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Objective: National surveys revealed a high prevalence of psychiatric disorders in Iran. Province-level estimates are needed to manage the resources and focus on preventive efforts more efficiently. The objective of this study was to provide province-level estimates of psychiatric disorders. Method: In this study, Iranian Mental Health Survey (IranMHS) data (n = 7886) was used to produce province-level prevalence estimates of any psychiatric disorders among 15-64 year old males and females. Psychiatric disorders were diagnosed based on structured diagnostic interview of the Persian version of Composite International Diagnostic Interview (CIDI, version, 2.1). The Hierarchical Bayesian (HB) random effect model was used to calculate the estimates. The mental health status of half of the participants was also measured using a 28-item general health questionnaire (GHQ). Results: A wide variation in the prevalence of psychiatric disorders was found among 31 provinces of Iran. The direct estimates ranged from 3.6% to 62.6%, while the HB estimates ranged from 12.6% to 36.5%. The provincial prevalence among men ranged from 11.9% to 34.5%, while it ranged from 18.4% to 38.8% among women. The Pearson correlation coefficient between HB estimates and GHQ scores was 0.73. Conclusion: The Bayesian small area estimation provides estimation with improved precision at local levels. Detecting high-priority communities with small-area approach could lead to a better distribution of limited facilities and more effective mental health interventions. [ABSTRACT FROM AUTHOR]

Background: Work-related accidents result in human suffering and economic losses and are considered as a major health problem worldwide, especially in the economically developing world.Objectives: To introduce seasonal autoregressive moving average (ARIMA) models for time series analysis of work-related accident data for workers insured by the Iranian Social Security Organization (ISSO) between 2000 and 2011.Methods: In this retrospective study, all insured people experiencing at least one work-related accident during a 10-year period were included in the analyses. We used Box-Jenkins modeling to develop a time series model of the total number of accidents.Results: There was an average of 1476 accidents per month (1476·05±458·77, mean±SD). The final ARIMA (p,d,q) (P,D,Q)s model for fitting to data was: ARIMA(1,1,1)×(0,1,1)12 consisting of the first ordering of the autoregressive, moving average and seasonal moving average parameters with 20·942 mean absolute percentage error (MAPE).Conclusions: The final model showed that time series analysis of ARIMA models was useful for forecasting the number of work-related accidents in Iran. In addition, the forecasted number of work-related accidents for 2011 explained the stability of occurrence of these accidents in recent years, indicating a need for preventive occupational health and safety policies such as safety inspection. [ABSTRACT FROM AUTHOR]

Objective:Traffic crashes are multifactorial events caused by human factors, technical issues, and environmental conditions. The present study aimed to determine the role of human factors in traffic crashes in Iran using the proportional odds regression model. Methods:The database of all traffic crashes in Iran in 2010 (n= 592, 168) registered through the “COM.114” police forms was investigated. Human risk factors leading to traffic crashes were determined and the odds ratio (OR) of each risk factor was estimated using an ordinal regression model and adjusted for potential confounding factors such as age, gender, and lighting status within and outside of cities. Results:The drivers’ mean age ± standard deviation was 34.1 ± 14.0 years. The most prevalent risk factors leading to death within cities were disregarding traffic rules and regulations (45%), driver rushing (31%), and alcohol consumption (12.3%). Using the proportional odds regression model, alcohol consumption was the most significant human risk factor in traffic crashes within cities (OR = 6.5, 95% confidence interval [CI], 4.88–8.65) and outside of cities (OR = 1.73, 95% CI, 1.22–3.29). Conclusions:Public health strategies and preventive policies should be focused on more common human risk factors such as disregarding traffic rules and regulations, drivers’ rushing, and alcohol consumption due to their greater population attributable fraction and more intuitive impacts on society. [ABSTRACT FROM PUBLISHER]

Background: Sistan and Balouchestan province is one of areas in Iran that have the highest malaria incidence. We have tried to investigate the epidemiology of malaria in this province. Materials and Methods: In this study, we evaluated epidemiological data of all malaria cases from April 2008 to March 2011 in this province. Results: In our study Plasmodium vivax was the most type of malaria. Malaria incidence was more in men and rural than female and urban. 22.7% of all cases were foreigners. Malaria incidence has had two picks. Conclusion: Malaria control interventions should be focused on high risk group and based on incidence peak. [ABSTRACT FROM AUTHOR]

Background: Vaccination seems to be the most critical means of halting the COVID-19 pandemic. It is crucial to understand the factors that influence COVID-19 vaccine acceptance to avoid low vaccination rates. This study intended to monitor the COVID-19 vaccine acceptance and its association with socio-demographic factors and prior diagnosis of COVID-19 in Iranian adults during the COVID-19 pandemic. Methods: The study utilized data from the COVID-19 Population Survey of Iran (COPSIR), a repeated national survey designed to monitor COVID-19-related behavioral insights. From April 2020 to November 2021, thirteen iterations of a series of crosssectional studies involving computer-assisted telephone interviews were conducted. Results: The COVID-19 vaccine acceptance rate remained above 80% until the ninth wave in February 2021, when it dropped to 62.9%. However, throughout the next four surveys, it rose gradually from 72.0% to 85.7%. The multilevel regression model revealed that the COVID-19 vaccine acceptance was significantly and positively linked with age and education. Conclusion: Despite the relatively high COVID-19 vaccine acceptance rate among Iranian adults, after the emergence of vaccines on the global market and controversies about their safety in Iran, the initially high vaccine acceptance rate dropped significantly, and then increased over time and returned to its peak level (85%). According to the Commodity Theory, this rise in vaccine acceptance can be attributed to the COVID-19 vaccine shortage in the country between January and July 2022. For Iranian adults to accept vaccines more readily, health promotion programs should target the youth and the less literate adults. [ABSTRACT FROM AUTHOR]

Background & objectives: Species identification and information on transmission pattern of malaria parasite in any malaria endemic area is key to success for a malaria control programme. In this investigation, malaria diagnosis using molecular method was used to assess the transmission pattern of malaria parasite in three malaria endemic regions: Afghanistan, Iran and Pakistan. Methods: Blood samples were collected from the patients presenting with vivax malaria from Afghanistan (n = 108), Iran (n = 200) and Pakistan (n = 199). Malaria parasite detection was made by the gold standard (microscopy) and also nested-PCR assay, using 18S small sub-unit ribosomal RNA (ssrRNA) gene. Results: Based on microscopy method, the level of mixed infection was zero to 2.5 per cent; however, nested-PCR assay detected 6.5, 22 and 23.5 per cent mixed infections in samples collected from Afghanistan, Iran and Pakistan, respectively. The present results showed that the co-infection of P. vivax with P. falciparum was frequent in malaria endemic regions of Iran and Pakistan. Interpretation & conclusion: The present data suggest the need for improving microscopy diagnosis method and the clinician should also have careful clinical observation, along with the reports on Giemsa-stained thick blood films, particularly in summer time when P. vivax is predominant. Also sharing information on transmission pattern of mixed infection among these countries may help in designing better control strategies for malaria. [ABSTRACT FROM AUTHOR]

Abstract: In this study, the diversity of Plasmodium vivax populations circulating in Pakistan and Iran has been investigated by using circumsporozoite protein (csp) and merozoite surface proteins 1 and 3α (msp-1 and msp-3α) genes as genetic markers. Infected P. vivax blood samples were collected from Pakistan (n =187) and Iran (n =150) during April to October 2008, and were analyzed using nested-PCR/RFLP and sequencing methods. Genotyping pvmsp-1 (variable block 5) revealed the presence of type 1, type 2 and recombinant type 3 allelic variants, with type 1 predominant, in both study areas. The sequence analysis of 33 P. vivax isolates from Pakistan and 30 from Iran identified 16 distinct alleles each, with one allele (R-8) from Iran which was not reported previously. Genotyping pvcsp gene also showed that VK210 type is predominant in both countries. Moreover, based on the size of amplified fragment of pvmsp-3α, three major types: type A (1800bp), type B (1500bp) and type C (1200bp), were distinguished among the examined isolates that type A was predominant among Pakistani (72.7%) and Iranian (77.3%) parasites. PCR/RFLP products of pvmsp-3α with HhaI and AluI have detected 40 and 39 distinct variants among Pakistani and Iranian examined isolates, respectively. Based on these three studied genes, the rate of combined multiple genotypes were 30% and 24.6% for Pakistani and Iranian P. vivax isolates, respectively. These results indicate an extensive diversity in the P. vivax populations in both studies. [Copyright &y& Elsevier]