The role of interaction-based effects on fatal accidents using logic regression

Background and Objectives: Road traffic accidents (RTAs) were estimated to be the eighth major cause of death worldwide in 2016. Investigation of various factors alone can distort the results. Thus, it is important to consider interactions among the various factors associated with RTAs. Logic regression was used to investigate the important combinations among traffic accident variables. Methods: In this analytical study, the existing 1-year data from the police accident database in 2014 were examined. The Legal Medicine Organization database was also used to correct death after 30 days. Logic regression, a generalized regression model, was used to explore the interactions among different factors of the accident. Results: Cross-validation results showed the best model in the form of three trees and eight leaves. Being a professional driver and exposure to a heavy vehicle on sandy or earthy road double the chance of death. Operating an unsafe car on a road with curve increases the odds of a fatal crash by 1.65 times. Driver error on a nonresidential road without any shoulders adds 90 to the odds of having a deadly crash. Conclusions: The significance of the interactions between the road and driver factors shows that roads with poor design can cause a driver to make mistakes and increase fatal accidents. Therefore, politicians must consider constructing structures alongside nonresidential roads and proper shoulders, install signs at curves, and repair pavement in order to reduce the fatality of accidents. It is also recommended that manufacturers of commercial vehicles install proper safeguards in all heavy vehicles to reduce fatal accidents

Predicting the status of COVID-19 active cases using a neural network time series

The design of intelligent systems for analyzing information and predicting the epidemiological trends of the disease is rapidly expanding because of the coronavirus disease (COVID-19) pandemic. The COVID-19 datasets provided by Johns Hopkins University were included in the analysis. This dataset contains some missing data that is imputed using the multi-objective particle swarm optimization method. A time series model based on nonlinear autoregressive exogenou (NARX) neural network is proposed to predict the recovered and death COVID-19 cases. This model is trained and evaluated for two modes: predicting the situation of the affected areas for the next day and the next month. After training the model based on the data from January 22 to February 27, 2020, the performance of the proposed model was evaluated in predicting the situation of the areas in the coming two weeks. The error rate was less than 5%. The prediction of the proposed model for April 9, 2020, was compared with the actual data for that day. The absolute percentage error (AE) worldwide was 12%. The lowest mean absolute error (MAE) of the model was for South America and Australia with 3 and 3.3, respectively. In this paper, we have shown that geographical areas with mortality and recovery of COVID-19 cases can be predicted using a neural network-based model

Burden of sexually transmitted infections in Iran from 1990 to 2010: Results from the global burden of disease study 2010

The present study describes the epidemiological status of sexually transmitted infections (STIs) in Iran based on the Global Burden of Disease study 2010 (the GBD 2010), and compares this with those of other neighboring countries. Methods: The burden of STIs from 1990 to 2010 in Iran was derived from a systematic study, namely the GBD 2010, which was conducted by the Institute for Health Metrics and Evaluation (IHME). Using a model-based estimation, Disability Adjusted Life Years (DALYs) were calculated on the basis of the prevalence of STIs. The GBD 2010 used disability weights, and a mortality rate that was obtained from the vital registration system of Iran. We review the results of the GBD 2010 estimations for STIs in Iran. Results: The trend of DALYs attributable to STIs (107. 3 and 26. 47 per 100, 000 people in 1990 and 2010, respectively) and deaths (1. 13 and 0. 12 per 100, 000 people in 1990 and 2010, respectively) decreased dramatically in Iran during the last two decades. The majority of individuals affected by STI DALYs were aged 1-4 and 20-24 years. Conclusion: Since the majority of DALYs attributed to STIs were observed among those aged 1-4 years and young people, the economic burden of STIs will remain high in Iran. Therefore, effective evidence-based planning is critical to allocate the essential budget for utilizing treatment and prevention approaches

Serial Interval Distribution of COVID-19 among Iranian Reported Confirmed Cases

Type of manuscript: short report Introduction:  Serial interval refers to the average time between of the onset of the symptoms of two successive cases. Serial interval distribution can be used for the calculation of the basic reproduction number (R0), transmission rate, and study of an epidemic trend. This study aims to investigate the mean, standard deviation, and distribution of serial interval among the confirmed cases of COVID-19 using a Gamma distribution.      Methods: To determine the serial interval, 60 confirmed infected cases of COVID-19 (based on PCR test results) in February 20th-May 20th, 2020 were selected as the cases. For these cases, 37 transmissions occurred. The data of the dates of the occurrence of primary and secondary symptoms were collected by referring to the COVID-19 surveillance system and interviewing the patients Results: The findings showed that the median and mean of the serial interval were 3.0 and 4.5± 3.5 days. The findings showed that the median of the serial interval was 3.0 days (with the inter-quartile range of 2.0-6.0). The mean serial interval was 4.5± 3.5 days (95% confidence interval: 3.1-5.5). Conclusions: Our report showed a shorter period for a serial interval less than the previous reported interval in China. It seems that regarding the shorter serial interval reported in this study, the basic reproduction numbers reported by the first papers published in Iran have been overestimated regarding the serial interval of 7.5 days. Key words: COVID-19, Serial interval, Gamma distributio

Serial Interval Distribution of COVID-19 among Iranian Reported Confirmed Cases

Type of manuscript: short report Introduction:  Serial interval refers to the average time between of the onset of the symptoms of two successive cases. Serial interval distribution can be used for the calculation of the basic reproduction number (R0), transmission rate, and study of an epidemic trend. This study aims to investigate the mean, standard deviation, and distribution of serial interval among the confirmed cases of COVID-19 using a Gamma distribution.      Methods: To determine the serial interval, 60 confirmed infected cases of COVID-19 (based on PCR test results) in February 20th-May 20th, 2020 were selected as the cases. For these cases, 37 transmissions occurred. The data of the dates of the occurrence of primary and secondary symptoms were collected by referring to the COVID-19 surveillance system and interviewing the patients Results: The findings showed that the median and mean of the serial interval were 3.0 and 4.5± 3.5 days. The findings showed that the median of the serial interval was 3.0 days (with the inter-quartile range of 2.0-6.0). The mean serial interval was 4.5± 3.5 days (95% confidence interval: 3.1-5.5). Conclusions: Our report showed a shorter period for a serial interval less than the previous reported interval in China. It seems that regarding the shorter serial interval reported in this study, the basic reproduction numbers reported by the first papers published in Iran have been overestimated regarding the serial interval of 7.5 days. Key words: COVID-19, Serial interval, Gamma distributio

Integration of Research, Public Health, and Hospital Interventions as a Successful Model for Controlling COVID-19 Pandemic: A Perspective

The COVID-19 pandemic has been a serious health problem in most countries in the last few months, with every country adopting different preventive and therapeutic measures based on their specific circumstances. The epidemic began in Iran on February 19, 2020, and gradually spread across the country. The epidemic extent varies, and different preventive and therapeutic measures are taken in Iran. Shahroud and Miami Counties, covered by the Shahroud University of Medical Sciences, have experienced the highest incidence of COVID-19 in Iran. However, the epidemic is well controlled by integrating the activities of the health, treatment, and research sectors and using information technology and a proprietary software application. This model can be thus studied as a successful experience. Keywords: COVID-19, Control, Successful model, Ira

Inequalities in cancer distribution in Tehran; A disaggregated estimation of 2007 incidencea by 22 districts

Background: Cancer is the third cause of death in Iran, with an increasing incidence projected for the next decade. This study aimed to provide a disaggregated viewpoint on cancer incidence in all 22 districts of Tehran, using the Geographic Information System (GIS). Identifying clusters of cancers may assist in recognizing the cause of the disease, visualizing patterns of cancer distribution, the potential disparities, and help in the provision of early detection programs and equitable, curative, and palliative services. Methods: According to the 2007 - 2008 Cancer Registry Data published by the Ministry of Health, there were 7948 new cancer cases diagnosed in Tehran. Data were collected from all pathology centers and hospitals, either public or private facilities, in Tehran. These were classified into 31 main categories according to the expert panels and available resources. The population of the districts and neighborhoods were obtained from the Iran Statistical Center and the Municipally of Tehran, respectively. Home addresses and phones were extracted from the database and imported to GIS. The Age-Standardized Rate (ASR) was calculated using both the new world standard population (2000 - 2025) and the Iran population. Results: Overall, the cancer incidence rate and ASR were 101.8 and 94.775 per 100,000 people, respectively. The maximum cancer incidence rates in both sexes were in districts 6, 3, 1, and 2, whereas, the maximum ASRs were in districts 6, 1, 2, and 3. District 6 accommodated the highest ASRs in both the sexes. Common cancers were breast, skin, colorectal, stomach, and prostate. The ASR in men and women were 129.954 and 114.546 per 100,000 population. Conclusion: This report provides an appropriate guide to estimate the cancer distribution within the districts of Tehran. Higher ASR in districts 6, 1, 2, and 3, warrant further research, to obtain robust population-based incidence data and also to investigate the background predisposing factors in the specified districts

Investigation the prevalence of COVID-19 in different occupations in Shahroud city

Introduction: Covid-19 was first reported as a viral disease in China in 2019, and it soon became a global pandemic. In addition, the types of occupations people have and the environments in which they work may increase the likelihood of being exposed to the virus. Thus, this study was conducted to investigate the prevalence of Covid-19 disease in various occupations and its relationship with some effective parameters in Shahroud city. Methods: This research is a cross-sectional, descriptive-analytical study that was conducted in 2021. The required information was extracted from the database provided by Shahroud University of Medical Sciences. These files contain the results of the comprehensive study of COVID-19 in Shahroud. All the jobs that were asked of the person were classified based on International Standard Classification of Occupations and suspicious and definite cases were examined in different occupation. The information analyzed using SPSS software version 22. Results: According to the results, the highest percentage of cases (45%) was in healthcare workers, such as doctors, nurses, and operating room staffs—in other words, all employees working in the healthcare system. The next highest percentages were in household and home nursing workers (44.5%), retirees (43.2%), and construction workers (43%). The relationship between variables such as age, smoking status, presence of comorbidities, and presence of a high body mass index (BMI) associated with Covid-19 disease was examined by the regression test. It was found that the relationship was significant, that these variables affected the prevalence of the disease. Based on the odds ratio in the age variable, with each year of age, the chance of getting infected increased by 1%. A current smoker had a reduced chance of getting the disease by 57.2%. Having a comorbidity increased the chance of getting the disease by 14%, and with each increase in BMI, the chance of getting the disease increased by 3.8%. Conclusion: The study found that in some occupations, such as healthcare worker, the prevalence of the disease was higher because workers were in direct contact with patients and people infected with the virus. In general, it can be said that the prevalence of the disease was low in workers who could telework and remain at home rather than go to a job or in the community. Factors such as age, the presence of comorbidities, status as a current smoker, and having a high BMI had an effect on contracting Covid-19 disease

The global and regional prevalence of hepatitis C and B co-infections among prisoners living with HIV: a systematic review and meta-analysis.

BackgroundHepatitis B virus (HBV) and hepatitis C virus (HCV) infections are common among individuals with human immune deficiency virus (HIV) infection worldwide. In this study, we did a systematic review and meta-analysis of the published literature to estimate the global and regional prevalence of HCV, HBV and HIV coinfections among HIV-positive prisoners.MethodsWe searched PubMed via MEDLINE, Embase, the Cochrane Library, SCOPUS, and Web of science (ISI) to identify studies that reported the prevalence of HBV and HCV among prisoners living with HIV. We used an eight-item checklist for critically appraisal studies of prevalence/incidence of a health problem to assess the quality of publications in the included 48 cross-sectional and 4 cohort studies. We used random-effect models and meta-regression for the meta-analysis of the results of the included studies.ResultsThe number of the included studies were 50 for HCV-HIV, and 23 for HBV-HIV co-infections. The pooled prevalence rates of the coinfections were 12% [95% confidence interval (CI) 9.0-16.0] for HBV-HIV and 62% (95% CI 53.0-71.0) for HCV-HIV. Among HIV-positive prisoners who reported drug injection, the prevalence of HBV increased to 15% (95% CI 5.0-23.0), and the HCV prevalence increased to 78% (95% CI 51.0-100). The prevalence of HBV-HIV coinfection among prisoners ranged from 3% in the East Mediterranean region to 27% in the American region. Also, the prevalence of HCV-HIV coinfections among prisoners ranged from 6% in Europe to 98% in the East Mediterranean regions.ConclusionsOur findings suggested that the high prevalence of HBV and HCV co-infection among HIV-positive prisoners, particularly among those with a history of drug injection, varies significantly across the globe. The results of Meta-regression analysis showed a sliding increase in the prevalence of the studied co-infections among prisoners over the past decades, rising a call for better screening and treatment programs targeting this high-risk population. To prevent the above coinfections among prisoners, aimed public health services (e.g. harm reduction via access to clean needles), human rights, equity, and ethics are to be seriously delivered or practiced in prisons. Protocol registration number: CRD42018115707 (in the PROSPERO international)

More reliability of suspicious symptoms plus chest CT-scan than RT_PCR test for the diagnosis of COVID-19 in an 18-days-old neonate

The present study investigated an 18-days-old neonate who was referred to the hospital with suspected respiratory symptoms of COVID-19. Results of CT-Scan and blood tests were highly suspicious, but result of the first RT-PCR test was negative on March 1. The second RT-PCR test reported positive on March 12. The neonate's medical history indicated no close contact except with family members and hospital treatment staffs, but the RT-PCR test results of all family members were also negative