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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 COVID-19 has placed pandemic modeling at the forefront of the whole world's public policymaking. Nonetheless, forecasting and modeling the COVID-19 medical waste with a detoxification center of the COVID-19 medical wastes remains a challenge. This work presents a Fuzzy Inference System to forecast the COVID-19 medical wastes. Then, people are divided into five categories are divided according to the symptoms of the disease into healthy people, suspicious, suspected of mild COVID-19, and suspicious of intense COVID-19. In this regard, a new fuzzy sustainable model for COVID-19 medical waste supply chain network for location and allocation decisions considering waste management is developed for the first time. The main purpose of this paper is to minimize supply chain costs, the environmental impact of medical waste, and to establish detoxification centers and control the social responsibility centers in the COVID-19 outbreak. To show the performance of the suggested model, sensitivity analysis is performed on important parameters. A real case study in Iran/Tehran is suggested to validate the proposed model. Classifying people into different groups, considering sustainability in COVID 19 medical waste supply chain network and examining new artificial intelligence methods based on TS and GOA algorithms are among the contributions of this paper. Results show that the decision-makers should use an FIS to forecast COVID-19 medical waste and employ a detoxification center of the COVID-19 medical wastes to reduce outbreaks of this pandemic. [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]

Introduction: The COVID-19 pandemic posed significant risks to children worldwide. This study aimed to assess the COVID-19 protection status of children and explored the relationship between household socio-economic status and COVID-19 morbidity and preventive measures, including vaccination and mask-wearing, in two cities in Iran. Method: A population-based cross-sectional study was conducted from July to October 2022 among 7 to 18-year-old children and their families in Tehran and Karaj. A total of 3,022 samples were selected using stratified multistage cluster sampling. Data were collected through interviews with children and adults, using questionnaires and was analyzed with Stata software version 14. Results: The analysis focused on 2,878 children with a median age of 12. Over half (54%) reported that the pandemic negatively affected their family's financial status, with 45% describing its impact on children's needs as negative or very negative. Just under 50% of respondents consistently wore masks during the study period, and around 54% had received at least one dose of the COVID-19 vaccine. Reasons for not getting vaccinated included concerns about side effects, ineligibility for the target age group, and overcrowding at vaccination sites. The odds of not getting vaccinated were significantly lower for children aged 15–18, with boys more likely to refuse vaccination than girls. Conclusion: The financial impact of the pandemic in Iran affected families' ability to meet their children's needs. Moreover, low vaccination acceptance rates increased children's vulnerability to health problems and contributed to COVID-19 infections. Efforts should be made to increase vaccination acceptance, particularly among immigrant populations. [ABSTRACT FROM AUTHOR]

With the severe outbreak of the novel coronavirus (COVID-19), researchers are motivated to develop efficient methods to face related issues. The present study aims to design a resilient health system to offer medical services to COVID-19 patients and prevent further disease outbreaks by social distancing, resiliency, cost, and commuting distance as decisive factors. It incorporated three novel resiliency measures (i.e., health facility criticality, patient dissatisfaction level, and dispersion of suspicious people) to promote the designed health network against potential infectious disease threats. Also, it introduced a novel hybrid uncertainty programming to resolve a mixed degree of the inherent uncertainty in the multi-objective problem, and it adopted an interactive fuzzy approach to address it. The actual data obtained from a case study in Tehran province in Iran proved the strong performance of the presented model. The findings show that the optimum use of medical centers' potential and the corresponding decisions result in a more resilient health system and cost reduction. A further outbreak of the COVID-19 pandemic is also prevented by shortening the commuting distance for patients and avoiding the increasing congestion in the medical centers. Also, the managerial insights show that establishing and evenly distributing camps and quarantine stations within the community and designing an efficient network for patients with different symptoms result in the optimum use of the potential capacity of medical centers and a decrease in the rate of bed shortage in the hospitals. Another insight drawn is that an efficient allocation of the suspect and definite cases to the nearest screening and care centers makes it possible to prevent the disease carriers from commuting within the community and increase the coronavirus transmission rate. [ABSTRACT FROM AUTHOR]

By applying multivariate regression to 2020 survey data from four Tehran hospitals, we measure eight recognized sources of Coronavirus disease 2019 (COVID-19) pandemic-related anxiety among 723 healthcare workers (HCWs) with diverse sociodemographic characteristics employed across different hospital areas and positions. The most prominent anxiety source identified is the risk of workplace COVID-19 contraction and transmission to family, followed by uncertainty about organizational support for personal and family needs in the event of worker infection. A supplemental qualitative analysis of 68 respondents in the largest hospital identifies four additional anxiety sources, namely, health, finances, workload, and leadership. This evidence of the multifaceted nature of anxiety sources among HCWs highlights the differentiated approaches that hospital policymakers must take to combat anxiety. [ABSTRACT FROM AUTHOR]

During the last months of the coronavirus pandemic, with all those public restrictions and health interventions, the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) appears now to have been raised in some countries around the world. Iran was one of those first countries facing the second wave of coronavirus, due to the lack of appropriate public restrictions because of economic problems the country is facing. The clinical and demographic characteristics of severe cases and non-severe cases of Coronavirus Disease (COVID-19) in 192 patients in Tehran, Iran, between June 16 and July 11, 2020, were investigated. The patients were divided into severe cases (n = 82) and non-severe cases (n = 110). Demographic and clinical characteristics were compared between the two study clusters. The mean age was 54.6 ± 17.2 years, and the most common presenting symptom was persistent cough (81.8%) and fever (79.7%). The logistic regression model revealed that age, BMI, and affected family members were statistically associated with severity. Patients with complicated conditions of disorders faced more hospitalization days and medical care than the average statistical data. As the coronavirus spike in the case and death reports from June 2020, we observed the rise in the incidence of severe cases, where 42.7% (82/192) of cases have resulted in severe conditions. Our findings also suggested that the effect of IFB (Betamethasone) was more valid than the other alternative drugs such as LPV/r and IVIg. [ABSTRACT FROM AUTHOR]