ﻣﺪلﺳﺎزي ﺗﻐﯿﯿﺮات ﻣﮑﺎﻧﯽ-زﻣﺎﻧﯽ ﺑﺮوز ﻟﯿﺸﻤﺎﻧﯿﻮز ﺟﻠﺪي در اﺳﺘﺎنﻫﺎي ﺧﺮاﺳﺎن ﺟﻨﻮﺑﯽ، رﺿﻮي و ﺷﻤﺎﻟﯽ در ﺷﻤﺎل ﺷﺮق اﯾﺮان ﺑﺮاﺳﺎس ﻣﻌﯿﺎرﻫﺎي ﻣﺤﯿﻄﯽ و اﮐﻮﻟﻮژﯾﮏ

Modeling Spatial-Temporal Variations of Cutaneous Leishmaniasis Incidence in Southern, Razavi and Northern Khorasan Provinces Based on Environmental and Ecological Criteria in Northeast Iran

ﻣﻘﺪﻣﻪ و اﻫﺪاف: ﺷﺮاﯾﻂ ﻣﺤﯿﻄﯽ در ﻣﻨﺎﻃﻖ ﻣﺨﺘﻠﻒ ﺟﻐﺮاﻓﯿﺎﯾﯽ زﻣﯿﻨﻪ را ﺑﺮاي ﺷﯿﻮع ﺑﺮﺧﯽ از ﺑﯿﻤﺎريﻫﺎ ﻓﺮاﻫﻢ ﻣﯽﮐﻨﺪ. ﻟﯿﺸﻤﺎﻧﯿﻮز ﺟﻠـﺪي ﯾﮏ ﺗﻬﺪﯾﺪ ﺟﺪي ﺑﺮاي ﺳﻼﻣﺖ ﻋﻤﻮﻣﯽ ﺟﺎﻣﻌﻪ ﻣﺤﺴﻮب ﻣﯽﺷﻮد و در زﻣﺮه ﺑﯿﻤﺎريﻫﺎي ﻫﻤﻪﮔﯿﺮ ﻣﻨﺘﻘﻠﻪ ﺑﻪوﺳﯿﻠﻪ ﺑﻨـﺪﭘﺎﯾﺎن اﺳـﺖ. ﺷـﯿﻮع و ﺗﻮزﯾﻊ اﯾﻦ ﺑﯿﻤﺎري ﺗﺤﺖ ﺗﺄﺛﯿﺮ ﻋﻮاﻣﻞ ﻣﺤﯿﻄﯽ و اﻗﻠﯿﻤﯽ ﻗﺮار دارد. ﻣﻄﺎﻟﻌﻪ ﺣﺎﺿﺮ ﺑﺎﻫﺪف ﻣﺪلﺳﺎزي ﺗﻐﯿﯿﺮات ﻣﮑﺎﻧﯽ زﻣﺎﻧﯽ ﺑﺮوز اﯾﻦ ﺑﯿﻤـﺎري ﺑﺮاﺳﺎس ﻣﻌﯿﺎرﻫﺎي ﻣﺤﯿﻄﯽ و اﮐﻮﻟﻮژﯾﮏ اﻧﺠﺎمﺷﺪه اﺳﺖ. روش ﮐﺎر: ﺷﻤﺎل ﺷﺮق اﯾﺮان ﺑﻪﻋﻨﻮان ﻣﻨﻄﻘﻪ ﻣﻮردﻣﻄﺎﻟﻌﻪ اﻧﺘﺨﺎب ﺷﺪ. دادهﻫﺎي ﻣﻮرداﺳﺘﻔﺎده در اﯾﻦ ﺗﺤﻘﯿﻖ ﺷﺎﻣﻞ ﭘﻮﺷﺶ ﮔﯿﺎﻫﯽ، دﻣـﺎي ﺳﻄﺢ، ﺑﺎرش، ﺗﺒﺨﯿﺮ و ﺗﻌﺮق، رﻃﻮﺑﺖ ﺧﺎك، ﻣﺪل رﻗﻮﻣﯽ ارﺗﻔﺎع و ﺗﻌﺪاد ﺳﺎﻋﺎت آﻓﺘﺎﺑﯽ ﺑﻮدﻧﺪ. ﺑـﺮاي ﻣﺪلﺳـﺎزي ﺗﻐﯿﯿـﺮات زﻣـﺎﻧﯽ و ﻣﮑـﺎﻧﯽ ﻟﯿﺸﻤﺎﻧﯿﻮز ﺟﻠﺪي از روش ﺷﺒﮑﻪ ﻋﺼﺒﯽ ﻣﺼﻨﻮﻋﯽ اﺳﺘﻔﺎده ﮔﺮدﯾﺪ. ﯾﺎﻓﺘﻪﻫﺎ: ﺗﻐﯿﯿﺮات ﻣﮑﺎﻧﯽ ﺑﺮوز اﯾﻦ ﺑﯿﻤﺎري روﻧﺪي ﺷﻤﺎﻟﯽ- ﺟﻨﻮﺑﯽ دارد و از ﺷﻤﺎل ﺑﻪ ﺟﻨﻮب ﮐﺎﻫﺶ ﻣﯽﯾﺎﺑﺪ. ﻫﻤﭽﻨﯿﻦ دو ﮐﺎﻧﻮن در ﻣﻨﺎﻃﻖ ﺑﺎ ارﺗﻔﺎع ﻣﺘﻮﺳﻂ در دو اﺳﺘﺎن ﺧﺮاﺳﺎن ﺷﻤﺎﻟﯽ و ﺟﻨﻮﺑﯽ ﺷﻨﺎﺳﺎﯾﯽ ﺷﺪ. ﺗﻐﯿﯿﺮات زﻣﺎﻧﯽ ﺑﺮوز ﺑﯿﻤـﺎري در ﻃـﯽ دوره ﻧﺸـﺎن داد ﮐـﻪ از ﺳـﺎل 1390 ﺗﺎ 1395 ﺑﺮوز در دو ﮐﺎﻧﻮن ﺷﻨﺎﺳﺎﯾﯽﺷﺪه ﺳﯿﺮ ﻧﺰوﻟﯽ داﺷﺘﻪ اﺳﺖ. ﻧﺘﯿﺠﻪﮔﯿﺮي: ﺑﺮ اﺳﺎس ﻧﺘﺎﯾﺞ ﻣﺪلﺳﺎزي ﻣﻘﺪار ﺿﺮﯾﺐ رﮔﺮﺳﯿﻮن ﺑﺮاي ﻣﺪل ﺷﺒﮑﻪ ﻋﺼﺒﯽ ﺳﺎﺧﺘﻪﺷﺪه ﺑﺮ ﻣﺒﻨﺎي ﻫﺮ ﺳﻪ ﻧـﻮع داده آﻣـﻮزش، اﻋﺘﺒﺎر ﺳﻨﺠﯽ، آزﻣﻮن 0/92 ﺑﻮد ﮐﻪ ﻧﺸﺎندﻫﻨﺪه ﮐﯿﻔﯿﺖ ﻣﻨﺎﺳﺐ ﻣﺪل ﺷﺒﮑﻪ ﻋﺼﺒﯽ ﺳﺎﺧﺘﻪﺷﺪه اﺳﺖ. ﻫﻤﭽﻨﯿﻦ ﻧﺘﺎﯾﺞ آﻧﺎﻟﯿﺰ ﺣﺴﺎﺳﯿﺖ ﻧﺸﺎن داد ﮐﻪ ﺳﺎﻋﺎت آﻓﺘﺎﺑﯽ و رﻃﻮﺑﺖ ﺧﺎك ﺑﺎﻻﺗﺮﯾﻦ ﺗﺄﺛﯿﺮ در ﺗﺎﺑﻊ ﻣﺪل را داﺷﺘﻪ اﺳﺖ.

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 arthropodborne 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.