 27 Member States (MS) of the EU during the high risk period (HRP) and to identify MS that would most likely contribute to ASF spread (“super-spreaders”) or MS that would most likely receive cases from other MS (“super-receivers”). A stochastic spatio-temporal state-transition model using simulated individual farm records was developed to assess silent ASF virus spread during different predefined HRPs of 10–60 days duration. Infection was seeded into farms of different pig production types in each of the 27 MS. Direct pig-to-pig transmission and indirect transmission routes (pig transport lorries and professional contacts) were considered the main pathways during the early stages of an epidemic. The model was parameterised using data collated from EUROSTAT, TRACES, a questionnaire sent to MS, and the scientific literature. Model outputs showed that virus circulation was generally limited to 1–2 infected premises per outbreak (95% IQR: 1–4; maximum: 10) with large breeder farms as index case resulting in most infected premises. Seven MS caused between-MS spread due to intra-Community trade during the first 10 days after seeding infection. For a HRP of 60 days from virus introduction, movements of infected pigs will originate at least once from 16 MS, with 6 MS spreading ASF in more than 10% of iterations. Two thirds of all intra-Community spread was linked to six trade links only. Denmark, the Netherlands, Lithuania and Latvia were identified as “super-spreaders”; Germany and Poland as “super-receivers”. In the sensitivity analysis, the total number of premises per country involved in intra-Community trade was found to be a key determinant for the between-MS spread dynamic and needs to be further investigated. It was concluded that spread during the HRP is likely to be limited, especially if the HRP is short. This emphasises the importance of having good disease awareness in all MS for early disease detection. 2013-03 2013-03-10T12:05:02Z 2013-03-10T12:05:02Z Journal Article https://hdl.handle.net/10568/27700 en Limited Access Elsevier Nigsch, A., Costard, S., Jones, B.A., Pfeiffer, D.U. and Wieland, B. 2013. Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period. Preventive Veterinary Medicine 108(4): 262-275. |
| spellingShingle | animal diseases swine Nigsch, A. Costard, Solenne Jones, B.A. Pfeiffer, Dirk U. Wieland, Barbara Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period |
| title | Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period |
| title_full | Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period |
| title_fullStr | Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period |
| title_full_unstemmed | Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period |
| title_short | Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period |
| title_sort | stochastic spatio temporal modelling of african swine fever spread in the european union during the high risk period |
| topic | animal diseases swine |
| url | https://hdl.handle.net/10568/27700 |
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