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K Azam , A Gerami , K Mohammad , A Kazemnejad ,
Volume 2, Issue 1 (4-2004)
Abstract

In large–scale sampling opeartions (e.g. nation-wide health surveys) we always face the problem of non-response item(s) and/or non-response unit(s). In fitting a model to the data we have two groups of variables, namely dependent and independent variables. Non-response may occur for any of these groups of variables. In this paper we assume Y as a categorical dependent variable with three levels, Z and X as independent variables from any kind: scale, categorical, ordinal, etc. We have complete data on the first two variables and we assume that the missing items follow a random pattern (MAR). Then a model is devised based on the likelihood function for the whole data set (including missing values) and estimates of parameters are compared with those obtained by statistical programs such as SPSS, which are only based on completely observed data and ignore units with missing data. Our results show that the likelihood-based model is superior to the standard approach utilized by the software packages. The comparison is made using data on thyriod disease (goiter) obtained by a health survey in Gazvin province.


V Mazaheri, K Holakouie Naieni, S Simani, M Yunesian, A Fayaz , E Mostafavi, P Biglari,
Volume 8, Issue 3 (9-2010)
Abstract

Background and Aim: Rabies, a viral and zoonotic disease, causes acute and fetal encephalitis in humans and other mammals and is a cause of death in developing countries. It is usually transmitted by animal bite, but other routes of transmission are mucus membranes, breathing, placenta, contaminated instruments, and organ implanting. This study shows the mapping of geographical distribution of animal bite cases, rabies, and death due rabies in 3 Caspian Sea littoral provinces, namely, Golestan, Mazandaran, and Gilan.

Materials and Methods: Data on human and animal rabies cases and animal bites were collected from the Reference Rabies Center of the Pasteur Institute in Tehran and the Rabies Diagnosis Section of the Amol Research Center during 2002-2007.The data was analyzed by the SPSS (11.5) software and mapping was done by Arc GIS 9.2.

Results: During the 6-year period, of the 670,743 animal bite cases reported in Iran 63890 (9.5%) had occurred in Golestan, 25,767 (3.8%) in Mazandaran, and 22,874 (3.4%) in Gilan. The distribution of animal bite cases in the 3 provinces was as follows: Agh ghala, Bandar Torkaman, Azad shahr and Kolaleh in Golestan Galugah, Behshahr, Ramsar and Neka in Mazandaran and Shaft, Masal, Siahkal and Fuman in Gilan. The data also showed that of the total 2,312 animal rabies cases, in Iran, 9.22% had been reported from Golestan, 4% from Mazandaran, and 2.6% from Gilan. Furthermore, animal rabies cases had occurred mostly in Gonbadekavoos, Bandar Torkaman, Gorgan and Kolaleh in the Golestan Province Behshahr, Neka and Chalus in the Mazandaran Province and Masal, Fuman and Rezvanshahr in the Gilan Province. The most important disease vector (91.3%) for both human and animal rabies was the dog. A total of 41 human deaths due to rabies had been reported during the period, 2 being from Mazandaran.

Conclusion: The results show that a more effective disease control and surveillance system is essential and can help improve planning for service provision in the health care centers.


Mansour Halimi, Mehdi Delavari, Ashraf Takhtardeshir,
Volume 10, Issue 3 (1-2013)
Abstract

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).


Iman Hatami, Narges Khanjani, Mohsen Aliakbarpoor, Azizallah Dehghan,
Volume 16, Issue 1 (6-2018)
Abstract

Background and Aim: Considering the importance of cutaneous leishmaniasis in Iran, this study was conducted to present the epidemiological characteristics of patients with cutaneous leishmaniasis, the time trend and the mapping of the disease in the cities under the supervision of Shiraz University of Medical Sciences.

Materials and Methods: Data was collected from the Heath deputy of Shiraz University of Medical Sciences and Health Centers of cities from 2005 to 2014; and was analyzed using Excel and SPSS19 software. Chi square test and Poisson regression were used for analysis.

Results: The incidence of the disease increased from 109 cases per 100,000 in 2005 to 218 in 2008 and decreased to 110 in 2014. The 0-9 age group was the most vulnerable and housewives were the most involved occupational group. Most people had a wet wound. The hands were the most affected. The highest incidence of disease was in the autumn. Zoonotic Cutaneous Leishmaniasis (ZCL) was the dominant type. Cutaneous leishmaniasis was more in northern than southern regions of the province in the recent years.

Conclusion: In the last years of the study, unlike in the early years, the incidence of disease in the northern region of the province was more than the southern regions. This finding could be a warning signal that the disease could be relocating and spreading in areas where the disease was not endemic before.


Saeed Motesadi Zarandi, Rasul Nasiri, Mohammad Esmaeil Motlagh,
Volume 19, Issue 1 (6-2021)
Abstract

Background and Aim: High concentrations of particulate matter-25 (PM2.5) have been the cause of the unhealthiest days in Tehran, Iran in recent years. This study was conducted with the aim of the spatio-temporal analysis of traffic volume and its relationship with PM2.5 pollutant concentrations in Tehran metropolis, Tehran during 2015-2018, using the Geographic Information System (GIS).
Materials and Methods: In this study in different regions of Tehran, the Inverse Distance Weighting (IDW) model was used for prediction and zoning of the PM2.5 concentrations and traffic volume during the period 2015-2018. In addition, the association between the PM2.5 concentrations and traffic volume was determined based on the Geographically Weighted Regression (GWR) model.
Results: The findings showed that the southern and southwestern regions of Tehran had the highest PM2.5 pollutant concentration (annual average more than 40 μg/m3), while the eastern and northern regions had the highest traffic volume. In addition, based on the GWR model, the eastern regions were found to have the highest local R2 values (between 0.36 and 0.70).
Conclusion: In most regions of Tehran, no strong association can be found between high concentrations of PM2.5 and traffic volume. However, based on the findings of this study we cannot reject the relationship between traffic volume and PM2.5 pollutant but postulate other sources to be the main reason for the high concentrations of PM2.5. Thus, in the first step, these sources should be identified, followed by adopting strategies for traffic volume control and reduction aiming at having a cleaner air in Tehran.

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