Sheep scab transmission: a spatially explicit dynamic metapopulation model
Abstract Psoroptic mange (sheep scab), caused by the parasitic mite, Psoroptes ovis, is an important disease of sheep worldwide. It causes chronic animal welfare issues and economic losses. Eradication of scab has proved impossible in many sheep-rearing areas and recent reports of resistance to macr...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2021-04-01
|
| Series: | Veterinary Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13567-021-00924-y |
| _version_ | 1818329388584796160 |
|---|---|
| author | Emily Nixon Ellen Brooks-Pollock Richard Wall |
| author_facet | Emily Nixon Ellen Brooks-Pollock Richard Wall |
| author_sort | Emily Nixon |
| collection | DOAJ |
| description | Abstract Psoroptic mange (sheep scab), caused by the parasitic mite, Psoroptes ovis, is an important disease of sheep worldwide. It causes chronic animal welfare issues and economic losses. Eradication of scab has proved impossible in many sheep-rearing areas and recent reports of resistance to macrocyclic lactones, a key class of parasiticide, highlight the importance of improving approaches to scab management. To allow this, the current study aimed to develop a stochastic spatial metapopulation model for sheep scab transmission which can be adapted for use in any geographical region, exhibited here using data for Great Britain. The model uses agricultural survey and sheep movement data to geo-reference farms and capture realistic movement patterns. Reported data on sheep scab outbreaks from 1973 to 1991 were used for model fitting with Sequential Monte Carlo Approximate Bayesian Computation methods. The outbreak incidence predicted by the model was from the same statistical distribution as the reported outbreak data ( $${\chi }^{2}$$ χ 2 = 115.3, p = 1) and the spatial location of sheep scab outbreaks predicted was positively correlated with the observed outbreak data by county ( $$\tau$$ τ = 0.55, p < 0.001), confirming that the model developed is able to accurately capture the number of farms infected in a year, the seasonality of scab incidence and the spatial patterns seen in the data. This model gives insight into the transmission dynamics of sheep scab and will allow the exploration of more effective control strategies. |
| first_indexed | 2024-12-13T12:47:16Z |
| format | Article |
| id | doaj.art-9302b8d5cb0c44ecaa5a2ea55c56924f |
| institution | Directory Open Access Journal |
| issn | 1297-9716 |
| language | English |
| last_indexed | 2024-12-13T12:47:16Z |
| publishDate | 2021-04-01 |
| publisher | BMC |
| record_format | Article |
| series | Veterinary Research |
| spelling | doaj.art-9302b8d5cb0c44ecaa5a2ea55c56924f2022-12-21T23:45:27ZengBMCVeterinary Research1297-97162021-04-015211910.1186/s13567-021-00924-ySheep scab transmission: a spatially explicit dynamic metapopulation modelEmily Nixon0Ellen Brooks-Pollock1Richard Wall2School of Biological Sciences, University of BristolBristol Veterinary School, University of BristolSchool of Biological Sciences, University of BristolAbstract Psoroptic mange (sheep scab), caused by the parasitic mite, Psoroptes ovis, is an important disease of sheep worldwide. It causes chronic animal welfare issues and economic losses. Eradication of scab has proved impossible in many sheep-rearing areas and recent reports of resistance to macrocyclic lactones, a key class of parasiticide, highlight the importance of improving approaches to scab management. To allow this, the current study aimed to develop a stochastic spatial metapopulation model for sheep scab transmission which can be adapted for use in any geographical region, exhibited here using data for Great Britain. The model uses agricultural survey and sheep movement data to geo-reference farms and capture realistic movement patterns. Reported data on sheep scab outbreaks from 1973 to 1991 were used for model fitting with Sequential Monte Carlo Approximate Bayesian Computation methods. The outbreak incidence predicted by the model was from the same statistical distribution as the reported outbreak data ( $${\chi }^{2}$$ χ 2 = 115.3, p = 1) and the spatial location of sheep scab outbreaks predicted was positively correlated with the observed outbreak data by county ( $$\tau$$ τ = 0.55, p < 0.001), confirming that the model developed is able to accurately capture the number of farms infected in a year, the seasonality of scab incidence and the spatial patterns seen in the data. This model gives insight into the transmission dynamics of sheep scab and will allow the exploration of more effective control strategies.https://doi.org/10.1186/s13567-021-00924-yControlDiseaseEctoparasitePsoroptes ovisSheep movementTransmission dynamics |
| spellingShingle | Emily Nixon Ellen Brooks-Pollock Richard Wall Sheep scab transmission: a spatially explicit dynamic metapopulation model Veterinary Research Control Disease Ectoparasite Psoroptes ovis Sheep movement Transmission dynamics |
| title | Sheep scab transmission: a spatially explicit dynamic metapopulation model |
| title_full | Sheep scab transmission: a spatially explicit dynamic metapopulation model |
| title_fullStr | Sheep scab transmission: a spatially explicit dynamic metapopulation model |
| title_full_unstemmed | Sheep scab transmission: a spatially explicit dynamic metapopulation model |
| title_short | Sheep scab transmission: a spatially explicit dynamic metapopulation model |
| title_sort | sheep scab transmission a spatially explicit dynamic metapopulation model |
| topic | Control Disease Ectoparasite Psoroptes ovis Sheep movement Transmission dynamics |
| url | https://doi.org/10.1186/s13567-021-00924-y |
| work_keys_str_mv | AT emilynixon sheepscabtransmissionaspatiallyexplicitdynamicmetapopulationmodel AT ellenbrookspollock sheepscabtransmissionaspatiallyexplicitdynamicmetapopulationmodel AT richardwall sheepscabtransmissionaspatiallyexplicitdynamicmetapopulationmodel |