Geographical distribution of Anthrax using Geographic Information System (GIS) during 2010-2015 in Iran.

Background: Anthrax is a zoonotic infectious disease that is still considered as a health problem in developing countries. Therefore, the aim of this study was to investigate the incidence and geographical distribution of anthrax using the Geographic Information System (GIS) and predict its incidence in Iran in 2021. Methods: This study is descriptive analytical study. Information on anthrax was obtained from the Center for Communicable Diseases Control during 2010-2015. In the next step, ArcGIS 9.3 was used to prepare geographic maps of the disease incidence and frequency. Therefore, using the Raster Calculator tool, the disease prediction map was drawn. Results: The highest incidence of anthrax during 2010-2015 was observed in the provinces of Kurdistan, North Khorasan, and Chaharmahal and Bakhtiari, respectively. The trend of the incidence of anthrax in Iran had increased from 2010 to 2013, while its incidence decreased in 2014. Based on the results of modeling in Iran, the provinces of Kurdistan, West Azarbaijan, Tehran, and Zanjan, respectively, with 37.16%, 33.83%, 16.78%, and 10.49% of their area (km2) had the highest risk of anthrax disease in the country in the year 2021. Conclusion: Since the provinces of Kurdistan, West Azerbaijan, Tehran, and Zanjan are among the high-risk areas in the country in the coming years, the cooperation between the veterinary organization and the health care system and the vaccination of livestock in these areas can significantly help to control and prevent the disease.

Epidemiology incidence and geographical distribution of leptospirosis using GIS and its incidence prediction in Iran in 2021.

Background: Leptospirosis is known as a public health problem in developing and developed countries. The aim of this study was to investigate the incidence and geographical distribution of leptospirosis using the Geographic Information System (GIS) and to predict its incidence in Iran in 2021. Methods: This was a descriptive analytical study. Information on leptospirosis was obtained from the Center for Communicable Diseases Control during 2009-2015. In the next step, The ArcGIS 9.3 was used to prepare geographic maps of the disease incidence and frequency. Therefore, using the Raster Calculator tool, the disease prediction map was drawn. Results: The results showed that the highest incidence of leptospirosis during 2009-2015 was observed in Gilan, Mazandaran, and Golestan provinces, respectively. The incidence of the disease had an increasing trend from 2013 to 2015. Based on the results of the modeling in Iran, the provinces of Gilan, Mazandaran, and Golestan, with 72.18%, 8.54%, and 4.95% of their area, respectively, have the largest areas at a high-risk for leptospirosis in the coming years. Conclusion: The prevalence of leptospirosis is affected by geographical and climatic conditions of every region; thus, the incidence of the disease is higher in the provinces located at the Caspian coastal side and in some regions in Semnan province. Hence, if health authorities pay more attention to developing health plans to prevent the disease, the risk of disease in these areas will be reduced in the future.

Assessment and prediction of road accident injuries trend using time-series models in Kurdistan.

BACKGROUND: Road traffic accidents are commonly encountered incidents that can cause high-intensity injuries to the victims and have direct impacts on the members of the society. Iran has one of the highest incident rates of road traffic accidents. The objective of this study was to model the patterns of road traffic accidents leading to injury in Kurdistan province, Iran. METHODS: A time-series analysis was conducted to characterize and predict the frequency of road traffic accidents that lead to injury in Kurdistan province. The injuries were categorized into three separate groups which were related to the car occupants, motorcyclists and pedestrian road traffic accident injuries. The Box-Jenkins time-series analysis was used to model the injury observations applying autoregressive integrated moving average (ARIMA) and seasonal autoregressive integrated moving average (SARIMA) from March 2009 to February 2015 and to predict the accidents up to 24 months later (February 2017). The analysis was carried out using R-3.4.2 statistical software package. RESULTS: A total of 5199 pedestrians, 9015 motorcyclists, and 28,906 car occupants' accidents were observed. The mean (SD) number of car occupant, motorcyclist and pedestrian accident injuries observed were 401.01 (SD 32.78), 123.70 (SD 30.18) and 71.19 (SD 17.92) per year, respectively. The best models for the pattern of car occupant, motorcyclist, and pedestrian injuries were the ARIMA (1, 0, 0), SARIMA (1, 0, 2) (1, 0, 0)12, and SARIMA (1, 1, 1) (0, 0, 1)12, respectively. The motorcyclist and pedestrian injuries showed a seasonal pattern and the peak was during summer (August). The minimum frequency for the motorcyclist and pedestrian injuries were observed during the late autumn and early winter (December and January). CONCLUSION: Our findings revealed that the observed motorcyclist and pedestrian injuries had a seasonal pattern that was explained by air temperature changes overtime. These findings call the need for close monitoring of the accidents during the high-risk periods in order to control and decrease the rate of the injuries.

Application of accelerated failure time models for breast cancer patients' survival in Kurdistan Province of Iran.

CONTEXT: Breast cancer is the most common cancer and the second common cause of cancer-induced mortalities in Iranian women. There has been a rapid development in hazard models and survival analysis in the last decade. AIMS: The aim of this study was to evaluate the prognostic factors of overall survival (OS) in breast cancer patients using accelerated failure time models (AFT). SETTING AND DESIGN: This was a retrospective-analytic cohort study. SUBJECTS AND MATERIALS: About 313 women with a pathologically proven diagnosis of breast cancer who had been treated during a 7-year period (since January 2006 until March 2014) in Sanandaj City, Kurdistan Province of Iran were recruited. STATISTICAL ANALYSIS USED: Performance among AFT was assessed using the goodness of fit methods. Discrimination among the exponential, Weibull, generalized gamma, log-logistic, and log-normal distributions was done using Akaik information criteria and maximum likelihood. RESULTS: The 5 years OS was 75% (95% CI = 74.57-75.43). The main results in terms of survival were found for the different categories of the clinical stage covariate, tumor metastasis, and relapse of cancer. Survival time in breast cancer patients without tumor metastasis and relapse were 4, 2-fold longer than other patients with metastasis and relapse, respectively. CONCLUSION: One of the most important undermining prognostic factors in breast cancer is metastasis; hence, knowledge of the mechanisms of metastasis is necessary to prevent it so occurrence and treatment of metastatic breast cancer and ultimately extend the lifetime of patients.

Correlation Assessment of Climate and Geographic Distribution of Tuberculosis Using Geographical Information System (GIS).

BACKGROUND: Tuberculosis (TB) spread pattern is influenced by geographic and social factors. Nowadays Geographic Information System (GIS) is one of the most important epidemiological instrumentation identifying high-risk population groups and geographic areas of TB. The aim of this study was to determine the correlation between climate and geographic distribution of TB in Khuzestan Province using GIS during 2005-2012. METHODS: Through an ecological study, all 6363 patients with definite diagnosis of TB from 2005 until the end of September 2012 in Khuzestan Province, southern Iran were diagnosed. Data were recorded using TB- Register software. Tuberculosis incidence based on the climate and the average of annual rain was evaluated using GIS. Data were analyzed through SPSS software. Independent t-test, ANOVA, Linear regression, Pearson and Eta correlation coefficient with a significance level of less than 5% were used for the statistical analysis. RESULTS: The TB incidence was different in various geographic conditions. The highest mean of TB cumulative incidence rate was observed in extra dry areas (P= 0.017). There was a significant inverse correlation between annual rain rate and TB incidence rate (R= -0.45, P= 0.001). The lowest TB incidence rate (0-100 cases per 100,000) was in areas with the average of annual rain more than 1000 mm (P= 0.003). CONCLUSION: The risk of TB has a strong relationship with climate and the average of annual rain, so that the risk of TB in areas with low annual rainfall and extra dry climate is more than other regions. Services and special cares to high-risk regions of TB are recommended.

Predictive factors of survival time of breast cancer in kurdistan province of Iran between 2006-2014: a cox regression approach.

BACKGROUND: Breast cancer is the most common cancer and the second most common cause of cancer-induced mortalities in Iranian women, following gastric carcinoma. The survival of these patients depends on several factors, which are very important to identify in order to understand the natural history of the disease. MATERIALS AND METHODS: In this retrospective study, 313 consecutive women with pathologically-proven diagnosis of breast cancer who had been treated during a seven-year period (January 2006 until March 2014) at Towhid hospital, Sanandaj city, Kurdistan province of Iran, were recruited. The Kaplan-Meier method was used for data analysis, and finally those factors that showed significant association on univariate analysis were entered in a Cox regression model. RESULTS: the mean age of patients was 46.10±10.81 years. Based on Kaplan-Meier method median of survival time was 81 months and 5 year survival rate was 75%±0.43. Tumor metastasis (HR=9.06, p=0.0001), relapse (HR=3.20, p=0.001), clinical stage of cancer (HR=2.30, p=0.03) and place of metastasis (p=0.0001) had significant associations with the survival rate variation. Patients with tumor metastasis had the lowest five-year survival rate (37%)and among them patients who had brain metastasis were in the worst condition (5 year survival rate= 11%±0.10). CONCLUSIONS: Our findings support the observation that those women with higher stages of breast malignancies (especially with metastatic cancer) have less chance of surviving the disease. Furthermore, screening programs and early detection of breast cancer may help to increase the survival of those women who are at risk of breast cancer.