A Shuffling Building Block and Augmentation Parameter Tuning Techniques to Handle Small Medical Dataset

The recent COVID-19 outbreak showed us the importance of faster disease diagnosis using medical image processing as it is considered the most reliable and accurate diagnostic tool. In a CNN architecture, performance improves with the increasing number of trainable parameters at the cost of processing time. We have proposed an innovative approach of combining efficient novel architectures like Inception, ResNet, and ResNet-Xt and created a new CNN architecture that benefits Extreme Cardinal dimensions. We have also created four variations of the same base architecture by varying the position of each building block and used X-Ray, Microscopic, MRI, and pathMNIST datasets to train our architecture. For learning curve optimization, we have applied learning rate changing techniques, tuned image augmentation parameters, and chose the best random states value. For a specific dataset, we reduced the validation loss from 0.22 to 0.18 by interchanging the architecture's building block position. Our results indicate that image augmentation parameters can help to decrease the validation loss. We have also shown rearrangement of the building blocks reduces the number of parameters, in our case, from 5,689,008 to 3,876,528. © 2023 IEEE.

Impact of supplemental vitamins and natural honey for treatment of COVID-19: A review

Abstract The main aim of the paper is to assess whether vitamin C, vitamin D, and natural honey can be administered in the course of the COVID-19 pandemic for promising in line methods with recent evidence. Both systematic literature and clinical trial identification were conducted by searching various databases. A total 58 articles and 29 clinical trials were selected wherein 11 for vitamin C, 16 for vitamin D, and 2 for natural honey were identified for analysis. The high doses of vitamin C (i.e. '200 mg/kg body weight/day, divided into 4 doses') has been found to reduce COVID-19 lung damage, various flu infections. Additionally, the high doses of vitamin C can shorten around 7.8% stay in the intensive care unit. At the same time, vitamin D can effectively protect from lung injury and acute respiratory infections whereas vitamin D deficiency severely affects 75% of the institutionalized people (serum 25(OH) D < 25 nmol/L). Meanwhile, natural honey which contains proteins (0.1-0.4%); ash (0.2%); water (15-17%) has potential antiviral effects and the ability to improve immunity. Therefore, the administration of vitamins and honey is the promising evidence-based approach for reducing fatalities, saving lives, and bringing the COVID-19 pandemic to a rapid end. It is believed that the utilization of vitamin C, vitamin D, and natural honey with the current treatment may be effective in treating COVID-19-caused fatal complications such as pneumonia. Therefore, high-level clinical studies are required on COVID-19 to administrate the effects of vitamins and natural honey.

COVID-19 Chest X-Ray Classification with Augmented GAN

Coronavirus disease (COVID-19) is a major concern now. According to the Globe Health Organization, the coronavirus (COVID-19) epidemic is straining healthcare systems worldwide (WHO). Early-stage detection using artificial intelligence of this virus will help in the fast recovery. Early identification of this infection utilizing artificial intelligence will aid in its quick recovery. In the fight against COVID-19, it’s critical to have a positive chest X-ray for infected patients. Early research suggests that chest X-ray abnormalities in COVID-19 patients are common. Using augmented chest X-ray images, this research proposes a novel model for identifying the presence of COVID-19. As medical images are sensitive, GAN (Generative Adversarial Networks) augments chest X-Ray images. Augmented images are classified through our proposed model. Then classified images are segmented for validation. GAN augmentation model consists of a generator and a discriminator. Convolutional neural networks (CNNs) based classification model needs a substantial amount of training data. Augmentation increased dataset into 10x amount. Before augmentation, our initial model received 94.42% accuracy, and after augmentation, our final model accuracy raised to 98.58%. We hope our model will detect COVID-19 presence accurately through X-Ray images. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Euphorbia neriifolia Leaf Juice on Mild and Moderate COVID-19 Patients: Implications in OMICRON Era

Coronavirus disease-2019 (COVID-19) has shattered the public health delivery system of most of the countries of the world. COVID-19 displays variable clinical presentations. The severe COVID-19 represents a fulminant pathological condition and most of the patients run a downhill course if extensive medical measures are not adopted. The major challenges about COVID-19 are related to develop strategies to manage huge populations of mild and moderate cases of COVID-19 with two realistic purposes: (1) early negativity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and (2) arrest of progression of moderate COVID-19 patients from developing severe complications. Although several medications have been repurposed for these purposes, none of these have passed the test of time in global perspective. Thus, there remains a pressing need to develop new and novel innovative management strategies for these patients as new variants of SARS-CoV-2 have been destroying the normal public health delivery system of different countries from time to time. The study presented here has checked the safety and efficacy of a herbal medication, leaves of Euphorbia neriifolia Linn (E. neriifolia), in mild and moderate COVID-19 patients. Sixty patients (30 mild COVID-19 and 30 moderate COVID-19) were enrolled in the study. Fifteen mild COVID-19 patients received standard of care (SOC) management, and the remaining 15 patients received SOC plus E. neriifolia. The moderate COVID-19 patients similarly received either SOC (N = 15) or SOC plus E. neriifolia (N = 15). Although there were marked diversity regarding biochemical parameters of these patients at entry, the moderate COVID-19 patients receiving E. neriifolia showed decrease in C-reactive protein and D-dimer and increase in oxygen saturation 7 days after trial commencement. However, these improvements were not detected in moderate COVID-19 patients receiving SOC. Hospital staying was significantly lower in both mild and moderate COVID-19 patients receiving SOC plus E. neriifolia than those receiving only SOC. Taken together, it may be proposed that usage of E. neriifolia may have beneficial effects regarding management for COVID-19 patients, especially for those in developing and resource-constrained countries, although a conclusive statement may not be given due to small sample size. This herbal medication is also pertinent in the context of emergence of OMICRON variant of COVID-19 as the overload of SARS-CoV-2-infecetd patients may be addressed considerably by this medication without hospitalization, if proper communication between patients and physicians can be ensured. How to cite this article Pramanik MEA, Miah MMZ, Ahmed I, et al. Euphorbia neriifolia Leaf Juice on Mild and Moderate COVID-19 Patients: Implications in OMICRON Era. Euroasian J Hepato-Gastroenterol 2022;12(1):10–18.

A Systematic Review on the Use of AI and ML for Fighting the COVID-19 Pandemic.

Artificial intelligence (AI) and machine learning (ML) have caused a paradigm shift in healthcare that can be used for decision support and forecasting by exploring medical data. Recent studies have shown that AI and ML can be used to fight COVID-19. The objective of this article is to summarize the recent AI- and ML-based studies that have addressed the pandemic. From an initial set of 634 articles, a total of 49 articles were finally selected through an inclusion-exclusion process. In this article, we have explored the objectives of the existing studies (i.e., the role of AI/ML in fighting the COVID-19 pandemic); the context of the studies (i.e., whether it was focused on a specific country-context or with a global perspective; the type and volume of the dataset; and the methodology, algorithms, and techniques adopted in the prediction or diagnosis processes). We have mapped the algorithms and techniques with the data type by highlighting their prediction/classification accuracy. From our analysis, we categorized the objectives of the studies into four groups: disease detection, epidemic forecasting, sustainable development, and disease diagnosis. We observed that most of these studies used deep learning algorithms on image-data, more specifically on chest X-rays and CT scans. We have identified six future research opportunities that we have summarized in this paper. Impact Statement: Artificial intelligence (AI) and machine learning(ML) methods have been widely used to assist in the fight against COVID-19 pandemic. A very few in-depth literature reviews have been conducted to synthesize the knowledge and identify future research agenda including a previously published review on data science for COVID-19 in this article. In this article, we synthesized reviewed recent literature that focuses on the usages and applications of AI and ML to fight against COVID-19. We have identified seven future research directions that would guide researchers to conduct future research. The most significant of these are: develop new treatment options, explore the contextual effect and variation in research outcomes, support the health care workforce, and explore the effect and variation in research outcomes based on different types of data.

How to explain AI systems to end users: a systematic literature review and research agenda

Purpose>Inscrutable machine learning (ML) models are part of increasingly many information systems. Understanding how these models behave, and what their output is based on, is a challenge for developers let alone non-technical end users.Design/methodology/approach>The authors investigate how AI systems and their decisions ought to be explained for end users through a systematic literature review.Findings>The authors’ synthesis of the literature suggests that AI system communication for end users has five high-level goals: (1) understandability, (2) trustworthiness, (3) transparency, (4) controllability and (5) fairness. The authors identified several design recommendations, such as offering personalized and on-demand explanations and focusing on the explainability of key functionalities instead of aiming to explain the whole system. There exists multiple trade-offs in AI system explanations, and there is no single best solution that fits all cases.Research limitations/implications>Based on the synthesis, the authors provide a design framework for explaining AI systems to end users. The study contributes to the work on AI governance by suggesting guidelines on how to make AI systems more understandable, fair, trustworthy, controllable and transparent.Originality/value>This literature review brings together the literature on AI system communication and explainable AI (XAI) for end users. Building on previous academic literature on the topic, it provides synthesized insights, design recommendations and future research agenda.

Impact of COVID-19 on Small- and Medium-sized Enterprises

The COVID-19 pandemic has severely impacted global business operations. Most importantly, practitioners of small- and medium-sized enterprises (SMEs) have been facing devastating economic shocks emanated from the COVID-19 pandemic. The purposes of this study are to explore the business status of SMEs, business sustenance period, types of problems faced by the practitioners and impact on production volume, due to the COVID-19 pandemic. For these purposes, primary survey data from 284 SMEs in Bangladesh are collected in this study. The survey data are descriptively analyzed using appropriate graphs. This study finds that SMEs are facing several problems such as demand fall (92.96%), cancellation of orders (85.56%), liquidity crisis (74.30%), delayed transportation (72.53%), unsecured working environment (68.31%), raw material shortage (63.73%) and employees? absenteeism (62.67%). The SMEs face beyond 40% decrease in production volume against the pre-pandemic year. Furthermore, this study formulates several strategic measures, which will certainly guide policymakers and practitioners to combat the COVID-19 economic shocks for the SMEs and also for other industries.

Coping with pandemics using social network sites: A psychological detachment perspective to COVID-19 stressors.

Prior research has often portrayed information technology (IT) as a stressor. In this paper, we propose and demonstrate that IT can also be an effective means of coping with life stressors, including those induced by pandemics such as COVID-19. We thus deviate from the common IT-as-a-stressor perspective and adopt an IT-as-a-coping-mechanism viewpoint. To this end, we apply the stressor-detachment model from organisational psychology to the use of social network sites (SNSs) in coping with stressors wrought by the COVID-19 pandemic. We examine psychological well-being as our dependant variable and introduce psychological detachment through SNS use as a mediator and moderator of the associations between psychological well-being and two COVID-19 stressors: work-family conflict and perceived isolation. We used structural equation modelling and tested this model with survey data collected from 398 professionals who were in lockdown and working from home during the pandemic. The results indicated that psychological detachment through SNS uses increased psychological well-being and that heightened work-family conflict motivated this detachment strategy. In contrast, consistent with helplessness and motivation-opportunity theories, perceived isolation as a stressor did not influence psychological detachment through SNS use. While perceived isolation directly reduced individual well-being, the effect of work-family conflict on well-being was contingent upon users' levels of psychological detachment through SNS use. These findings suggest that while psychological detachment through SNS use is an effective means of improving one's well-being, it can be positively or negatively affected by stressors. Our study contributes to research on technology-mediated strategies for coping with stress and the psychosocial implications of global pandemics.

A review of clinical management practice of COVID-19 in South Asian countries: systematic review

Our world is currently fighting with highly infectious and deadly severe acute respiratory syndrome-coronavirus-2 virus which has no specific remedy yet. No study focused on reviewing applied clinical management and treatment protocol of coronavirus disease-2019 (COVID-19) by health ministry of different nations till date. Therefore, this study focuses to identify and compare clinical management and treatment protocol guidelines for COVID-19 from 8 South Asian countries. This study will assist the healthcare workers and authorities of different nations by sharing the key information from potential guidelines to treat COVID-19 patients. Necessary information has been collected from the clinical management guidelines for COVID-19 in Health Ministry website of India, Bangladesh, Sri Lanka, Pakistan, Afghanistan, Nepal, Bhutan, and Maldives. Though clinical management practices vary from country to country, all of these countries are utilizing high flow oxygen therapy and mechanical ventilation for critical cases. Moreover, some potential drugs have been suggested for treatment by most of the countries but were not recommended yet as all of them are under clinical trials. Hydroxychloroquine has been suggested by most of these countries. All the countries are developing and updating their guidelines for clinical management of COVID-19 patients. It is worth mentioning that the recovery rate of Bangladesh, India, Sri Lanka, Pakistan, Afghanistan, Nepal, Bhutan, and Maldives is 63.52%, 76.24%, 94.88%, 94.47%, 83.65%, 71.5%, 71.14%, and 83.83% respectively. The oxygen therapy and empirical antibiotic for preventing secondary infection have been used commonly in most of these countries as an effective treatment.

Evaluation of outcome of Coronavirus disease 2019 patients receiving RAAS inhibitors (OCRAS study): A prospective observational study of Bangladeshi hypertensive patients

Background: The fact that SAARS-Cov2 virus enters cells through ACE2 receptors and the Renin-Angiotensin-Aldosterone System Inhibitors (RAASi) upregulate the ACE2 receptors, there was speculation that use of RAASi may lead increased cellular entry of the virus. There was a pause for a brief period of the use of RAASi in COVID 19 patients. But clinically the speculation has been found to be incorrect. Different professional societies come up with the assertion to continue to use RAASi. As the hesitancy among the clinicians appears to continue and there is no first hand data regarding the safety of the use of RAASi in Bangladeshi population, the study was undertaken to evaluate the safety of RAASi in COVID 19 patients. Aims & Methods This study was a prospective, observational multi-center study to evaluate the outcome of COVID-19 patients receiving RAAS inhibitors. Adult Hypertensive patients (age ≥18 years) with diagnosed COVID-19 confirmed by RT-PCR test who have a history of taking either ACE inhibitor/ARB or any other anti-hypertensive medication. Evaluation of outcome was assessed by rate of hospitalization, requirement of oxygen therapy, requirement of high flow nasal cannula, admission to ICU and mortality between two groups. All statistical analyses were performed using SPSS for Windows, version 20.0 (SPSS Inc., Chicago, IL, USA). Results: We collected data from 147 Covid-19 positive patients confirmed by RT-PCR. Among them, 117 (79.6%) had a history of taking RAAS inhibitor and 30 had history of taking other antihypertensive medications. Of them, two-third patients had more than 50 years of age and more than half of the patients had overweight or obesity. Other than hypertension they had several comorbidities such as Diabetes Mellitus (45.4%), Ischemic Heart Diseases (35.4%), Asthma or COPD (15%) etc. Rate of hospitalization had no statistical difference between RAAS inhibitor group and other hypertensive group (48.7% vs 46.70% respectively;p-value-0.841). There was no statistical difference between two groups in terms of requirement of oxygen therapy (p-value-0.297), High Flow Nasal Cannula (p-value-0.430), intensive care unit (p-value-0.194) and death (p-value-0.383) also. Almost half and one-third of the patients had persistence of symptoms even after 14 days and 28 days respectively. Fatigue, cough, breathlessness, loss of appetite and taste were the most common symptoms among those. Conclusion: In our study we found that RAAS inhibitor treatment had no adverse effect on the outcome of COVID-19 patients compared with other antihypertensive drugs. Patients may continue receiving ACEIs and ARBs for the treatment of any indication for RAASi without an increased risk of worse outcomes.

Clinical Consequences and Economic Burden Associated with Febrile Neutropenia in Hospitalized Cancer Patients: A Prospective Study

Objective: Febrile neutropenia (FN) is viewed as the most decimating oncological crisis particularly in chemotherapy-incited patients. The primary objective of the study was to identify the total direct expenditure of patients during febrile neutropenia with clinical consequences and the secondary aim was to find out the factors associated with higher cost. Materials and Method: This was a single-centered hospital-based study in the largest and only specialized cancer care centre in Bangladesh in the government sector. This prospective study was done in the inpatients’ department of the National Institute of Cancer Research and Hospital from April 2020 to January 2021. The primary outcome was the out-of-pocket patient payments (adjusted by government subsidy) per FN episode. Univariate analysis and multiple linear regression were conducted to identify the factors associated with higher costs. Results and Discussions: A total of 101 patients were enrolled in the study. The mean (SD) age was 33.49 (±15.79) years. Of the 101 participants, 63.4% were male.Among the patients, 13.9% died during the episode and 86.1% recovered. Having co-morbidities and COVID-19 were associated with an increased risk of death. The mean cost was US$ 999.44 (±499.05) and the mean length of hospital stay was 21.98 (±9.3) days. The longer hospital stay was significantly associated with higher costs. Conclusion: This study will help to ascertain the hospital cost and clinical outcome of FN which ultimately can help in policymaking strategy.

A Review on the Mobile Applications Developed for COVID-19: An Exploratory Analysis.

The objective of this research is to explore the existing mobile applications developed for the COVID-19 pandemic. To obtain this research objective, firstly the related applications were selected through the systematic search technique in the popular application stores. Secondly, data related to the app objectives, functionalities provided by the app, user ratings, and user reviews were extracted. Thirdly, the extracted data were analyzed through the affinity diagram, noticing-collecting-thinking, and descriptive analysis. As outcomes, the review provides a state-of-the-art view of mobile apps developed for COVID-19 by revealing nine functionalities or features. It revealed ten factors related to information systems design characteristics that can guide future app design. The review outcome highlights the need for new development and further refinement of the existing applications considering not only the revealed objectives and their associated functionalities, but also revealed design characteristics such as reliability, performance, usefulness, supportive, security, privacy, flexibility, responsiveness, ease of use, and cultural sensitivity.

Application of Internet of Things for Early Detection of COVID-19 using Wearables

As the latest pandemic spreads, the world's governing bodies have been forced to impose strict social distancing measures. This has impacted businesses and manufacturing industries worldwide, including Bangladesh's RMG sector. To aid in the rapid spread of this infectious disease, this paper illustrates a simulation of an IoT system centered on wristbands specifically designed to detect early symptoms of COVID-19 (SARS-CoV-2). The system, which includes a facemask detection system and a thermal camera, identifies potential employees who may be at risk of contracting the COVID-19 virus. We simulated the wristband system using a simulation software in order to conduct a few test cases to ensure its feasibility. The wristbands' results were largely consistent with expectations, demonstrating their ability to monitor a wearer's vitals throughout the day. When combined with an attendance system and a face mask detection system, the wristband system enables a workplace to track its employees and detect possible infected workers. © 2021 IEEE.

Adverse consequences of emotional support seeking through social network sites in coping with stress from a global pandemic.

This study explores how using social networking sites (SNSs) to cope with stressors induced by a global pandemic (in this case, COVID-19) can have negative consequences. The pandemic has imposed particular stressors on individuals, such as the threats of contracting the virus and of unemployment. Owing to the lockdowns and confinements implemented to limit the spread of the pandemic, SNS use has surged worldwide. Drawing on Lazarus and Folkman's theory of stress and coping, we consider COVID-19 obsession to be an adverse emotional response to the stressors brought about by the pandemic and emotional support seeking through SNS as a coping strategy. Furthermore, we identify SNS exhaustion as an adverse outcome of this form of coping. Finally, we analyze the intention to reduce SNS use as a corrective behavioral outcome to mitigate the negative effect of SNS-mediated coping. The findings indicate that: 1) the threat of the COVID-19 disease and the threat of unemployment drive COVID-19 obsession; 2) COVID-19 obsession contributes to emotional support seeking through SNS; 3) emotional support seeking through SNS exerts a positive effect on SNS exhaustion; 4) SNS exhaustion contributes to the intention to reduce SNS use. Our results advance Information Systems (IS) research by focusing on the use of Information Technology (IT) to cope with stressors that are essentially not IT-related; such research is largely absent from previous literature. Furthermore, our paper contributes to the increasing amount of literature on IT-mediated coping with stressors and reduced social media use.

Towards a GDPR-Compliant Blockchain-Based COVID Vaccination Passport

The COVID-19 pandemic has shaken the world and limited work/personal life activities. Besides the loss of human lives and agony faced by humankind, the pandemic has badly hit different sectors economically, including the travel industry. Special arrangements, including COVID test before departure and on arrival, and voluntary quarantine, were enforced to limit the risk of transmission. However, the hope for returning to a normal (pre-COVID) routine relies on the success of the current COVID vaccination drives administered by different countries. To open for tourism and other necessary travel, a need is realized for a universally accessible proof of COVID vaccination, allowing travelers to cross the borders without any hindrance. This paper presents an architectural framework for a GDPR-compliant blockchain-based COVID vaccination passport (VacciFi), whilst considering the relevant developments, especially in the European Union region.

The mechanism and the management strategy of COVID-19 associated thromboembolic manifestations

Objectives: Severe acute respiratory syndrome corona virus 2 (SARS-COV-2) is a recently known zoonotic coronavirus that has devastated the whole world. The objective of this review paper is to find out the available information related to COVID-19 infection and thromboembolism. This would help build better understanding of the pathophysiology and effective management strategy of thromboembolism in COVID-19 patients. Data sources: A few articles are available on printed versions, but many more are available online versions or in the pipeline. We used various search engines to find out COVID-19 and thromboembolism related articles. Study selection: The papers depicting various aspects of COVID-19 and thromboembolism have been selected and analyzed. Their core messages have been extracted and compiled. Data extraction: Data have been collected from the articles available from MEDLINE and Google Scholar up to July, 2020. We also gathered information from doctors involved in the treatment of the COVID patients. Data synthesis: Information on relationship between COVID-19 and thromboembolism has been collected. In addition, there have been reports of many sudden deaths attributed to deadly cardiac arrythmia and increased thromboembolic manifestation. A higher risk of vessel thrombosis has been correlated with severity of the disease and multiorgan involvement. Conclusions: COVID-19 appears to be associated with thrombosis in general, both venous and arterial. These patients have increased risk of thromboembolism due to infection related inflammation, immobility and hypercoagulable state. Adequate thromboprophylaxis should be administered in all moderate to severe COVID-19 patients including patients of comorbidity and aged patients.

Understanding the impact of information sources on COVID-19 related preventive measures in Finland.

The COVID-19 pandemic amplified the influence of information reporting on human behavior, as people were forced to quickly adapt to a new health threatening situation by relying on new information. Drawing from protection-motivation and cognitive load theories, we formulated a structural model eliciting the impact of the three online information sources: (1) social media, (2) official websites, and (3) other online news sources; on motivation to adopt recommended COVID-19 preventive measures. The model was tested with the data collected from university employees and students (n = 225) in March 2020 through an online survey and analyzed using partial least square structural equation modeling (PLS-SEM). We observed that social media and other online news sources increased information overload amongst the online information sources. This, in turn, negatively affected individuals' self-isolation intention by increasing perceived response costs and decreasing response efficacy. The study highlights the role of online information sources on preventive behaviors during pandemics.

Undiagnosed SARS-CoV-2 infection and outcome in patients with acute MI and no COVID-19 symptoms.

OBJECTIVE: We aimed to determine the prevalence and outcome of occult infection with SARS-CoV-2 and influenza in patients presenting with myocardial infarction (MI) without COVID-19 symptoms. METHODS: We conducted an observational study from 28 June to 11 August 2020, enrolling patients admitted to the National Institute of Cardiovascular Disease Hospital, Dhaka, Bangladesh, with ST-segment elevation MI (STEMI) or non-ST-segment elevation MI who did not meet WHO criteria for suspected COVID-19. Samples were collected by nasopharyngeal swab to test for SARS-CoV-2 and influenza virus by real-time reverse transcriptase PCR. We followed up patients at 3 months (13 weeks) postadmission to record adverse cardiovascular outcomes: all-cause death, new MI, heart failure and new percutaneous coronary intervention or stent thrombosis. Survival analysis was performed using the Kaplan-Meier method. RESULTS: We enrolled 280 patients with MI, 79% male, mean age 54.5±11.8 years, 140 of whom were diagnosed with STEMI. We found 36 (13%) to be infected with SARS-CoV-2 and 1 with influenza. There was no significant difference between mortality rate observed among SARS-CoV-2 infected patients compared with non-infected (5 (14%) vs 26 (11%); p=0.564). A numerically shorter median time to a recurrent cardiovascular event was recorded among SARS-CoV-2 infected compared with non-infected patients (21 days, IQR: 8-46 vs 27 days, IQR: 7-44; p=0.378). CONCLUSION: We found a substantial rate of occult SARS-CoV-2 infection in the studied cohort, suggesting SARS-CoV-2 may precipitate MI. Asymptomatic patients with COVID-19 admitted with MI may contribute to disease transmission and warrants widespread testing of hospital admissions.

Can COVID-19 Change the Big5 Personality Traits of Healthcare Workers?

To curb the spread of the coronavirus, authorities around the world implemented lockdown measures for months. In these locked down days, people as well as healthcare workers (HWs) are increasingly relying on social media platforms to socialize among themselves and get the latest updates of this pandemic situation. As a result, social media users' interaction data have become a key resource in analyzing their behaviors. COVID-19 is the first global pandemic in the global scale after the appearance of social media. HWs such as physicians, nurses, technicians, and hospital support staff provide essential services to the patients with COVID-19 even after having lack of sufficient equipment, poor preparation, and risking their own lives. These HWs may experience sudden change in their personality traits due to pandemic, which are not studied in the existing literature. In this paper, we investigate how the pandemic influences Big5 personality traits of HWs using social media data. Our analysis shows that HWs' neuroticism, conscientiousness, and extroversion have increased significantly due to pandemic. In contrast, we observe a decrease of HWs' agreeableness and openness dimensions of Big5 personality. © 2020 ACM.