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B ackground: According to the World Health Organization, preventive measures are the o nly non-pharmacological method to combat the COVID-19 epidemic. This study aimed t o investigate the relationship between perceived social support and preventive behaviors mediated by the variables of life expectancy and mental wellbeing. Materials and Methods: This study is applied in terms of purpose and was conducted by survey method. The statistical population included women living in Tehran City, Iran, with a sample size of 428. The study data were collected using the preventive behavior scale, mental wellbeing scale, Snyder hope scale, and multidimensional perceived social support scale. The obtained data were analyzed using SPSS 25 and AMOS 23 software. Results: The study results showed a positive and significant relationship between perceived social support and mental wellbeing, between perceived social support and life expectancy, and between mental wellbeing and life expectancy. Also, life expectancy and mental wellbeing variables mediate between perceived social support and preventive behaviors. Conclusion: Considering the critical role of women in family management and preventive measures during the COVID-19 epidemic, strengthening social support networks, hope, and mental wellbeing should be considered. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to investigate the effects of COVID-19 regarding the efficiency of industries based on data in the Tehran stock market. A hybrid model of Data Envelopment Analysis (DEA) and data mining techniques is used to analyze the investment behavior in Tehran stock market. Particularly during the COVID-19 pandemic, many companies face financial crises. That is why companies with inferior performance must be benchmarked with efficient companies. First, the financial data of investments on selective companies are analyzed using data mining approaches to recognize the behavioral patterns of investors and securities. Second, customers are clustered into 3 selling and 4 buying groups using data mining techniques. Then, the efficiency of active companies in stock exchange is evaluated using input-oriented DEA. The results indicate that, among 23 industries listed on the stock market in Iran, solely nine were efficient in 2019. Moreover, in 2020, the number of efficient industries further decreased to six industries. Comparing the obtained results with those of another study which was conducted in 2018 by other researchers revealed that COVID-19 strongly affects the performance of an industry and some industries which were efficient in the past such as the bank industry became inefficient in the following year. [ABSTRACT FROM AUTHOR]

The Islamic Republic of Iran reported its first COVID-19 cases by 19th February 2020, since then it has become one of the most affected countries, with more than 73,000 cases and 4,585 deaths to this date. Spatial modeling could be used to approach an understanding of structural and sociodemographic factors that have impacted COVID-19 spread at a province-level in Iran. Therefore, in the present paper, we developed a spatial statistical approach to describe how COVID-19 cases are spatially distributed and to identify significant spatial clusters of cases and how socioeconomic and climatic features of Iranian provinces might predict the number of cases. The analyses are applied to cumulative cases of the disease from February 19th to March 18th. They correspond to obtaining maps associated with quartiles for rates of COVID-19 cases smoothed through a Bayesian technique and relative risks, the calculation of global (Moran's I) and local indicators of spatial autocorrelation (LISA), both univariate and bivariate, to derive significant clustering, and the fit of a multivariate spatial lag model considering a set of variables potentially affecting the presence of the disease. We identified a cluster of provinces with significantly higher rates of COVID-19 cases around Tehran (p-value< 0.05), indicating that the COVID-19 spread within Iran was spatially correlated. Urbanized, highly connected provinces with older population structures and higher average temperatures were the most susceptible to present a higher number of COVID-19 cases (p-value < 0.05). Interestingly, literacy is a factor that is associated with a decrease in the number of cases (p-value < 0.05), which might be directly related to health literacy and compliance with public health measures. These features indicate that social distancing, protecting older adults, and vulnerable populations, as well as promoting health literacy, might be useful to reduce SARS-CoV-2 spread in Iran. One limitation of our analysis is that the most updated information we found concerning socioeconomic and climatic features is not for 2020, or even for a same year, so that the obtained associations should be interpreted with caution. Our approach could be applied to model COVID-19 outbreaks in other countries with similar characteristics or in case of an upturn in COVID-19 within Iran. Author summary: Iran was among the first countries reporting a rapid increase in the number of COVID-19 cases. Spatial epidemiology is useful to study the spatial distribution of a disease and to identify factors associated with the number of cases of such disease. By applying these methods, we aimed to identify whether there are clusters of regions in Iran with high or low number of COVID-19 cases and the association of different factors with these numbers, considering spatial relationships and maps representing these associations. Interestingly, we found regions of high number of cases and that more COVID-19 cases were present in provinces with more urbanization, aging population, number of physicians, efficient communications, and greater average temperatures, whereas less COVID-19 cases were present in provinces with more literacy. This study allowed us to understand the spatial behavior of the disease and the importance of having adequate health policies, literacy campaigns, and disseminating health information to the population. [ABSTRACT FROM AUTHOR]

In February 2020, the first sample test was confirmed as positive for corona virus in Masih Daneshvari Hospital that is the reference center in Iran for all pulmonary and respiratory diseases. The decisions made in a hospital or organization to manage a crisis is very vital. Success in managing any crisis requires a scientific and scholarly attitude. This paper was distilled from experiences gained in Masih Daneshvari Hospital in Tehran, capital of Iran, in March 2020 at the stubborn time of coping and managing corona virus crisis. This study was conducted using participatory action research, a methodology which identifies problems in practice, and finds methods to solve them. This Action research involves five stages: statement of the problem, planning, data interpretation and analysis, action, and evaluation of the research process during performing the study. The whole hospital was equipped for corona virus patients in 10 phases during one week and 250 active beds were equipped for these patients. Three models, namely, "corona virus crisis management model", "Pharmaceutical care management in coronavirus crisis model" and "nursing in coronavirus crisis model" were planned and implemented. During one month of implementing these three models, the supervision team monitored the accurate implementation of instructions and resolving or revising the possible deficiencies and faults. The Masih Daneshvari crisis management model in coronavirus, can be a useful and applicable model in other corona virus centers. [ABSTRACT FROM AUTHOR]

Objectives: Comparison of the effect of hydroxychloroquine with placebo to prevent infection from the COVID -19 virus among healthcare professionals TRIAL DESIGN: Single centre, 2-arm, double-blind randomised (ratio 1:1) placebo-controlled trial PARTICIPANTS: Treatment staff who are in contact with patients and have at least 3 shifts a week in Arash hospital affiliated with Tehran University of Medical Sciences, in Iran and who consent to participate in the study. Exclusion criteria include: History of COVID -19 virus infection, clinical symptoms such as fever, nausea, dyspnea and myalgia in the past two months, history of underlying diseases hypersensitivity to hydroxychloroquine and G6PD enzyme deficiency.Intervention and Comparator: Intervention group: Hydroxychloroquine 200 mg tablet of Amin Pharmaceutical.Control Group: placebo which is completely similar in form and taste to 200 mg hydroxychloroquine tablet and is manufactured by the same factory (Amin Pharmacy). The dosage is two tablets daily, once a week for one to three months (based on the duration of the Coronavirus epidemic in Tehran).Main Outcomes: Confirmed COVID-19 virus infection using Polymerase chain reaction (PCR) test is the primary outcome. The time period for measuring the primary outcome is any infection within the trial period up to one month after taking the last dose.Randomisation: The randomized block allocation method was developed using Stata version 15 software by an independent researcher, using a block size of six. Allocation to the two treatment groups will be conducted by this researcher using paper labels (random 10-digit codes) in a 1:1 ratio t The labels will be attached to the drug packages in order of randomization. Drug packages will be arranged in a box according to the randomization list.Blinding (masking): Participants and caregivers are blinded to group assignment and the data will be analyzed by an independent statistical expert who is unaware of the treatment allocation.Numbers To Be Randomised (sample Size): A total of 282 participants will be randomised with 141 participants the Hydroxychloroquineeach intervention group and 141 participants to the placebo control group TRIAL STATUS: The protocol version number is 99-1-101-47091 and the approval ID is IR.TUMS.VCR.REC.1399.001 and recruitment began April 7, 2020, and is anticipated to be complete by August 7, 2020.Trial Registration: The name of the trial register is Iranian registry of clinical trial (IRCT), registration number is IRCT20120826010664N6, date of trial registration is April 7, 2020, FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol. [ABSTRACT FROM AUTHOR]