Volume 17, Issue 1 (Vol 17,No.1, Spring 2021 2021)                   irje 2021, 17(1): 21-33 | Back to browse issues page

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Javanbakht M, Argani M, Ezimand K, Saghafipour A. Modeling Spatial-Temporal Variations of Cutaneous Leishmaniasis Incidence in Southern, Razavi and Northern Khorasan Provinces Based on Environmental and Ecological Criteria in Northeast Iran Mohammad Javanbakht1 , Maysam Argany2 , Kayvan Ezimand. irje 2021; 17 (1) :21-33
URL: http://irje.tums.ac.ir/article-1-6927-en.html
Modeling Spatial-Temporal Variations of Cutaneous Leishmaniasis Incidence in Southern, Razavi and Northern Khorasan Provinces Based on Environmental and Ecological Criteria in Northeast Iran Mohammad Javanbakht1 , Maysam Argany2 , Kayvan Ezimand
M Javanbakht1 , M Argani * 2, K Ezimand3 , A Saghafipour4
1- hD Student in Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran
2- Assistant Professor Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran , argany@ut.ac.ir
3- PhD Student in Remote Sensing and GIS, Faculty of Earth Science, University of Shahid Beheshti, Tehran, Iran
4- Assistant Professor, Department of Public Health, Faculty of Public Health, Qom University of Medical Sciences, Qom, Iran
Abstract:   (2640 Views)
 
Background and Objectives: Environmental conditions in different geographical areas provide a basis for the spread of some diseases. Cutaneous leishmaniasis is a serious threat to public health and is one of the arthropod-borne diseases. The prevalence and distribution of this disease is affected by environmental and climatic factors. The aim of this study was to model the Spatio-temporal variations in the incidence rate of this disease based on environmental and ecological criteria.
 
Methods: The northeast of Iran was selected as the study area. The data used in this study included vegetation, surface temperature, precipitation, evapotranspiration, soil moisture, digital elevation model and sunny hours. The artificial neural network method was used to model the spatio-temporal changes of cutaneous leishmaniasis.
 
Results: Spatial variations in the incidence of the disease had a north-south trend and decreased from north to south. In addition, two foci were identified in the medium altitude areas in North and South Khorasan provinces. Temporal variations in the incidence of disease in the study period showed that the incidence rate decreased in the two identified foci from 2011 to 2016.
 
Conclusion: The modeling results showed that the estimated regression coefficient was 0.92 for neural network based on all three types of data (training, validation, test) indicating good quality of constructed neural network.  In addition, sensitivity analysis results showed that sunny hours and soil moisture were the most important factors in the model function.
Keywords: Cutaneous leishmaniasis, Environmental and ecological criteria, Artificial neural network, Sensitivity analysis
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Type of Study: Research | Subject: Epidemiology
Received: 2021/08/20 | Accepted: 2021/05/31 | Published: 2021/05/31
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