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Modeling of Environmental Factors Affecting the Prevalence of Zoonotic and Anthroponotic Cutaneous, and Zoonotic Visceral Leishmaniasis in Foci of Iran: A Remote Sensing and Gis Based Study



Golpayegani AA1, 2, 3 ; Moslem AR4 ; Akhavan AA1, 5 ; Zeydabadi A1, 2 ; Mahvi AH1, 3, 6 ; Allahabadi A7
Authors
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Authors Affiliations
  1. 1. School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Bam University of Medical Sciences, Bam, Iran
  3. 3. National Institute of Health Research, Ministry of Health, Tehran, Iran
  4. 4. Sabzevar University of Medical Sciences, Sabzevar, Iran
  5. 5. Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Center for Solid Waste Research, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran
  7. 7. Leishmaniasis Research Center, Sabzevar University of Medical Sciences, Sabzevar, Iran

Source: Journal of Arthropod-Borne Diseases Published:2018

Abstract

Background: Leishmaniasis is a re-emerging serious international public health problem, and both visceral and cu-taneous types of leishmaniasis became important endemic diseases in Iran. In this study, the relationships between environmental factors (vegetation and elevation) and the prevalence of diseases have been investigated. Methods: All international and national online databases were searched by terms such as leishmaniasis, incidence, prevalence and other related words attributed to Iran and published until first quarter of 2015. The developed database in Excel, later imported to the ArcMap for spatial analyst and mapping. Afterwards, the software was used for modeling the relationship between the prevalence/incidence and environmental variables (vegetation and elevation) by both linear and nonlinear regression. Results: After mapping the prevalence data from 144 studies, considering non-parametric ANOVA, the tendency of zoonotic visceral leishmaniasis to presence in high elevation and high vegetation was more than Anthroponotic and zoonotic cutaneous leishmaniasis. While linear regression showed weaker results for modeling, however, additive nonparametric regression analysis suggested that 10km buffers for elevation, and 10 as well as 50km buffers for veg-etation could contribute in better fitness in modeling of these variables. Conclusion: The detailed maps for distribution of disease concluded. The nonlinear regression is a reliable predictor of the relationship between environmental factors and disease incidence, although more and wide researchers are needed to confirm it. © 2018 Tehran University of Medical Sciences.
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