Health in Emergencies and Disasters Quarterly
Year:2022 | Volume:7 | Issue:4|Papers Count:7

today, due to the COVID-19 pandemic, the governments and international institutions are using various strategies to control the spread of infection. In the meantime, the health of healthcare workers who are responsible for the health and treatment of patients is very important [1]. . . .

Background: Safety plays a significant role in the oil & gas industries, where there are many risk factors that can cause accidents. This study aims to evaluate the level of safety culture among the employees of the operational units of South Zagros Oil & Gas Production Company (SZOGPC). Materials and Methods: In this descriptive-analytical study, a standardized safety culture questionnaire with 50 items and five domains of education, workplace, safety priority, information exchange, and management commitment was used. All employees in the operational units of the SZOGPC were selected as samples (n=260). They answered the questions based on Five-point Likert scales. After collecting the data, their were entered into SPSS software, v. 23. Results: The mean safety culture score in Parsian operational unit was higher than in other operational units. The lowest level of safety culture was related to the operational unit of Sarkhun & South Gashu. The Mean±, SD of total safety culture score was 19. 03±, 0. 248. Among the safety culture domains, safety priority had the highest score, while the workplace had the lowest score. Conclusion: The safety culture among the employees of the operational units of the SZOGPC is at moderate level. The managers of this company should improve the safety culture among their employees,a positive and high safety culture among employees can facilitate the organization’, s movement to achieve higher safety standards.

Background: Forecasting methods are used in various fields including the health problems. This study aims to use the Artificial Neural Network (ANN) method for predicting coronavirus disease 2019 (COVID-19) cases in Iran. Materials and Methods: This is a descriptive, analytical, and comparative study to predict the time series of COVID-19 cases in Iran from May 2020 to May 2021. An ANN model was used for forecast ing, which had three Input, output, and intermediate layers. The network training was conducted by the Levenberg-Marquardt algorithm. The forecasting accuracy was measured by calculating the mean absolute percentage error. Results: The mean absolute error of the designed ANN model was 6 and its accuracy was 94%. Conclusion: The ANN has high accuracy in forecasting the number of COVID-19 cases in Iran. The outputs of this model can be used as a basis for decisions in controlling the COVID-19.

Background: Women are at higher risk of death during disasters due to physical, biological, psychological, and cultural differences. After a disaster, they experience more miscarriages, premature births, inadequate fetal growth, low birth weight, sexual violence, and unwanted pregnancies. This study aims to investigate the reproductive health status of women affected by the 2017 earthquake in Kermanshah, Iran. Materials and Methods: This descriptive cross-sectional study was conducted in 2018. The study population consists of women aged 15-49 years (Mean age=31. 7 years) living in Sarpol-e Zahab, Javanrood, and Thalas Babajani towns in Kermanshah city affected by the earthquake in 2017. The questionnaire used for assessing the status of reproductive health in women was the Reproductive Health Assessment Questionnaire for Women of Reproductive Age, which has already been localized in Iran and its reliability and validity have been confirmed. Native Kurdish language experts completed the questionnaires on behalf of 396 participants. Descriptive statistics were used to describe the variables. Results: It was found that 42. 4% of women complained of abnormal menstruation and 34. 09% of limited menstrual hygiene materials. Sixty women were pregnant at the time of the earthquake, all of whom gave birth in hospital,two had miscarriages, two had premature births, and one had stillbirth. Urinary tract infection was the most common problem (21%) in pregnant women. Moreover, 48% of women used contraceptive methods after the earthquake, the most commonly used method was the use of contraceptive pills (23%). Access to contraception methods was difficult for 14. 4% of them after the earthquake. Furthermore, 25% had experienced violence after the earthquake,of these, 30 reported physical violence, 86 verbal violence, and 13 sexual violence. Conclusion: The control of pregnancy and safe delivery in earthquake-affected areas of Kermanshah is relatively acceptable,however, the provision of reproductive health services seems to be challenging. It is recommended to pay attention to the menstrual hygiene of women and regular distribution of contraceptives (despite the current population growth plan), address sexual acts of violence, and develop a protocol to support the victims.

Background: Today, with the coronavirus disease 2019 (COVID-19) pandemic, the governments and international institutions are taking various approaches to control the infections. This study aims to propose an improved susceptible-exposed-infectiousremoved (SEIR) model to predict the future trend of pandemic and assess the effectiveness of prevention and control strategies. Materials and Methods: A new SEIR model was developed by adding two Q1 and Q2 isolation parameters (at home and hospital) named “, SEIR-Q1Q2”,to predict the future trend of pandemic, and assess the effectiveness of prevention and control strategies in Ezhou, Hubei province, China. The stimulation was conducted in Python by evaluating the effects of pandemic knowledge dissemination, medical supply, and both. Results: due to the lack of knowledge of the disease risk, there was no strong tendency towards self-isolation, and the outbreak time coincided with the start of the Spring Festival, China’, s major holiday, when many Chinse people are gathered and have close contact with each other. Therefore, it was not possible to disseminate the knowledge of pandemic, which let the virus kill many people. Conclusion: The SEIR-Q1Q2 model can be used to predict the future trend of the COVID-19 pandemic by proposing the dissemination of the pandemic knowledge and increasing the supply of medical resources.

Background: Social distancing is an effective way to prevent the spread of COVID-19 and its new variants. This study aims to develop the Attitude & Practice towards Social Distancing (APSD) Questionnaire and evaluate its validity and reliability during the COVID-19 pandemic in Iran. Materials and Methods: This mixed-method study, used Waltz’, s 4-step method to develop the APSD questionnaire. The initial items were formulated based on a semistructured interview with the participants and social distancing guidelines. After confirming the face validity and content validity of the questionnaire, it was distributed among the participants online. Its internal consistency was assessed by calculating the Cronbach’, s alpha (α, ). The exploratory factor analysis and confirmatory factor analysis (CFA) were carried out in SPSS software, version 16 and AMOS version 24. Finally, the reliability was evaluated using the test-retest method. Results: The preliminary draft with 33 items (15 for the attitude and 18 for the practice) were answered by 623 participants. After CFA, the final draft consisted of 7 items and three factors (CVR=0. 77, CVI=0. 92, α, =0. 73) for the attitude subscale, and 8 items and three factors for the practice subscale (CVR=1, CVI=0. 98, α, =0. 76). Conclusion: The 15-item APSD questionnaire is a valid and reliable tool to evaluate the status of social distancing during the COVID-19 pandemic in Iran.

Background: Disasters put high burden on healthcare workers. This study aims to determine the willingness and competence of nurses to work during disasters who were employed in a state hospital in Bolu, Turkey and also investigate the related socio-demographic factors. Materials and Methods: This descriptive study was carried out on 311 nurses working in a state hospital in the center of Bolu city in Turkey. A researcher-made questionnaire with 35 items as well as a questionnaire with 45 items assessing the basic skills of nurses for preparation in disasters were used to collect data. Results: Most participants were undecided about working during disasters. Most of them were willing to work in earthquakes, while they had less willingness to work during pandemics. Nurses who were single, male, had no phobias, had hobbies, had no children, had a dependent person in the family, had membership in NGOs, and had Hospital Disaster Plan knowledge were more willing to work during disasters (P<0. 05). Nurses who were single, male, had hobbies, and had a role in Hospital Disaster Plan had more competence to work during disasters (P<0. 05). Conclusion: Most nurses in Turkey are undecided about working during disasters. Medical centers should use the nurses that have more willingness and competence to work during disasters.