Iranian Journal of

  Background & Objectives : Leishmaniasis is a disease of the skin caused by a variety of protozoa. Leishmaniasis can be seen in any geographic region. This study investigated the role of climate on the prevalence of cutaneous leishmaniasis in the city of Sabzevar between 2003 and 2009.

  Methods : Daily meteorological data (minimum, maximum and mean temperature, sunshine hours, precipitation, and humidity) and city-level data on the prevalence of cutaneous leishmaniasis between 2003 and 2009 were prepared and analyzed using Pearson correlation, time delay, and time series methods.

  Results: The maximum incidence of the disease was observed during the second half of the year, especially in the autumn, in the age group 10 to 20 years. The highest incidence was seen among women and for the wet (rural) type. In addition, the disease showed a weak positive correlation with relative humidity and rainfall, and a weak inverse correlation with sunshine and temperature. It is noteworthy that in the delay analysis, correlations increased with a confidence interval of 95%. In the time delay of three months, the correlation of leishmaniasis incidence and prevalence with relative humidity and rainfall was positive and strong (r=0.82 and P=0.006, r=0.88 and P=0.002, respectively) and the correlation of the disease with temperature and sunshine hours was inverse and strong (r=0.80 and P=0.01, r=0.77 and P=0.01, respectively).

  Conclusion : Considering the significant relationship between climatic factors and leishmaniasis in desert regions, we recommend appropriate measures should be taken to identify and control these factors.

Background and Objectives: Spatial epidemiology is the description and analysis of geographic variations of diseases with respect to demographic, environmental, behavioral, socioeconomic, genetic, and infectious risk factors. Disease mapping includes a set of statistical techniques that lead to providing clean maps based on estimation of the incidence, prevalence and mortality rates for the users to enable them to reliably estimate the distribution of the diseases. In this study, the spatial epidemiology of diarrhea was evaluated in Mazandaran.

Methods: In the present study, statistical methods like the Moran’s I spatial autocorrelation, Anselin local Moran’s I, K function and Ripley index were used to evaluate 4924 cases between 1385-1390, based on certain factors detected in diarrheal diseases.

Results: The results of the global Moran index showed that this disease provided adherence to a cluster pattern in the province. The results of the K function also showed that apart from the western regions of the province, the diarrheal disease followed the above-mentioned cluster pattern. The results of Anselin local Moran and sensitive indicators revealed that the central region of the province, including the cities of Sari, Qaymshmhr, and Babol had the highest prevalence of the disease.

Conclusion: The results showed that the prevalence of syndrome diarrhea follows the pattern cluster and the use of spatial analysis methods in a specific geographic area is appropriate for programs to reduce health risks. And in epidemiological studies, analysis and risk assessment diarrhea syndrome are very important.