Spatiotemporal Anopheles Population Dynamics, Response to Climatic Conditions: The Case of Chabahar, South Baluchistan, Iran

Farajzadeh, M. and Halimi, M. and Ghavidel, Y. and Delavari, M. (2015) Spatiotemporal Anopheles Population Dynamics, Response to Climatic Conditions: The Case of Chabahar, South Baluchistan, Iran. Annals of Global Health, 81 (5). pp. 694-704.

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Background An understanding of the factors that affect the abundance of Anopheline species provides an opportunity to better understand the dynamics of malaria transmission in different regions. Chabahar, located south east of Iran, is the most malarious region in the country. Objective The main aim of this study was to quantify the spatiotemporal Anopheles population dynamics, response to climatic conditions in Chabahar. Methods Satellite-based and land-based climatic data were used as explanatory variables. Monthly caught mosquitoes in 6 village sites of Chabahar were used as dependent variable. The spatiotemporal associations were first investigated by inspection of scatter plots and single variable regression analysis. A multivariate linear regression model was developed to reveal the association between environmental variables and the monthly mosquito abundance at a 95 confidence level (P � 0.5). Findings Results indicated that Anopheles mosquitoes can be found all year in Chabahar with 2 significant seasonal peaks from March to June (primary peak) and September to November (secondary peak). Results of the present study showed that 0.77 of yearly mosquito abundance emerges in the thermal range of 24°C to 30°C and the humidity range of 0.70 to 0.80 in Chabahar. Conclusion According to the developed multivariate linear model, 0.88 of temporal variance of mosquito abundance, nighttime land surface temperature, and relative humidity of 15 Universal Time Coordinated (18.30 Iran) are the main drivers of mosquito population dynamics in Chabahar. © 2015 The Authors.

Item Type: Article
Additional Information: cited By 0
Uncontrolled Keywords: Anopheles; climate; dependent variable; driver; explanatory variable; human; human experiment; humidity; linear regression analysis; population dynamics; quantitative study; statistical model
Subjects: Environmental Science
Divisions: Faculty of Medicine > Basic Sciences > Department of Parasitological & Mycology
Depositing User: editor . 2
Date Deposited: 08 Mar 2017 14:13
Last Modified: 08 Mar 2017 14:13

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