Abstract

Cutaneous leishmaniasis (CL) is a prevalent debilitating disease in many countries, particularly in Iran, the Middle East, North Africa, and South America. Bam County is the most important highly endemic focus of anthropometric CL in Iran and has been under consideration by WHO. This study investigated the environmental and geographic factors affecting the occurrence and distribution of CL in this focus. Demographic data and the home addresses of CL patients diagnosed from 2015 to 2020 were retrieved from the Leishmaniasis Center of Bam in southeast Iran. The effects of mean annual rainfall (MAR), mean annual humidity (MAH), mean annual temperature (MAT), maximum annual temperature (MaxMAT), minimum annual temperature (MinMAT), mean annual humidity (MAH), mean annual evaporation (MAE), mean annual frosty days (MAFD), mean annual snowy hours (MASH), elevation, and land cover on the distribution of CL were analyzed using geographical information systems (GIS) and univariate and multivariate regression models. Of 847 patients studied, 50.9% (n = 431) were female and 49.1% (n = 416) were male. The age classes 0-10 (n = 246) and 11-20 (n = 145) showed the highest frequency of patients, respectively. Leishmaniasis patients were reported from 66 villages/cities (11.8%) out of 561 residential areas in Bam County. Univariate analysis showed that urban settings (OR = 21.66), agriculture (OR = 5.73), orchards (OR = 5), salty land (OR = 1.05), and temperatures (OR = 2.37, 2.79 and 3.47) had positive effects on CL occurrence (p < 0.05), while altitude, precipitation, humidity, evaporation, and the number of frozen days had negative effects. Multivariate analysis identified urban settings (OR = 13.6), orchards (OR = 6.29), agriculture (OR = 5.82), and minimum temperature (OR = 2.38) as the most significant determinants of CL occurrence in this region. Environmental and ecological factors play an important role in the distribution of CL in Bam County. The high-risk zones for CL are cities/large villages, agricultural and orchard areas in lower altitudes and with warmer climates and lower rainfall and humidity. This model can guide researchers and health managers to properly conduct CL control programs and allocate budgets.

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