isfahan province
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Background: Pediatric-onset multiple sclerosis (POMS) is an autoimmune demyelinating disorder of the central nervous system (CNS), affecting individuals younger than 18 years of age. We sought to characterize the epidemiological and clinical features of patients with POMS in Isfahan, Iran, from April 1997 to March 2020. Methods: The medical records of patients with POMS in the databases of Isfahan Department of Public Health and Isfahan Multiple Sclerosis Society (IMSS) were retrospectively reviewed. The 2006 and 2016 Isfahan Province population censuses were used as reference values for assessing the temporal trend of POMS. Results: From April 1997 to March 2020, 509 individuals under18 years of age were diagnosed with POMS in Isfahan. 404 of these patients (79.4%) were girls, and 105 patients (20.6%) were boys (a female to male ratio of 3.85:1). Most of the patients (83%) were monosymptomatic at onset, with optic neuritis and brainstem-cerebellar disorders being the most frequent initial presentations. Mean ± standard deviation (SD) of age at disease diagnosis was 15.8 ± 2.5 years (ranging from 3 to 18, mode = 18).From April 2019 to March 2020, the crude prevalence and the crude incidence rate of the POMS were  5.42 per 100000 and 1.86 per 100000, respectively. Poisson regression analysis revealed a 3.4% increase in the incidence rate of POMS from April 1997 to March 2020 [relative rate:1.034, 95% confidence interval (CI): 1.021-1.048]. Conclusion: The female to male ratio in our cohort was significantly higher than any other studies conducted previously. The high female to male ratio and increasing incidence of the disease suggest increasing regionalization of care.

Background: We aimed to evaluate the effect of COVID-19 vaccines in preventing infection, hospitalization, and mortality due to COVID-19 in Isfahan Province, Iran. Methods: Following a retrospective cohort design, data of all vaccinated individuals since the rollout of vaccination of the general population are analyzed, Mar 2020 to Aug 13, 2021. Moreover, the data of all non-vaccinated people were collected by the census method for this period. The two groups were compared concerning hospitalization and mortality using the Chi-square test. Kaplan-Meyer was also used to calculate the median interval between receiving a vaccine and outcome (hospitalization and death). Results: Overall, 583434 people have received a second dose of a vaccine from Mar 2020 to Aug 2021, which 74% (n=433403) was Sinopharm, 18.2% (n=106027) AstraZeneca, 3.6% (n=21216) Sputnik, and 3.9% (n=22,788) Barekat. In contrast, 2,551,140 people living in the Isfahan Province did not receive a vaccine. The median interval between injection of the first dose and the hospitalization for those who received Sinopharm, AstraZeneca, Sputnik, and Barekat was 22, 61, 19, and 19 days, respectively. For unvaccinated cases, the rates of infection, hospitalization, and mortality (per 1000 population) were 69.7, 12.1, and 1.04, respectively. In contrast, for vaccinated individuals, these rates were 3.9, 1.08, and 0.09, two weeks after the second dose, respectively. Conclusion: The highest and lowest reduction in relative risk was for those who received AstraZeneca and Sputnik, respectively.  

The purpose of this paper is to investigate the corporate social responsibility (CSR) and organizational commitment (OC) in agricultural cooperatives of Iran. The study’s research model is tested through a survey consulting 260 respondents. The method of data collection is using the standard questionnaire of corporate social responsibility (CSR) based on the Carol model and organizational commitment (OC) based on the Allen-Meyer model. Data validity was confirmed by Bartlett test and KMO coefficient and its reliability was confirmed by Cronbach’s alpha. The statistical population of this study was the agricultural cooperatives with managed by the Rural Cooperative Organization (RCO) of Isfahan Province in Iran. The results of this research showed that from the members’ viewpoint, the highest corporate social responsibility was in the legal dimension and the lowest was in the discretionary dimension as based on the Carol model. The research results show that the organizational commitment index of managers is nearly of 50%. The results of cluster analysis in the field of members ‘perception of cooperative social responsibility showed that the four variables such as: performance satisfaction, members’ participation in cooperative meetings, age and purpose of membership, predicts the members’ behavior in separating the cooperative into two groups with strong and weak the CSR. Also, the result of cluster analysis in board of director’s organizational commitment showed that the variables such as: level of education, management experience and belief in the non-interference of other institutions in cooperative management, predicts the board of directors organizational commitment behavior in separating into two strong and weak the OC. Recibido: 29 diciembre 2020Aceptado: 23 septiembre 2021

AbstractLandslides are considered as one of the most devastating natural hazards in Iran, causing extensive damage and loss of life. Landslide susceptibility maps for landslide prone areas can be used to plan for and mitigate the consequences of catastrophic landsliding events. Here, we developed a deep convolutional neural network (CNN–DNN) for mapping landslide susceptibility, and evaluated it on the Isfahan province, Iran, which has not previously been assessed on such a scale. The proposed model was trained and validated using training (80%) and testing (20%) datasets, each containing relevant data on historical landslides, field records and remote sensing images, and a range of geomorphological, geological, environmental and human activity factors as covariates. The CNN–DNN model prediction accuracy was tested using a wide range of statistics from the confusion matrix and error indices from the receiver operating characteristic (ROC) curve. The CNN–DNN model was evaluated comprehensively by comparing it to several state-of-the-art benchmark machine learning techniques including the support vector machine (SVM), logistic regression (LR), Gaussian naïve Bayes (GNB), multilayer perceptron (MLP), Bernoulli Naïve Bayes (BNB) and decision tree (DT) classifiers. The CNN–DNN model for landslide susceptibility mapping was found to predict more accurately than the benchmark algorithms, with an AUC = 90.9%, IRs = 84.8%, MSE = 0.17, RMSE = 0.40, and MAPE = 0.42. The map provided by the CNN–DNN clearly revealed a high-susceptibility area in the west and southwest, related to the main Zagros trend in the province. These findings can be of great utility for landslide risk management and land use planning in the Isfahan province.

Background and aims: Brucellosis is one of the most common infectious diseases in both humans and animals. It has been controlled in developed countries; however, it is still regarded as a public health problem in developing countries including Iran. The aim of this study was to investigate the epidemiology of human brucellosis in Isfahan province. Methods: The present study is a cross-sectional descriptive study investigating the epidemiology of human brucellosis in Isfahan province from 2010 to 2015. Sampling was done using Isfahan’s disease registry database. Chi-square and t test were used for analyzing the data, and all data analyses were performed using SPSS software version 21.0. Results: A total of 3,245 patients were included in this study, and their mean (SD) age was 35.29 (18.00) years. The age group of 15-25 years with a frequency of 23.80% had the highest frequency of the disease. The annual incidence of the disease from 2010 to 2014 shows an increasing trend, reaching from 6.25 to 15 per 100000 people. It was reduced in 2015 and reached 12.25 per 100000. In addition, the highest incidence was observed in July. Conclusion: This study implies that the trend of human brucellosis has been increasing over the years, so it is recommended that people be educated on how to prevent it in humans and animals. The results of this study can help health administrators in the province to more effectively control the disease at the provincial level by identifying high-risk cities and focusing on health care in these areas.

Introduction: Medical errors include treatments that do not match approved standards in medical science and cause harm to the patients. This study aimed to investigate the frequency of complaints relating to pediatric dentistry in Isfahan province. Materials & Methods: This research is a descriptive, prospective, and cross-sectional study. Among 688 cases of dental complaint, of which data and documents collected in the medical council of Isfahan Province in 2008-2018, 14 identified cases of complaints were in the pediatric dentistry field, which then provided the needed data for research. Results: The number of complaints in 2009-2011, 2013, 2014, and 2015 was one case, in 2012, 2016, two cases and in 2017 and 2018 were no reports. 5 were dental malpractices. 13 identified complainants were from patients' fathers, and 1 case was the mother among practitioners, were 50% men, 50% women, 29% pedodontists, and 50% general dentists. 2 of 4 complaints from pedodontists and 3 of 7 complaints from general dentists in the pediatric field recognized as malpractices. Conclusion: This study shows the number of pediatric malpractices is low in the Isfahan province. However, dentists must adhere to the medical oath and have good relationships with their patients. Supporting patients during treatment and considering their opinions and also treatment charges may lead to patients' satisfaction. Meanwhile, dentists should know about their abilities and their limits in practices. Also, they should refer complex cases to a specialist when they need to prevent further problems.