Journal of School of Public Health and

Background and aim:  Malaria as a mosquito-borne disease is largely dependent on climatic conditions. Temperature, rainfall and relative humidity are considered as climatic factors affecting the geographical distribution of this disease. These climatic factors have definite roles not only in the growth and proliferation of the mosquito Anopheles but also in the parasite Plasmodium activity. The purpose of this study was to find in which regions of Iran climatic conditions favour spread of malaria.

Material and Methods: Data on 3 climatic factors, including the mean monthly temperature, rainfall and mixed ratio of humidity, obtained from 31 synoptic meteorological stations during the 30-year period 1975-2005 were used. By running the informative filters through map algebra tools in the Geographical Information System (GIS), the synoptic meteorological stations were classified into 4 groups in terms of climatic conditions favouring activity and proliferation of the mosquito Anopheles and the parasite Plasmodium. Then the regions were interpolated in terms of climate risk of malaria incidence using the tension Spiline interpolation method.

Results: The maps of climatic potential malaria risk indicated that the southern provinces including Hormozgan, Bushehr and Khuzestan, southern parts of Sistan-Balouchistan province, such as Chabahar and Nikshahr, as well as Northern provinces of the country, including Mazandaran and Gilan, have the highest climatic potential for risk of malaria spread. On the other hand, provinces in the North Western region, including West and East Azarbaijan, Ardebil, Kurdistan and Zanjan, have the lowest climatic potential risk of malaria spread. Further analysis of the data showed that a large segment of the population is living in regions with medium- to high-risk zones.

Conclusion: The findings of this study can be used when designing malaria control programs to identify different regions in terms of climate-based malaria risk. The presented risk map of malaria in this study is completely based on climatic factors. The disconformity between these presented climate-based maps and the observed high-risk map is due to such factors as socioeconomic and lifestyle changes, as well as border problems (foreign subjects entering the country).

  Background and Aim: Environmental and ecological factors especially climatic conditions have a significant impact on the prevalence of parasitic diseases. These factors has is more importance in Malaria Incidence and Epidemiology. Malaria as the most important parasitic disease, considered as one of most important public health problem. The climatic factors not only affect the growth and proliferation of the Anopheles mosquito but also affect in Plasmodium activity . In present study we surveyed the malaria situation during 1972 to 2005. In order to the five climatic parameters including mean temperature, total precipitation, number of days with precipitation over 0mm, rainfall distribution index and relative humidity were used as annual average during 1971 to 2005.

  Materials and Methods : we calculate average of annual of climatic parameters for the 31 synoptic stations of Iran Using GIS software. First, using the ordinary Kriging model with spherical a Semi variogram was traced maps of climatic parameters and these factors mean was calculated for each year . Finally, to investigate the relationship between climatic parameters with the prevalence index the Pearson correlation coefficient at 0.9 confidence level (p = 0.10) . was used. A multivariate linear regression model was applied to estimate the prevalence of disease based on the mentioned climatic factors .

  Results : Study of malaria prevalence in 1971 to 2005 showed cases of disease with has a decreasing trend with slope 0.0142 in year that this trend has been accelerated from 1375 . Many cases of disease have been reported one year after increased precipitation . The result showed the weather humidity factors is important than temperature factors in the prevalence of malaria . I general, the developed model is explained 0.48 of changes prevalence time.

  Conclusion: In order to be successful Anti-malaria campaign in Malaria-prone areas in addition different influencing factors climatic factors should be considered .

Background and Aims: Cutaneous leishmaniosis (CL) is a neglected tropical vector-borne disease. As other vector-transmitted diseases, its transmission is sensitive to the physical environment. The purpose of this study was to investigate the relationship between El Niño-Southern Oscillation (ENSO) and annual incidence of CL in Iran.

Materials and Methods: The data of ENSO were obtained from the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center for the period 1977-2011(34 years), and the annual data on CL incidence in Iran from WHO. To determine the association between the ENSO annual fluctuations and annual CL incidence we used crosstab analysis and tow-tailed independent t-test to find any possible differences among the annual CL incidence according to different phases of the Southern Oscillation Index (SOI: El Niño, warming phase; La Niña, cooling phase; neutral phase).

Results: Analysis of the data showed that, as compared with the years when El Niño and La Niña were dominant, the annual incidence of CL in Iran was lower in the years when neutral phases of SOI were dominant. The highest incidence was found to have occurred during the years with an intermediate La Niña dominance. During the years when La Nina was dominant the incidence of CL was, on the average, 15-20% higher than that in the years with a neutral phase, while the difference between the annual CL incidence in neutral years and El Niño years was not statistically significant.

Conclusion: The findings reveal that in general the mean incidence of cutaneous leishmaniosis during the years with a neutral ENSO index is lower than that during the years with dominant El Nino or La Nina, although there is no difference between incidence in the neutral years and the El Nino-dominant years.