ArticleOpen veterinary journal
Role of eco-climatic factors in the distribution of bluetongue in endemic areas in Tunisia.
Article in Open veterinary journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Epidemiological Analyses of the First Incursion of the Epizootic Hemorrhagic Disease Virus Serotype 8 in Tunisia, 2021-2022.Viruses · 2024Article
- Retrospective Phylodynamic and Phylogeographic Analysis of the Bluetongue Virus in Tunisia.Evolutionary bioinformatics online · 2023Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Bluetongue (BT) is an important infectious, non-contagious, OIE-listed viral disease of domestic and wild ruminants. The disease is transmitted among susceptible animals by a few species of an insect vector in the genus Aim: Determine the eco-climatic variables most likely associated with delegations reporting BT cases. Methods: A logistic regression model (LRM) was used to examine which eco-climatic variables were most likely associated with delegations reporting BT cases. Results: Based on the LRM, our findings demonstrated that the key factors contributing significantly to BT cases' distribution among delegations in Tunisia included day land surface temperatures (DLST), night land surface temperatures (NLST) and normalized difference vegetation index (NDVI). A positive correlation between sheep distribution and rainfall amounts was demonstrated. Statistical analysis focusing on the most affected delegations during the BT epidemic (the Sahel and the Centre of Tunisia) demonstrated that the epidemic situation seems to be a consequence of the combination of the following environmental parameters: NDVI with values ranging between 0.16 and 0.2, moderate rainfall 2-4-fold above the normal (10-50 mm) and DLST values between 32°C and 34°C in September. Conclusion: These findings suggest and develop a robust and efficient early warning surveillance program in risk areas based on eco-climatic risk factors.
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Registered trials
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