Artikel ; Online: Assessing the impact of climate conditions on the distribution of mosquito species in Qatar.
2023 Band 10, Seite(n) 970694
Abstract: Qatar is a peninsular country with predominantly hot and humid weather, with 88% of the total population being immigrants. As such, it leaves the country liable to the introduction and dissemination of vector-borne diseases, in part due to the presence ... ...
| Abstract | Qatar is a peninsular country with predominantly hot and humid weather, with 88% of the total population being immigrants. As such, it leaves the country liable to the introduction and dissemination of vector-borne diseases, in part due to the presence of native arthropod vectors. Qatar's weather is expected to become warmer with the changing climatic conditions across the globe. Environmental factors such as humidity and temperature contribute to the breeding and distribution of different types of mosquito species in a given region. If proper and timely precautions are not taken, a high rate of particular mosquito species can result in the transmission of various vector-borne diseases. In this study, we analyzed the environmental impact on the probability of occurrence of different mosquito species collected from several different sites in Qatar. The Naive Bayes model was used to calculate the posterior probability for various mosquito species. Further, the resulting Naive Bayes predictions were used to define the favorable environmental circumstances for identified mosquito species. The findings of this study will help in the planning and implementation of an active surveillance system and preventive measures to curb the spread of mosquitoes in Qatar. |
|---|---|
| Mesh-Begriff(e) | Animals ; Mosquito Vectors ; Bayes Theorem ; Qatar ; Weather ; Culicidae ; Vector Borne Diseases |
| Sprache | Englisch |
| Erscheinungsdatum | 2023-01-16 |
| Erscheinungsland | Switzerland |
| Dokumenttyp | Journal Article ; Research Support, Non-U.S. Gov't |
| ZDB-ID | 2711781-9 |
| ISSN | 2296-2565 ; 2296-2565 |
| ISSN (online) | 2296-2565 |
| ISSN | 2296-2565 |
| DOI | 10.3389/fpubh.2022.970694 |
| Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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