Role of eco-climatic factors in the distribution of bluetongue in endemic areas in Tunisia

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 . Recently, during the fall of 2020 (September and October), a Bluetongue virus-...

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Veröffentlicht in:Open Veterinary Journal 2022-01, Vol.12 (1), p.114-123
Hauptverfasser: Hassine, Thameur Ben, Sghaier, Soufiène, Thabet, Sarah, Ammar, Héni Haj, Hammami, Salah
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Sprache:eng
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Zusammenfassung: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 . Recently, during the fall of 2020 (September and October), a Bluetongue virus-4 epizootic marked the epidemiological situation in several delegations of Tunisia with clinical cases recorded in sheep and cattle. Determine the eco-climatic variables most likely associated with delegations reporting BT cases. A logistic regression model (LRM) was used to examine which eco-climatic variables were most likely associated with delegations reporting BT cases. 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. These findings suggest and develop a robust and efficient early warning surveillance program in risk areas based on eco-climatic risk factors.
ISSN:2226-4485
2218-6050
DOI:10.5455/OVJ.2022.v12.i1.14