Graph theory in veterinary epidemiology : modelling an outbreak of classical swine fever
One objective of this study has been to demonstrate how graph theory can be a useful tool for intervention in the case of an outbreak of a contagious disease. By using graph theory algorithms on data from the Swedish surveillance network system (Grisregistret) and combining this with the power of gr...
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| Format: | L3 |
| Language: | Inglés Swedish |
| Published: |
SLU/Dept. of Ruminant Medicine and Veterinary Epidemiology
2004
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| Subjects: |
| _version_ | 1855572119156424704 |
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| author | Widgren, Stefan |
| author_browse | Widgren, Stefan |
| author_facet | Widgren, Stefan |
| author_sort | Widgren, Stefan |
| collection | Epsilon Archive for Student Projects |
| description | One objective of this study has been to demonstrate how graph theory can be a useful tool for intervention in the case of an outbreak of a contagious disease. By using graph theory algorithms on data from the Swedish surveillance network system (Grisregistret) and combining this with the power of graph layout engines for visualization of interherd movements, valuable information can rapidly be provided from data that is easily available. Thus a clear line of priority in the strategy of fighting the outbreak can be established from day 0. This can be invaluable during the first couple of days, before more thorough information concerning all different types of contacts has been collected by veterinarians during farm visits. Thus rapid control measures can be implemented and this should increase the likelihood that possible infectious holdings are found during an early stage of the outbreak. Combining the information of the geographical location of an infectious holding and the interherd movements during the relevant time period on the same map can improve the understanding of the spread of the outbreak. It would also be possible to add information concerning other types of contacts, when such information becomes available, to make the picture clearer.
Another objective has been to model a putative outbreak of classical swine fever without any interventions from authorities. The epidemiological model uses data from the Swedish surveillance network system of pig movements, Grisregistret, based on the reported flows of pigs between farms. The model includes all interherd pig movements that occurred within a community in southern Sweden during 6 months. Both a high virulent strain and a low virulent strain of classical swine fever virus have been modelled. The epidemiological model is based on a SEIRD model for each holding, which have been interconnected to each other through the reported movements of pigs. |
| format | L3 |
| id | RepoSLU12723 |
| institution | Swedish University of Agricultural Sciences |
| language | Inglés swe |
| publishDate | 2004 |
| publishDateSort | 2004 |
| publisher | SLU/Dept. of Ruminant Medicine and Veterinary Epidemiology |
| publisherStr | SLU/Dept. of Ruminant Medicine and Veterinary Epidemiology |
| record_format | eprints |
| spelling | RepoSLU127232017-10-19T12:40:22Z Graph theory in veterinary epidemiology : modelling an outbreak of classical swine fever Grafteori i veterinär epidemiologi : modellering av ett utbrott av klassisk svinpest Widgren, Stefan graph theory modelling swine fever One objective of this study has been to demonstrate how graph theory can be a useful tool for intervention in the case of an outbreak of a contagious disease. By using graph theory algorithms on data from the Swedish surveillance network system (Grisregistret) and combining this with the power of graph layout engines for visualization of interherd movements, valuable information can rapidly be provided from data that is easily available. Thus a clear line of priority in the strategy of fighting the outbreak can be established from day 0. This can be invaluable during the first couple of days, before more thorough information concerning all different types of contacts has been collected by veterinarians during farm visits. Thus rapid control measures can be implemented and this should increase the likelihood that possible infectious holdings are found during an early stage of the outbreak. Combining the information of the geographical location of an infectious holding and the interherd movements during the relevant time period on the same map can improve the understanding of the spread of the outbreak. It would also be possible to add information concerning other types of contacts, when such information becomes available, to make the picture clearer. Another objective has been to model a putative outbreak of classical swine fever without any interventions from authorities. The epidemiological model uses data from the Swedish surveillance network system of pig movements, Grisregistret, based on the reported flows of pigs between farms. The model includes all interherd pig movements that occurred within a community in southern Sweden during 6 months. Both a high virulent strain and a low virulent strain of classical swine fever virus have been modelled. The epidemiological model is based on a SEIRD model for each holding, which have been interconnected to each other through the reported movements of pigs. Ett syfte med den här studien har varit att visa hur grafteori skulle kunna vara ett användbart verktyg vid bekämpning av ett utbrott av en smittsam sjukdom. Genom att använda grafteori algoritmer på data från det svenska Grisregistret och kombinera detta med möjligheten att visualisera förflyttningar mellan gårdar kan man få fram värdefull information snabbt från data som är lätt tillgänglig. Därmed får man ett underlag för prioriteringar i bekämpningsstrategin redan dag 0. Detta är viktigt under de första dagarna, innan mer detaljerad information samlats in genom gårdsbesök av veterinär. På så sätt kan kontrollåtgärder snabbt sättas in och borde öka möjligheten att tidigt under utbrottet finna gårdar som kan vara smittade. Därutöver skulle det också vara användbart att markera gårdarnas läge och förflyttningar av djur mellan dem på samma karta för att ytterligare öka förståelsen för spridningen av sjukdomen. Det skulle också vara möjligt att komplettera med information avseende andra typer av kontakter, när sådan informationen finns tillgänglig, för att få en tydligare bild. Ett annat syfte med studien har varit att modellera ett tänkt utbrott av klassisk svinpest utan att några insatser görs för att begränsa spridningen. Den epidemiologiska modellen använder data från det svenska Grisregistret, innehållande rapporterade förflyttningar av grisar mellan gårdar. Modellen inkluderar grisförflyttningar under 6 månader från en kommun i södra Sverige. Både en hög- och lågvirulent stam av klassiskt svinpestvirus har modellerats. Den epidemiologiska modellen bygger på en SEIRD modell för varje gård som kopplats samman genom de förflyttningar som är rapporterade till Grisregistret. SLU/Dept. of Ruminant Medicine and Veterinary Epidemiology 2004 L3 eng swe https://stud.epsilon.slu.se/12723/ |
| spellingShingle | graph theory modelling swine fever Widgren, Stefan Graph theory in veterinary epidemiology : modelling an outbreak of classical swine fever |
| title | Graph theory in veterinary epidemiology : modelling an outbreak of classical swine fever |
| title_full | Graph theory in veterinary epidemiology : modelling an outbreak of classical swine fever |
| title_fullStr | Graph theory in veterinary epidemiology : modelling an outbreak of classical swine fever |
| title_full_unstemmed | Graph theory in veterinary epidemiology : modelling an outbreak of classical swine fever |
| title_short | Graph theory in veterinary epidemiology : modelling an outbreak of classical swine fever |
| title_sort | graph theory in veterinary epidemiology : modelling an outbreak of classical swine fever |
| topic | graph theory modelling swine fever |