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.
|Original language||English (US)|
|Journal||Frontiers in Public Health|
|State||Published - Jan 16 2023|
Bibliographical noteKAUST Repository Item: Exported on 2023-02-22
Acknowledgements: This publication was made possible by NPRP-Standard (NPRP-S) Twelfth (12th) Cycle grant NPRP12S-0212-190073 from the Qatar National Research Fund (a member of Qatar Foundation). DB and EF benefit from an NPRP grant (NPRP12S-0310-190284) from the QNRF. The findings herein reflect the work and are solely the responsibility of the authors. We express our gratitude and appreciation to MoPH for the support with staff and funding of the field studies. We also thank the Friends of Environment Center for their support in sample collection, as well as colleagues of Doha and Al Rayyan pest control units for assisting in the fieldwork.