AI Article Synopsis

  • Bluetongue (BT) is a significant viral disease affecting ruminants, recently causing outbreaks in Tunisia during fall 2020, particularly in sheep and cattle.
  • Major eco-climatic factors analyzed include day and night land surface temperatures, normalized difference vegetation index (NDVI), and rainfall, with results indicating specific thresholds for these variables that correspond to increased BT cases.
  • The study emphasizes the need for an effective early warning surveillance program in high-risk areas, leveraging these identified eco-climatic risk factors to better predict BT outbreaks.

Article 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 . 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.

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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956234PMC
http://dx.doi.org/10.5455/OVJ.2022.v12.i1.14DOI Listing

Publication Analysis

Top Keywords

delegations tunisia
8
eco-climatic variables
8
variables associated
8
associated delegations
8
delegations reporting
8
land surface
8
surface temperatures
8
delegations
5
role eco-climatic
4
eco-climatic factors
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!