Control Of COVID-19 Disease Research Articles

Modeling and control of COVID-19 disease using deep reinforcement learning method.

The prevalence of epidemics has been studied by researchers in various fields. In the last 2 years, the outbreak of COVID-19 has affected the health, economy, and industry of communities around the world and has caused the death of millions of people. Therefore, many researchers have tried to model and control the prevalence of this disease. In this article, the new SQEIAR model for the spread of the COVID-19 disease is provided, which, compared to previous models, explores the effects of additional interventions on the outbreak and incorporates a wider range of variables and parameters to enhance its accuracy and alignment with reality. These modifications in the model lead to a more rapid eradication and control of the disease. This model includes six variables of the group of susceptible, quarantined, exposed, symptomatic, asymptomatic, and recovered individuals and includes three control inputs such as quarantine of susceptible, vaccination, and treatments. In order to minimize symptomatic infectious individuals and susceptible individuals and also to reduce treatment, vaccination, and quarantine costs, an optimal control approach using the Deep Deterministic Policy Gradient (DDPG) method has been applied to the system. This algorithm is applied to the model in different cases of control inputs, and for each case, optimal control inputs are obtained. In the following, the number of deaths due to the disease and the total number of symptomatic infectious individuals for each of these optimal control cases has been calculated. The results of the implemented control structure demonstrated a reduction of 60% in the number of deaths and 74% in the number of symptomatically infected individuals compared to the uncontrolled model. Finally, to test the performance of the control system, noise was applied to the system in various ways, including three methods: applying noise to observer variables, applying noise to control inputs, and applying uncertainty to model parameters. Therefore, we found that this control system was robust and performed well in different conditions despite the disturbance.

The Effect of Coronavirus Disease 2019 on the Quality of Associated Care in Patients with Gastric Cancer.

Coronavirus is a new virus that has affected human life on a large scale; it has infected millions of people and killed hundreds of thousands of people. In contrast, among cancers, stomach neoplasia is the most common cancer of the upper gastrointestinal (UGI) tract. COVID-19 disease has disrupted the optimal management of patients with cancer. Metastasis, deterioration of the patient's nutritional status, UGI bleeding, and increased surgical complications are all consequences of delayed treatment of patients with gastric cancer. However, there is still insufficient evidence on the immunogenicity of the vaccine and the protection provided by coronavirus vaccines in patients with cancer, especially those with immunodeficiency or those who are treated for certain types of cancers. Also, as part of the prevention and control of COVID-19 disease, nutritional support for patients with gastrointestinal cancer is particularly important, and the psychological and physiological limitations caused by the disease duration are hurting the well-being of patients. Therefore, the assessment of the impact of the coronavirus on cancer should be treated as an important issue, and healthcare professionals should be prepared to deal with the long-term effects of the coronavirus disease.

Professional Quality of Life among Iranian Clinical Nurses at the Forefront of the Fight against COVID-19: A Multicenter Cross-Sectional Study.

With the prolonged COVID-19 disease control time, concerns about the caring ability of clinically exposed nurses have increased. This study aimed to investigate Compassion Satisfaction (CS), Burnout (BO), and Secondary Traumatic Stress (STS) as elements of Professional Quality of Life among nurses in COVID-19 settings. In this descriptive online national survey, 427 clinical nurses who had worked in the COVID-19 wards from all Iran provinces answered the Persian version of the Professional Quality of Life Scale as the profile tool with three subscales, including CS, BO, and STS. Data were collected using email, Short Message Service (SMS), and social networks from December 2020 to February 2021. The mean (SD) score of CS was 38.86 (9.00), the mean (SD) score of BO was 18.60 (4.08), and STS was 34.74 (7.02). STS was substantially more prevalent among married nurses whose Polymerase Chain Reaction (PCR) tests were positive for themselves or at least one family member (p < 0.05). Clinical nurses who respond to the COVID-19 crisis are at risk of STS and BO. In pandemic situations like COVID-19, it is necessary to consider supportive interventions to increase satisfaction and reduce burnout and secondary traumatic stress in nurses.

Impact of COVID-19 Disease Control Committee (CDCC) policies on prevention of the disease using Bayes network inference in west of Iran

BackgroundThe start of the COVID-19 pandemic was an emergency situation that led each country to adopt specific regional strategies to control it. Given the spread of COVID-19 disease, it is crucial to evaluate which policy is more effective in reducing disease transmission. The purpose of this study was to determine the impact of policies made by COVID-19 Disease Control Committee (CDCC) to reduce the risk of the disease in Hamadan province.MethodsIn the observational study, the data were extracted from three sources in Hamadan, west of Iran; first, the session reports of CDCC; second, information on periodic evaluations conducted by the primary health care directory in Hamadan from April to August 2021 and third, expert panel opinion. Bayes network analysis was used to determine the effect of each policy on mortality rate by GeNIe software version 2.2.ResultsAmong the policies adopted by CDCC in Hamadan, seven policies, i.e., vaccination, limiting gatherings, social distancing, wearing a mask, job closure, travel restriction, and personal hygiene had the most impact to prevent the spread of COVID-19, respectively. In this study, the prevalence of the disease was 17.64% with the implementation of these policies. Now, if all these policies are observed 30% more, the prevalence will decrease to 14.18%.ConclusionThis study showed that if the seven policies (i.e., vaccination, limiting gatherings, social distancing, wearing a mask, job closure, travel restriction, and personal hygiene) are followed simultaneously in the community, the risk of contracting the disease will be greatly reduced. Therefore, in the pandemic of infectious diseases, such policies can help prevent the spread of the disease.

The Role of Government Expenditure on Regional Economic Resilience During Pandemic Covid-19

The GDP growth rate in the second quarter of 2020 YoY decreased by 5.32%. This contraction was triggered by the COVID-19 pandemic which had an impact on economic activities. The policy of restricting the mobility of people and the closure of various business sectors has resulted in social and economic problems. This study examines government fiscal instruments to maintain the sustainability of the public economy. The analysis used in this study is a mixed method. Empirical testing is done by using regression techniques. The research variables include regional economic performance, spending on the prevention of COVID-19, spending on social safety nets, and spending on handling economic impacts. The research is also based on a questionnaire conducted with local governments regarding health performance and economic recovery efforts. The data used is a cross-section of the period at the end of the second quarter of 2020. The test results prove that the budget reallocation used for spending on COVID-19 disease control and social safety net spending affects improving the regional economy during the study period with p-values of 0.021 and 0.000. The government, through the Sub-National Budget, continues to refocus spending for economic recovery.

Ensemble Deep Learning Derived from Transfer Learning for Classification of COVID-19 Patients on Hybrid Deep-Learning-Based Lung Segmentation: A Data Augmentation and Balancing Framework.

Lung computed tomography (CT) techniques are high-resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease control classification. Most artificial intelligence (AI) systems do not undergo generalization and are typically overfitted. Such trained AI systems are not practical for clinical settings and therefore do not give accurate results when executed on unseen data sets. We hypothesize that ensemble deep learning (EDL) is superior to deep transfer learning (TL) in both non-augmented and augmented frameworks. The system consists of a cascade of quality control, ResNet-UNet-based hybrid deep learning for lung segmentation, and seven models using TL-based classification followed by five types of EDL's. To prove our hypothesis, five different kinds of data combinations (DC) were designed using a combination of two multicenter cohorts-Croatia (80 COVID) and Italy (72 COVID and 30 controls)-leading to 12,000 CT slices. As part of generalization, the system was tested on unseen data and statistically tested for reliability/stability. Using the K5 (80:20) cross-validation protocol on the balanced and augmented dataset, the five DC datasets improved TL mean accuracy by 3.32%, 6.56%, 12.96%, 47.1%, and 2.78%, respectively. The five EDL systems showed improvements in accuracy of 2.12%, 5.78%, 6.72%, 32.05%, and 2.40%, thus validating our hypothesis. All statistical tests proved positive for reliability and stability. EDL showed superior performance to TL systems for both (a) unbalanced and unaugmented and (b) balanced and augmented datasets for both (i) seen and (ii) unseen paradigms, validating both our hypotheses.

Sanitize the Man, Sanitize the Car: COVID-19 Disease Control in Botswana

COVID-19 has dominated global health since it became a global pandemic in early 2020. It has stressed global health systems and pushed many other health concerns to the back burner. There is an urgent need to look for innovative ways to tackle the pandemic in a sustainable and transferrable manner. This article examines the COVID-19 control measures in Botswana. It describes the innovative government actions taken to control the pandemic. It also presents the observations of the authors, who have observed these actions around the country. They report on the effectiveness of the control cordon belts and the disinfection of people and animals as well as the sanitizing of objects like shoes and cars that pass across the control boundaries. Based upon the effectiveness of the control measures in Botswana, the authors recommend an innovative disease control framework for COVID-19 and other infectious diseases which they contend is replicable in other countries.

Single-centre descriptive study of adverse events reported after anti-COVID vaccination

Introduction: In Italy, approximately 80.5% of the population has completed the primary anti-COVID vaccination cycle with approximately 141 million doses administered. With the introduction of new measures to counter the spread of COVID-19, including compulsory vaccination for certain categories of people, the population expressed fears about the safety and adverse effects of SARS-CoV-2 vaccines. Several factors, such as gender and age, could have influenced the outcomes associated with the vaccine. Our single-centre work seeks to provide such evidence with respect to Pfizer/BioNTech’s BNT162b2 (Comirnaty) and AstraZeneca’s AZD1222 (Vaxzevria) vaccines. Materials and Methods: Single-centre descriptive study carried out on a sample of subjects who underwent anti-COVID vaccination at the ‘San Giovanni di Dio e Ruggi d’Aragona’ AOU vaccination centre in Salerno. Patients who reported a suspected adverse reaction after receiving a dose of vaccine were included in the study. The regional vaccine platform SORESA and the VigiFarmaco portal were used to collect the data. Results: During the period covered by the study, 126,928 doses of SARS-CoV-2 vaccine were administered. The Pfizer-BioNTech vaccine group comprised 124,138 administrations. The AstraZeneca vaccine group consisted of 2,790 administrations. 287 post-vaccination adverse reaction reports entered in the National Pharmacovigilance Network were considered. In most of the reactions reported, for both vaccines considered, the symptomatology was attributable to local reactions at the injection site. At the systemic level, however, we noted the prevalence of non-specific events such as fever, headache and diffuse arthromyalgia. Conclusions: Based on our results and comparison with the literature, the data collected on the vaccines considered in the study suggest a favourable safety profile for their large-scale use. The rate of minor adverse events turned out to be low, with similarly reassuring data compared to serious adverse events, such as not to justify hesitation towards vaccination for COVID-19 disease control.

Willingness to Accept COVID-19 Vaccine among Anaesthetists in Nigeria

Background: Critical measures in the prevention and control of COVID-19 disease require health care professionals. This study aimed to assess the willingness to accept COVID-19 vaccine among anaesthetists in Nigeria.&#x0D; Methods: A descriptive cross-sectional study involving the total population of anaesthetists in Nigeria was carried out with the use of self-administered questionnaires. Data were analyzed using IBM SPSS version 21.0 statistical software.&#x0D; Results: A total of 195 respondents were assessed during this study. All of them were aware of COVID-19 disease, 119 (61%) had a good knowledge of COVID-19 disease while 57 (29.2%) and 19 (9.7%) had fair and poor knowledge, respectively. Over half of the respondents, 103 (52.8%) were willing to accept the vaccine. Predictors of willingness to accept the vaccine included being of the male gender (AOR=2.5, 95%CI=1.213-5.246, p=0.013), being from the South-west geopolitical zone (AOR=3.134, 95% CI= 1.353- 8.651, p=0.020) and having a good knowledge of the vaccine (AOR=14.910, 95%CI=6.114-36.359, p= &lt;0.001).&#x0D; Conclusion: Slightly over half of the respondents were willing to accept COVID 19 vaccines. There is an urgent need for tertiary health institutions in Nigeria to sensitize anaesthetists especially the females on the need to accept the vaccine.

Analyzing the Effect of Filtering and Feature-Extraction Techniques in a Machine Learning Model for Identification of Infectious Disease Using Radiography Imaging

The massive adaptation of reverse transcriptase-polymerase chain reaction (RT-PCR) has facilitated efforts to battle against the COVID-19 pandemic that has inflicted millions of individuals around the world. Besides RT-PCR, radiography imaging examinations yields valuable insight for detecting and diagnosing this infectious disease. Thus, this paper proposed a computer vision and artificial-intelligence-based hybrid approach aid in efficient detection and control of COVID-19 disease. The study utilized chest X-ray images to segregate COVID-19 positive cases among healthy individuals by exploiting several combinational structures of image filtering, feature-extraction techniques, and machine learning algorithms. It analyzed the effects of three noise removal filters and two feature-extraction techniques on performance of several machine learning and deep-learning-based classifiers. The proposed schemes first remove unnecessary noise using a conservative smoothing filter, Crimmins speckle removal, and Gaussian filter. It then employs linear discriminant analysis (LDA) as linear method and principal component analysis (PCA) as non-linear feature-extraction technique to extract highly discriminant feature sets. Finally, it uses these feature sets to train various classification models, including convolutional neural network (CNN), support vector machine (SVM), and logistic regression (LG). Evidently, the proposed conservative smoothing filter with single peak to maintain symmetry in horizontal and vertical directions for enhancement of image, along with LDA and SVM, secured an overall classification accuracy of 99.93%. Experimental results show that, besides achieving high accuracies, the incorporation of feature-extraction techniques significantly reduces the computational time of the proposed model.

COVID-19 control management in central corona hospitals using SWOT and QSPM matrices: A case study in Kashan central hospitals

Background: During the COVID-19 pandemic, hospitals have been the most important centers for the virus spread. Therefore, this study aimed to evaluate the management of infection control in central corona hospitals in Kashan using the quantitative strategic planning matrix (QSPM) matrix. Methods: The existing documents studied the strengths, weaknesses, opportunities, and threats of the organization identified by environmental health experts. The internal and external factors were identified as internal factor evaluation (IFE) and external factor evaluation (EFE) matrices, respectively, then, prioritized and weighted. In the next step, the SWOT matrix was formed and the type of used strategy by the organization was determined, and solutions to improve the current situation were presented by experts. Finally, the attractiveness table was compiled and weighted using the QSPM method to prioritize the proposed strategies. Results: After identifying 25 strengths, 28 weaknesses, 15 opportunities, and 13 threats, weighting was performed, the final score for internal and external factors was 2.6475 and 2.3825, respectively. The final strategy for implementing COVID-19 disease control in the studied hospitals was the Conservative Strategy (WO). Based on this, six control strategies were presented. The priority and attractiveness of each strategy were evaluated using the QSPM matrix. Finally, the strategy of "structuring the system and providing and upgrading the equipment and infrastructure facilities" was implemented as a priority. Conclusion: According to the results, the combination of SWOT (Strengths, Weaknesses, Opportunities, and Threats) and QSPM methods can play an efficient role in identifying and evaluating the factors affecting the management of the COVID-19 pandemic in hospitals and further developing and prioritizing control strategies for this infectious disease.

Explicitly sexing health security: analysing the downstream effects of Panama's sex-segregated COVID-19 disease control policy.

In response to COVID-19, Panama implemented a sex-segregated lockdown policy whereby women were allowed to access essential services on Monday, Wednesday and Friday and men on Tuesday, Thursday and Saturday. The logic was to reduce disease transmission by controlling population circulation at any one time. We sought to understand the impact of this policy approach on Panamanian society. To do so, we undertook key informant interviews with representatives from groups of society that have been significantly affected by this policy across Panamanian society. Framework analysis was undertaken on interview transcripts to identify key trends, which were latterly triangulated with academic, media and grey literature. Firstly, we engage with intersectional analyses to show that those most affected were marginalised groups including trans population, disabled groups, indigenous groups and migrants who faced discrimination as a consequence of this policy. Secondly, we highlight practical tensions that individuals faced relating to access to resources (financial, health-related and beyond), and third we interrogate the methods used to enforce this policy, and the role of the police and exemption passes. We conclude that this policy was regressive in that it affected those most vulnerable in Panamanian society, entrenching existing inequalities. Before implementing sex-segregated policies in future health crises, governments must seek advice of gender and equality advisors and ensure impact assessments are undertaken to understand the burden such policies may pose across society.

Optimal Prevention and Treatment Control on SVEIR Type Model Spread of COVID-19

COVID-19 pandemic has disrupted the world's health and economy and has resulted in many deaths since the first case occurred in China at the end of 2019. Moreover, The COVID-19 disease spread throughout the world, including Indonesia on March 2, 2020. Coronavirus quickly spreads through droplets of phlegm through the throat to the lungs. Researchers in the medical field and the exact science are jointly examined the spread, prevention, and optimal control of COVID-19 disease. Due to the prevention of COVID-19, a vaccine has been found in early 2021, which at the time, the vaccination process was carried out worldwide against COVID-19. This paper examines the spread model of SVEIR-type COVID-19 by considering the vaccination subpopulation. In this study, control of prevention efforts ( and ) and healing efforts are given and being analyzed with the fourth-order Runge-Kutta approach. Based on numerical simulations, it can be seen that using the controls and can reduce the number of infected individuals in the subpopulation compared to those without control. The control can increase the number of recovered individual subpopulations.Keywords: COVID-19; SVEIR model; optimal control; treatment; vaccination.

Health, economic, and social implications of COVID-19 for China's rural population.

This study examines the effects of local and nationwide COVID‐19 disease control measures on the health and economy of China's rural population. We conducted phone surveys with 726 randomly selected village informants across seven rural Chinese provinces in February 2020. Four villages (0.55%) reported infections, and none reported deaths. Disease control measures had been universally implemented in all sample villages. About 74% of informants reported that villagers with wage‐earning jobs outside the village had stopped working due to workplace closures. A higher percentage of rural individuals could not work due to transportation, housing, and other constraints. Local governments had taken measures to reduce the impact of COVID‐19. Although schools in all surveyed villages were closed, 71% of village informants reported that students were attending classes online. Overall, measures to control COVID‐19 appear to have been successful in limiting disease transmission in rural communities outside the main epidemic area. Rural Chinese citizens, however, have experienced significant economic consequences from the disease control measures.

Individually optimal choices can be collectively disastrous in COVID-19 disease control

BackgroundThe word ‘pandemic’ conjures dystopian images of bodies stacked in the streets and societies on the brink of collapse. Despite this frightening picture, denialism and noncompliance with public health measures are common in the historical record, for example during the 1918 Influenza pandemic or the 2015 Ebola epidemic. The unique characteristics of SARS-CoV-2—its high basic reproduction number (R0), time-limited natural immunity and considerable potential for asymptomatic spread—exacerbate the public health repercussions of noncompliance with interventions (such as vaccines and masks) to limit disease transmission. Our work explores the rationality and impact of noncompliance with measures aimed at limiting the spread of SARS-CoV-2.MethodsIn this work, we used game theory to explore when noncompliance confers a perceived benefit to individuals. We then used epidemiological modeling to predict the impact of noncompliance on control of SARS-CoV-2, demonstrating that the presence of a noncompliant subpopulation prevents suppression of disease spread.ResultsOur modeling demonstrates that noncompliance is a Nash equilibrium under a broad set of conditions and that the existence of a noncompliant population can result in extensive endemic disease in the long-term after a return to pre-pandemic social and economic activity. Endemic disease poses a threat for both compliant and noncompliant individuals; all community members are protected if complete suppression is achieved, which is only possible with a high degree of compliance. For interventions that are highly effective at preventing disease spread, however, the consequences of noncompliance are borne disproportionately by noncompliant individuals.ConclusionsIn sum, our work demonstrates the limits of free-market approaches to compliance with disease control measures during a pandemic. The act of noncompliance with disease intervention measures creates a negative externality, rendering suppression of SARS-CoV-2 spread ineffective. Our work underscores the importance of developing effective strategies for prophylaxis through public health measures aimed at complete suppression and the need to focus on compliance at a population level.

Natural Derived Nasal Spray; A Proposed Approach for COVID-19 Disease Control.

Considering the importance of COVID-19 disease pandemic, emerged by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in line with other studies to find appropriate prevention or treatment methods for this virus infection, our study objective was proposing the use of natural derived ingredients as an approach for COVID-19 disease control. Here we reviewed previous studies on natural derived nasal sprays andfound that some known natural derived ingredients have antiviral properties, so their topical use as a nasalspray is effective in reducing the symptoms of respiratory infections. Moreover, such nasal sprays also have thepotential of decreasing viral load, including titer of coronaviruses, in the nasal cavity. It seems that the use ofcarrageenan or other herbal ingredients in the nasal spray may block the SARS-CoV-2 virus from entering thelung cells of an affected person and can also prevent virus transmission to other susceptible persons. Further,noticing what we know about the novel 2019 coronavirus so far, we suggested carrageenan that has an unspecific physical antiviral activity and some other natural derived ingredients, as a choice in coping with SARS-CoV-2 virus infection.

Effects of COVID-19 lockdown on perceived discrimination and internalized stigma in people with previous mental disorder diagnoses in Spain.

COVID-19 disease control efforts and consequences are likely to be complicated by the impact of fear and stigmatization of the novel coronavirus. These complications may also worsen due to the potential compounding of COVID-19 related stigma with stigmatization associated with previously diagnosed conditions. This exploratory study analyzes the experiences of the stigma associated with COVID-19 lockdown in people with different previous diagnoses 2 and 5 weeks after the beginning of the state of emergency in Spain. Gender and age were controlled as covariables and 1,052 people participated in the study. The diagnosis groups were: Psychiatry and mental health (n = 71), Cardiovascular disease (n = 42), Neurological disease (n = 23), Lung disease (n = 53), and No diagnosis (n = 863). The instruments used to measure the stigma were the Intersectional Day-to-Day Discrimination Index and two items of the Internalized Stigma of Mental Illness scale. Analysis of covariance of repeated measures and analysis of variance, including Scheffe's post hoc test, were performed. We found significant differences in stigma among the first and second evaluation. Regarding the previous diagnosis, no differences were found at Time 1, but significant differences were found at Time 2, with those having a previous psychiatric or mental health diagnosis reporting higher levels of perceived discrimination and internalized stigmatization. Our results suggest that people with previous stigmatizing conditions might be more vulnerable to experiencing stigma in a confinement situation. In order to reduce the burden of the COVID-19 stigma, health interventions should also consider the resulting intersection of effects on internalized stigma and perceived discrimination. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Associations Between COVID-19 Misinformation Exposure and Belief With COVID-19 Knowledge and Preventive Behaviors: Cross-Sectional Online Study.

BackgroundOnline misinformation proliferation during the COVID-19 pandemic has become a major public health concern.ObjectiveWe aimed to assess the prevalence of COVID-19 misinformation exposure and beliefs, associated factors including psychological distress with misinformation exposure, and the associations between COVID-19 knowledge and number of preventive behaviors.MethodsA cross-sectional online survey was conducted with 1049 South Korean adults in April 2020. Respondents were asked about receiving COVID-19 misinformation using 12 items identified by the World Health Organization. Logistic regression was used to compute adjusted odds ratios (aORs) for the association of receiving misinformation with sociodemographic characteristics, source of information, COVID-19 misinformation belief, and psychological distress, as well as the associations of COVID-19 misinformation belief with COVID-19 knowledge and the number of COVID-19 preventive behaviors among those who received the misinformation. All data were weighted according to the Korea census data in 2018.ResultsOverall, 67.78% (n=711) of respondents reported exposure to at least one COVID-19 misinformation item. Misinformation exposure was associated with younger age, higher education levels, and lower income. Sources of information associated with misinformation exposure were social networking services (aOR 1.67, 95% CI 1.20-2.32) and instant messaging (aOR 1.79, 1.27-2.51). Misinformation exposure was also associated with psychological distress including anxiety (aOR 1.80, 1.24-2.61), depressive (aOR 1.47, 1.09-2.00), and posttraumatic stress disorder symptoms (aOR 1.97, 1.42-2.73), as well as misinformation belief (aOR 7.33, 5.17-10.38). Misinformation belief was associated with poorer COVID-19 knowledge (high: aOR 0.62, 0.45-0.84) and fewer preventive behaviors (≥7 behaviors: aOR 0.54, 0.39-0.74).ConclusionsCOVID-19 misinformation exposure was associated with misinformation belief, while misinformation belief was associated with fewer preventive behaviors. Given the potential of misinformation to undermine global efforts in COVID-19 disease control, up-to-date public health strategies are required to counter the proliferation of misinformation.

Exploration of the Pregnant Women's Experiences During COVID-19 Disease Crisis: A Qualitative Study

Background: Prevention and control of COVID-19 disease in pregnant women has become a major concern. Healthcare providers should be aware that restriction of the routine prenatal care may have adverse effects. A qualitative approach can be helpful in understanding the pregnant women's experience and perspective in crisis. The study was conducted to explain the pregnant women's experiences during COVID-19 disease crisis. Methods: The qualitative study was conducted with conventional content analysis. Pregnant women selected with purposive sampling from six urban health centers in Babol (North of Iran). The semi structured individual interviews were done by telephone from May 03 to June 10, 2020. The systematic thematic analysis was used to identify and organize themes into clusters and categories across interviews. Findings: We recruited twelve pregnant women until data saturation. Three theme categories extracted from data analysis. The first was "unpleasant feelings during pregnancy", the pregnant women stated feelings in this crisis such as worry, fear, obsession, boredom, nervousness, discouragement, and the like, which led them to have no positive pregnancy experience. The second category was "adjusted lifestyle". They experienced changes in lifestyle with the aim of preventing COVID-19 disease. The third category was “safe pregnancy care”. The pregnant women, while paying attention to the importance of pregnancy care, were forced to limit, delay, or modify some cares in order to be safe. Interpretation: The pregnant women experienced unpleasant feelings in this crisis; therefore, they should receive the necessary consulting to maintain mental health. All pregnant women reported some changes in their lifestyle and pregnancy care in order to health considerations to prevent the disease. Regular training for all pregnant women is necessary to manage this important pregnancy period while maintaining the maternal and fetal health in crisis.Funding Statement: This project was supported by Babol University of Medical Sciences.Declaration of Interests: The authors declare that have no competing interests.Ethics Approval Statement: This research was approved by Ethics Committee of Babol University of Medical Sciences (IR.MUBABOL.REC.1399.110).

Mental Health Concerns of Frontline Workers During the COVID-19 Pandemic: A Scoping Review

OBJECTIVES: The current COVID-19 pandemic continues to have a significant impact on the mental health of frontline workers worldwide. Currently there are limited published studies addressing mental health issues in frontline workers. The objective of this scoping review is to examine the range of existing global literature on mental health issues reported in frontline workers during the COVID-19 pandemic and to understand what mitigating factors exist.&#x0D; &#x0D; METHODS: The scoping review was guided by the Levac Colquhoun and O&amp;rsquo;Brien&amp;rsquo;s adapted version of Arkey and O&amp;rsquo;Malley&amp;rsquo;s framework. We performed a comprehensive search of three databases, Pubmed, APA PsychINFO, and CINAHL, identifying 684 studies. In total, 16 original studies and 4 letters to editors were included in this review.&#x0D; &#x0D; RESULTS: Of the original studies, 13 were published in China, and the remaining 3 in Italy, Turkey, and Iraq; all letters to editors were published in China. Sources of stress reported in frontline workers across studies included direct contact with COVID-19 patients, isolation, putting loved ones at risk, facing life and death decision making with COVID-19 patients, uncertainty with COVID-19 disease control, limited personal protective equipment, time spent thinking about COVID-19, limited staff/resources/pay, burnout, and stigma. Mental health symptoms and outcomes reported in frontline workers were fear, stress, anxiety, depression, insomnia, burnout, and psychological distress.&#x0D; &#x0D; CONCLUSION: Findings demonstrate the immediate need to increase mental health awareness and resources at an individual and system wide level. Mental health programs need to be catered towards each unique workplace to provide the necessary resources for frontline workers.