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The aim of this study was to investigate the relationship between the environmental and metrological variables and cutaneous leishmaniasis (CL) transmission and its prediction in a region susceptible to this disease prevalence using a time series model. The accurate locations of 4437 CL diagnosed from 2011 to 2015 were obtained to be used in the time series model. Temperature, number of days with temperature over 30 °C, and number of earthquake were related to CL incidence using the Seasonal Auto-correlated Integrated Moving Average (SARIMA) model according to the Box-Jenkins method. In addition, the relationship between land use and surface soil type in 500- and 1000-m radius around the CL patients were investigated. The SARIMA models showed significant associations between environmental and meteorological variables and CL incidence adjusted for seasonality and auto-correlation. The result indicated that there are need more robust preventive programs in earthquake-prone areas with high temperature and inceptisol soil type than other areas. In addition, the region with these characteristics should be considered as high-risk areas for CL prevalence.

The aim of this study was to assess the health impacts related to particulate matter less than 10 μm (PM) exposure in the city of Yazd, Iran. For this aim, AirQ 2.2.3 software was used to model relationship between short-term exposure to PM and disease cases proposed by the World Health Organization (WHO). The annual mean concentration of PM was 97 μg/m. The maximum concentration value of PM was measured during the summer (731 μg/m). 4.988% (95%CI: 3.381-6.542%) of the total mortality, 7.3% (95%CI; 4.19-10.21%) of cardiovascular mortality, and 10.21% (95%CI; 4.19-14.89%) of respiratory mortality were related to the PM concentrations. Consequently, the AirQ software can provide valuable information about the importance of air pollution and the substantial impacts of PM on the society for policymakers.