Abstract
Using data from a cohort study conducted by the Veterinary Laboratories Agency (VLA), evidence of spatial clustering at distances up to 30 km was found for S. Agama and S. Dublin (P values of 0.001) and borderline evidence was found for spatial clustering of S. Typhimurium (P = 0.077). The evolution of infection status of study farms over time was modelled using a Markov Chain model with transition probabilities describing changes in status at each of four visits, allowing for the effect of sampling visit. The degree of geographical clustering of infection, having allowed for temporal effects, was assessed by comparing the residual deviance from a model including a measure of recent neighbourhood infection levels with one excluding this variable. The number of cases arising within a defined distance and time period of an index case was higher than expected. This provides evidence for spatial and spatio-temporal clustering, which suggests either a contagious process (e.g. through direct or indirect farm-to-farm transmission) or geographically localized environmental and/or farm factors which increase the risk of infection. The results emphasize the different epidemiology of the three Salmonella serovars investigated.
| Original language | English |
|---|---|
| Pages (from-to) | 847-857 |
| Number of pages | 11 |
| Journal | Epidemiology and Infection |
| Volume | 137 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 1 Jan 2009 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Epidemiology
- K-function analysis
- Markov chain
- Salmonella
- Spatial clustering
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