Early COVID-19 Outbreak Research Articles

Loneliness and Mental Health in Response to Early and Late COVID-19 Outbreak: A Cross-Sectional Study of Czech Adults Aged 50 and Over.

The unpredictable spread of the COVID-19 pandemic, national lockdowns, and public health measures implemented in the Czech Republic had a negative effect on older adults' mental health and loneliness. The 2,631 older adults in 2020 and 2,083 older adults in 2021 used in this study formed a nationally representative sample of the Survey of Health, Ageing and Retirement in Europe (SHARE). Almost every third older adult experienced feelings of loneliness in both stages of the COVID-19 outbreak. Loneliness increased in 2021 in those individuals who reported their physical health as poor, who felt nervous, sad or depressed, and who had ever left their home since the outbreak. According to age-related drivers of loneliness, feelings of loneliness were prevalent (40% vs. 45%) among younger retirees in both waves. In both data sets, declared feelings of sadness or depression were the strongest sustainable predictor of loneliness (2020 and 2021 models, OR = 3.69; 95% CI [2.90, 4.69] and OR = 2.55; [1.97, 3.30]). Being a woman and feeling nervous equated with a higher likelihood of feeling lonely compared to counterparts. Policy makers should therefore aim to carefully improve psychosocial and health-related consequences faced by this vulnerable population during the pandemic and beyond.

Evaluating the efficiency and productivity of Malaysian logistics companies using epsilon-based measure and Malmquist index during the Covid-19 pandemic

Purpose: The impact of the Covid-19 outbreak since March 2020 has put Malaysia’s logistics sector in a contrasting reality to other sectors, as during the implementation of the movement control order (MCO), this sector was declared as providing essential service and allowed to operate in order to fulfil customers’ needs. This study aims to assess the efficiency and productivity of the logistics industry in Malaysia before and during the pandemic so that the performance of this industry can be observed.Design/methodology/approach: This study uses secondary data. Yearly records from the annual reports for the period of 2010–2020 were gathered pertaining to 15 Malaysian logistics companies treated as decision making units (DMUs) in this study. The efficiency and productivity of the Malaysian logistics industry during the Covid-19 pandemic have been assessed by using a hybrid DEA model consisting of a combination of epsilon-based measure (EBM) and Malmquist index.Findings: Findings showed that Lingkaran Trans Kota Holdings Berhad was the most efficient and productive logistics company with an average efficiency score of 1 and 12.7% growth in the average productivity index during the study period. In contrast, MISC Berhad obtained the lowest average efficiency score of 0.285. Nevertheless, the average productivity index for MISC Berhad showed an increase by 25.7%. During the early outbreak of Covid-19, Complete Logistics Services Berhad achieved full efficiency and also attained the highest positive growth of 76.2%. Harbour-Link Group Berhad was the least efficient company, scoring an efficiency score of only 0.254 and a decline in productivity growth by 40.8%.Research limitations/implications: The data used in this study may not be sufficient to represent the performance of the entire logistics industry as the pandemic is still not completely over. More useful insights can be obtained if the data can be extended until 2022 to assess the performance of logistics companies after the outbreak of Covid-19 in Malaysia. Many resources that have not been explored in this study and past research may provide an avenue for further research on the performance measurement of logistics companies, particularly in the Malaysian context.Practical implications: This study’s discovery may be used to facilitate the evaluation of resource utilisation and help inefficient logistics companies maximise their efficiency. Also, the findings may be used to help policymakers evaluate the existing policy in order to ensure that logistics companies have sufficient resources to offer reliable and efficient courier services.Originality/value: Although numerous studies have been conducted on the efficiency measurement of logistics companies, so far, scarce research in Malaysia has deployed a quantitative approach to measure the performance of Malaysia’s logistics industry, especially during the Covid-19 pandemic. Therefore, this study fills this gap by assessing the efficiency and productivity of the logistics industry in Malaysia before and during the pandemic of Covid-19.

Digital Merit: A Case Study of a Chinese Buddhist Meditation Group on WeChat During the Early Outbreak of Covid-19 in China

ABSTRACT While most academics regard virtual religious communities to be secondary to in-person religious communities, the virtual Buddhist sangha served as a full and complete social infrastructure that provides purpose to life and spiritual consolation to its members. From the outbreak of the Covid-19 from March to May in 2020, this paper investigates how a Chinese Buddhist group based in Beijing practices Theravada meditation on the WeChat social media platforms. This paper, based on online ethnography and informal interviews, argues that digital media is a significant arena for Chinese Buddhists to conduct Buddhist rituals, transmit Buddhist ideas, generate and accumulate Buddhist merits, and build alternative cyber-Buddhist economies. This paper also highlights that Buddhist groups are continuously growing and rising as highly united and community-oriented digital sanghas within current China’s technoculture context.

Does sleep disturbance predicts posttraumatic stress disorder and depression among college students during COVID-19 lockdown? A longitudinal survey.

AimTo examine the cross-sectional and longitudinal associations between self-reported sleep disturbances, posttraumatic stress disorder (PTSD) and depression in a large cohort of Chinese adolescents experiencing the COVID-19 pandemic.MethodsParticipants were 67905 Chinese college students in the two-wave longitudinal web-based survey during early COVID-19 outbreak (Time1, T1: Feb 3rd to 10th, 2020) and initial remission period (Time2, T2: March 24th to April 3rd, 2020). The Youth Self Rating Insomnia Scale (YSIS), 6-Item Impact of Event Scale (IES-6), and 9-Item Patient Heath Questionnaire (PHQ-9) were used to assess adolescents' sleep, PTSD, and depressive symptoms, respectively, at T1 and T2.ResultsSelf-reported PTSD and depression prevalence at T1 were 34.6% and 21.6% respectively. While depressive symptoms worsened as the lockdown time increased, while PTSD symptoms decreased. After adjusting for confounding factors, sleep disturbance and sleep deprivation at T1 were significantly associated with increased PTSD and depressive symptoms at T2. Furthermore, sleep disturbance and sleep deprivation also predicted the new onset and persistence of PTSD and depression.ConclusionSleep disturbance predicts the development and persistence of PTSD and depression. Early assessment and treatment of sleep disturbance may be an important strategy for prevention and intervention of PTSD and depression in adolescents after experiencing the special public health emergency.

A SURVEY ON RESPONSES OF COTTAGE, MICRO AND SMALL ENTERPRISES SECTOR DURING COVID-19 IN BANGLADESH

This study examines the short-term impact of COVID-19 restrictions on small-sized enterprises based on phone and social media interviews. This research aimed to study Cottage, Micro, and Small Enterprises (CMSEs) during the covid-19 pandemic and analyze the policy measures taken afterwards. Affected by problems of logistics challenges, labour shortages, and drops in demand, most Small and Medium Enterprises (SMEs) were temporarily closed at the time of the first wave of covid-19 during our survey. We found several challenges encountered by the CMSEs owners during the early outbreak of Covid-19. This study used a descriptive analysis method of primary data obtained directly from field surveys and secondary data from Bangladesh Bank and SME foundation. This study focuses on the Dhaka city area during the Covid-19 pandemic. After reining in COVID-19, authorities eased lockdown restrictions in August 2020, and most of the small businesses had reopened by this time. Considering their issues and problems, the Government of Bangladesh and Bangladesh Bank have taken several policy measures to mitigate the loss of SME owners during the pandemic. These policies are also mentioned at the end of the study.

Early-stage COVID-19 pandemic observations on pulmonary embolism using nationwide multi-institutional data harvesting

We introduce a multi-institutional data harvesting (MIDH) method for longitudinal observation of medical imaging utilization and reporting. By tracking both large-scale utilization and clinical imaging results data, the MIDH approach is targeted at measuring surrogates for important disease-related observational quantities over time. To quantitatively investigate its clinical applicability, we performed a retrospective multi-institutional study encompassing 13 healthcare systems throughout the United States before and after the 2020 COVID-19 pandemic. Using repurposed software infrastructure of a commercial AI-based image analysis service, we harvested data on medical imaging service requests and radiology reports for 40,037 computed tomography pulmonary angiograms (CTPA) to evaluate for pulmonary embolism (PE). Specifically, we compared two 70-day observational periods, namely (i) a pre-pandemic control period from 11/25/2019 through 2/2/2020, and (ii) a period during the early COVID-19 pandemic from 3/8/2020 through 5/16/2020. Natural language processing (NLP) on final radiology reports served as the ground truth for identifying positive PE cases, where we found an NLP accuracy of 98% for classifying radiology reports as positive or negative for PE based on a manual review of 2,400 radiology reports. Fewer CTPA exams were performed during the early COVID-19 pandemic than during the pre-pandemic period (9806 vs. 12,106). However, the PE positivity rate was significantly higher (11.6 vs. 9.9%, p < 10−4) with an excess of 92 PE cases during the early COVID-19 outbreak, i.e., ~1.3 daily PE cases more than statistically expected. Our results suggest that MIDH can contribute value as an exploratory tool, aiming at a better understanding of pandemic-related effects on healthcare.

Changes in Canadian Adolescent Time Use and Movement Guidelines During the Early COVID-19 Outbreak: A Longitudinal Prospective Natural Experiment Design.

Comprehensive, prospective, longitudinal data are lacking on the effects of the COVID-19 outbreak on adolescents' movement behaviors (moderate to vigorous physical activity [MVPA], sleep, recreational screen use, and strengthening exercises). The purpose was to compare movement behavior changes among adolescents affected by the pandemic with controls. Survey data from 10,659 students at 82 Canadian secondary schools (aged 12-19y) during the 2018-2019 and 2019-2020 school years were analyzed. One-year change in time spent in movement behaviors and likelihood of meeting Canadian 24-hour movement guidelines was compared between preoutbreak controls (October 2019-March 2020) and early outbreak respondents (May-July 2020) after controlling for sociodemographic factors. Compared with controls, the early outbreak group reported a greater decrease in time spent in MVPA and greater increases in time spent in sleep and recreational screen use. The early outbreak group was less likely to meet MVPA and recreational screen time guidelines but more likely to meet guidelines for strengthening exercises and sleep duration. Findings for MVPA and screen time changes were in the same direction as retrospective reports from children and youth samples. Sleep adherence may have improved due to no longer having to commute to school. Strengthening exercises may represent physical activity that is easier to do in the home with minimal equipment leading to improved adherence during restrictions.

Psychological impact of a country-wide lockdown. Role of personal, behavioral, social, and physical conditions on negative and positive affect and meaning in life

During the early outbreak of COVID-19 in 2020, a strict home lockdown was maintained in Spain for more than 50 days, disrupting social and economic activities. The aim of this study is to explore affective and well-being responses during the initial period of mandatory home lockdown. Specifically, we analyzed: 1) differences in risk perception according to sociodemographic and health profile; 2) relation between social and environmental characteristics of home isolation, positive and negative affect and meaning in life; and 3) the relationship between activities and behaviors performed by people under lockdown and well-being. A total of 1343 Spanish residents participated in this correlational and cross-sectional study. Results show a significant relationship between health and economic risk perception associated with confinement. Higher health risk perception was identified among the older population and those belonging to high-risk groups. High resilience was linked to lower negative affect and greater positive affect and meaning in life. Regarding social and environmental characteristics of home isolation, people living with others reported greater negative affect than people living alone and the daily frequency of use of open-air spaces was linked to positive affect. Higher positive affect and meaning in life were also reported in people who frequently participated in community activities or by helping others. Lower negative affect was only associated with physical exercise.

Preliminary Estimation of the Basic Reproduction Number of SARS-CoV-2 in the Middle East

Up to April 9, 2020, 142490 cases have been confirmed as COVID-19 infection including 5705 associated deaths in the Middle East. Most of the countries, such as Qatar, Bahrain, Iraq, Kuwait, United Arab Emirates (UAE), Oman, Lebanon, and Saudi Arabia have imported COVID-19 cases from Iran. Using the available data from WHO webpage, up to 9 April 2020, we traced epidemic curves and estimated the basic reproduction number ( ) of COVID-19 through the susceptible-infectious-recovered (SIR) model for the Middle East countries. Epidemic curves for Middle East countries and territory show similar trend as Iran, with a couple of weeks’ delay in time. In SIR model, ranged between 7.41 as in Turkey to lowest as 2.60 for Oman whereas basic reproduction number for Iran, Kuwait, Bahrain, Qatar, Saudi Arabia, United Arab Emirates (UAE), Oman, Jordan, Egypt, Lebanon, Syria, Israel, West Bank and Gaza Strip territory, and Cyprus were 4.13, 2.71, 3.39, 4.18, 4.45, 2.75, 2.60, 3.52, 3.35, 3.16, 4.99, 4.08, 2.89, and 4.05, respectively. This study indicates an important trend on an early outbreak of COVID-19 based on estimated for the Middle East countries, mean 3.76 for COVID-19, with median and interquartile range (IQR) in the Middle East.

Associations of childhood neglect, difficulties in emotion regulation, and psychological distresses to COVID-19 pandemic: An intergenerational analysis

BackgroundAlthough individuals' psychological responses to trauma are varied, significant associations between parental and offspring's reactions have been documented among trauma-exposed families. Common susceptible factors originated from intergenerational transmission may be underlying mechanisms of this phenomenon. ObjectiveThis study aimed to investigate the intergenerational transmission of depression and anxiety during early outbreak of COVID-19 and further examined whether the transmission of child neglect and difficulties in emotion regulation (ER) was associated with the transmission of psychological distresses. MethodsSelf-reported questionnaires of depression, anxiety, COVID-19 related worries, difficulties in ER, physical and emotional neglect suffered in childhood were completed by 2011 Chinese parent - offspring dyads. Path analysis was used to examine hypothesized relationships. ResultsThe proportions of physical neglect and emotional neglect were 31.2% and 16.9% respectively among parents, while 28.6% and 20.8% respectively among offspring. There were remarkably similar in response patterns between parents and offspring. Parents' COVID-19 related worries, depression and anxiety levels were significantly associated with offspring's COVID-19 related worries, depression and anxiety. Difficulties in ER not only impacted psychological distresses directly, but also mediated the relationships between childhood neglect and psychological distresses among both parents and offspring. Difficulties in ER and childhood neglect, as important risk factors, were modestly transmitted from parent to offspring. ConclusionsFamily members shared a certain degree of similarity in psychological reactions to trauma. Transmitted susceptible factors from parents to offspring may contribute to this similarity. Family therapy may be suitable for family members exposed to the same traumatic events.

A linear dynamical perspective on epidemiology: interplay between early COVID-19 outbreak and human mobility.

This paper investigates the impact of human activity and mobility (HAM) in the spreading dynamics of an epidemic. Specifically, it explores the interconnections between HAM and its effect on the early spread of the COVID-19 virus. During the early stages of the pandemic, effective reproduction numbers exhibited a high correlation with human mobility patterns, leading to a hypothesis that the HAM system can be studied as a coupled system with disease spread dynamics. This study applies the generalized Koopman framework with control inputs to determine the nonlinear disease spread dynamics and the input–output characteristics as a locally linear controlled dynamical system. The approach solely relies on the snapshots of spatiotemporal data and does not require any knowledge of the system’s underlying physical laws. We exploit the Koopman operator framework by utilizing the Hankel dynamic mode decomposition with Control (HDMDc) algorithm to obtain a linear disease spread model incorporating human mobility as a control input. The study demonstrated that the proposed methodology could capture the impact of local mobility on the early dynamics of the ongoing global pandemic. The obtained locally linear model can accurately forecast the number of new infections for various prediction windows ranging from two to four weeks. The study corroborates a leader-follower relationship between mobility and disease spread dynamics. In addition, the effect of delay embedding in the HDMDc algorithm is also investigated and reported. A case study was performed using COVID infection data from Florida, US, and HAM data extracted from Google community mobility data report.

Machine Learning-Based Prediction Models for Depression Symptoms Among Chinese Healthcare Workers During the Early COVID-19 Outbreak in 2020: A Cross-Sectional Study.

BackgroundThe 2019 novel coronavirus (COVID-19)-related depression symptoms of healthcare workers have received worldwide recognition. Although many studies identified risk exposures associated with depression symptoms among healthcare workers, few have focused on a predictive model using machine learning methods. As a society, governments, and organizations are concerned about the need for immediate interventions and alert systems for healthcare workers who are mentally at-risk. This study aims to develop and validate machine learning-based models for predicting depression symptoms using survey data collected during the COVID-19 outbreak in China.MethodSurveys were conducted of 2,574 healthcare workers in hospitals designated to care for COVID-19 patients between 20 January and 11 February 2020. The patient health questionnaire (PHQ)-9 was used to measure the depression symptoms and quantify the severity, a score of ≥5 on the PHQ-9 represented depression symptoms positive, respectively. Four machine learning approaches were trained (75% of data) and tested (25% of data). Cross-validation with 100 repetitions was applied to the training dataset for hyperparameter tuning. Finally, all models were compared to evaluate their predictive performances and screening utility: decision tree, logistics regression with least absolute shrinkage and selection operator (LASSO), random forest, and gradient-boosting tree.ResultsImportant risk predictors identified and ranked by the machine learning models were highly consistent: self-perceived health status factors always occupied the top five most important predictors, followed by worried about infection, working on the frontline, a very high level of uncertainty, having received any form of psychological support material and having COVID-19-like symptoms. The area under the curve [95% CI] of machine learning models were as follows: LASSO model, 0.824 [0.792–0.856]; random forest, 0.828 [0.797–0.859]; gradient-boosting tree, 0.829 [0.798–0.861]; and decision tree, 0.785 [0.752–0.819]. The calibration plot indicated that the LASSO model, random forest, and gradient-boosting tree fit the data well. Decision curve analysis showed that all models obtained net benefits for predicting depression symptoms.ConclusionsThis study shows that machine learning prediction models are suitable for making predictions about mentally at-risk healthcare workers predictions in a public health emergency setting. The application of multidimensional machine learning models could support hospitals' and healthcare workers' decision-making on possible psychological interventions and proper mental health management.

Decline in Hospital Visits by Patients with Schizophrenia Early in the COVID-19 Outbreak in Korea.

ObjectiveThis study investigated trends in hospital utilization by patients with schizophrenia during the first wave of the COVID-19 outbreak in Korea.MethodsThe Prophet algorithm was used to predict the monthly number of patients with schizophrenia in 2020 based on medical insurance data between 2010 and 2019. The projected expectations were compared with the actual number of patients receiving outpatient and inpatient treatment each month in the first half of 2020. We conduct interrupted time series analyses of short-term data to determine the significance of recent changes in the trend of hospital visits by patients with schizophrenia.ResultsThe prediction model showed that the actual number of patients receiving treatment each month during the early COVID-19 outbreak decreased by up to 3.6% compared to the projected expectations. The interrupted time series model also revealed a significant change in hospital utilization compared to the year before the onset of COVID-19 in Korea (F = 8.961, p = 0.010).ConclusionThis suggests that many patients with schizophrenia were not receiving adequate treatment during the COVID-19 outbreak. A strategy should be developed to keep treating patients with schizophrenia during the COVID-19 pandemic.

The Challenges Faced by Nursing Homes During the Early COVID-19 Outbreak.

The Challenges Faced by Nursing Homes During the Early COVID-19 Outbreak.

Changes in the characteristics of trauma patients after the early COVID-19 outbreak: A retrospective study of a regional level 1 trauma center in Republic of Korea.

Gyeonggi-do (Gyeonggi province) has the second highest number of coronavirus disease (COVID-19) cases in the Republic of Korea after Seoul, with approximately 25% of the COVID-19 patients as of January 2021. Our center is a level I trauma center located in south Gyeonggi-do, and we aimed to evaluate whether the characteristics of trauma patients changed after the COVID-19 pandemic.We retrospectively reviewed the trauma patients registered with the Korea Trauma Database of the Center from February 2019 to January 2021. The patients were dichotomized into pre-coronavirus disease (pre-COVID) and coronavirus disease (COVID) groups, and their trauma volumes, injury characteristics, intentionality, and outcomes were compared.A total of 2628 and 2636 patients were included in the pre-COVID and COVID groups, respectively. During the COVID-19 period, motorcycle accidents, bicycle accidents, and penetrating injury cases increased, and pedestrian traffic accidents, slips, and injury by machines decreased. The average daily number of patients in the COVID group was lower in March (5.6 ± 2.6/day vs 7.2 ± 2.4/day, P = .014) and higher in September (9.9 ± 3.2/day vs 7.7 ± 2.0/day, P = .003) compared to the pre-COVID group. The COVID group also had a higher ratio of direct admissions (67.5% vs 57.2%, P < .001), proportion of suicidal patients (4.1% vs 2.7%, P = .005), and injury severity scores (14 [9–22] vs 12 [4–22], P < .001) than the pre-COVID group. The overall mortality (4.7% vs 4.9%, P = .670) and intensive care unit length of stay (2 [0–3] days vs 2 [0–4] days, P = .153) was not different between the 2 groups.Although the total number of patients did not change, the COVID-19 pandemic affected the number of monthly admissions and the injury mechanisms changed. More severely injured patients were admitted directly to the trauma center.

COVID-19 Pandemic Driven Knowledge, Attitude, Clinical Practice, Distress Reactions, and Post-Traumatic Growth of Dental Care Providers in Riyadh City, Saudi Arabia: A Cross-Sectional Study

Objective: The present study aimed to assess knowledge, attitude, clinical practices, distress reactions, and post-traumatic growth of dentists during the COVID-19 pandemic in Riyadh City. Methodology: An online questionnaire was developed to assess various dental professionals from both governmental and private sectors during the early COVID-19 outbreak in Riyadh City, Saudi Arabia. The questionnaire was framed to assess the demographic variables, knowledge, attitude, and clinical practices towards handling the COVID-19 pandemic. Furthermore, the general anxiety disorder-7 (GAD-7), worry questionnaire items, short form of post-traumatic growth inventory (PTGI-SF), and life satisfaction questionnaire items were developed to assess the anxiety, worries, post-traumatic growth, and life satisfaction of dental care providers following the traumatic events. Data were analysed using SPSS 22.0 and R environment ver.3.2.2. Continuous measurement results were presented as mean ± SD, and categorical measurements results were presented in number (%). Results: Our study's significant findings revealed that a majority of the dentists were in the age group of 21-30 and practiced general dentistry. The study participants in age groups 51–60 and 41–50 years old showed more liability in perceiving COVID-19 as an extremely dangerous disease than 31–40 and 21–30 age groups. The majority of respondents (63.4%) had an anxiety scale score of greater than 40, followed by 22.8% with scores 20-40 and 13.9% with scores less than 20, respectively. The mean scores for the GAD-7 and the worry items were 8.24 ± 3.21 and 13.92 ± 4.77, respectively. The data showed that most survey participants had adopted moderate post-traumatic changes during the pandemic, as evident by their mean score of 34.17 ± 3.40. The life satisfaction of the participants was neutral, as demonstrated by their mean score of 20.16 ± 4.03. Conclusion: This study’s findings delineated that the COVID-19 pandemic situation has influenced dentists' mental health, with a moderate level of anxiety, and worries among other psychological symptoms. Furthermore, there was adequate knowledge regarding the COVID-19 among dentists; however, the pandemic affected the financial conditions of the respondents. There was a moderate level of post-traumatic growth and neutral life satisfaction of the dental providers.

Anger among Chinese migrants amid COVID-19 discrimination: The role of host news coverage, cultural distance, and national identity.

As the early COVID-19 outbreak sparked xenophobia against people of Asian and Chinese background, we collected data from Chinese migrants worldwide to test how discrimination at a macro-level was perceived by the Chinese during COVID-19 globally. Specifically, we examined (1) whether/how the Chinese migrants were aware of discrimination against their co-nationals during COVID; (2) if so, whether anger was a predominant reaction of these Chinese towards certain exposure to relevant information; (3) how responses of anger transcend across the group of Chinese migrants. Integrating the ecological approach to media and cultural psychology, as well as the intergroup perspective of social psychology, we conducted a study that explored the impact of traditional media exposure to discrimination on collective anger—a process mediated by national identity among the Chinese migrants. Findings provide some evidence that geographically dispersed mono-cultural groups may share or identify with collective emotions when facing xenophobic threats in a macro context. Further examination of cultural distance (between China and the host country) among the Chinese migrants also revealed a particular interaction between host newspaper coverage and cultural distance on national identity. These findings suggest further research to examine the emotional norms of similar cultures bonded via strong collective identities in times of intergroup threat and the theoretical possibility for diasporic identity processes.

Study on the Recovery Strategy of Tourism in Hubei Province in the Post Epidemic Era

The outbreak and spread of COVID-19 has had a negative impact on the development of China's tourism industry. Wuhan is an early outbreak of COVID-19 in the world and also a region deeply affected by the epidemic. How to repair the image of a tourist destination has become an important issue for the revival and development of domestic tourism at this stage. Based on the actual situation of Wuhan, this paper makes strategic measures to reveal the efforts made by domestic tourism marketing during the COVID-19 epidemic period to maintain the positive image of tourism, and provides reference for the selection and formulation of post-EPIDEMIC tourism destination image restoration strategies.

The impact of ethnic segregation on neighbourhood-level social distancing in the United States amid the early outbreak of COVID-19.

The COVID-19 pandemic has been argued to be the 'great equaliser', but, in fact, ethnically and racially segregated communities are bearing a disproportionate burden from the disease. Although more people have been infected and died from the disease among these minority communities, still fewer people in these communities are complying with the suggested public health measures like social distancing. The factors contributing to these ramifications remain a long-lasting debate, in part due to the contested theories between ethnic stratification and ethnic community. To offer empirical evidence to this theoretical debate, we tracked public social-distancing behaviours from mobile phone devices across urban census tracts in the United States and employed a difference-in-difference model to examine the impact of racial/ethnic segregation on these behaviours. Specifically, we focussed on non-Hispanic Black and Hispanic communities at the neighbourhood level from three principal dimensions of ethnic segregation, namely, evenness, exposure, and concentration. Our results suggest that (1) the high ethnic diversity index can decrease social-distancing behaviours and (2) the high dissimilarity between ethnic minorities and non-Hispanic Whites can increase social-distancing behavior; (3) the high interaction index can decrease social-distancing behaviours; and (4) the high concentration of ethnic minorities can increase travel distance and non-home time but decrease work behaviours. The findings of this study shed new light on public health behaviours among minority communities and offer empirical knowledge for policymakers to better inform just and evidence-based public health orders.

Resistance of SARS-CoV-2 variants to neutralization by convalescent plasma from early COVID-19 outbreak in Singapore

The rapid spreading of SARS-CoV-2 variants B.1.1.7 originated from the United Kingdom and B.1.351 from South Africa has contributed to the second wave of COVID-19 cases in the respective countries and also around the world. In this study, we employed advanced biochemical and virological methodologies to evaluate the impact of Spike mutations of these strains on the degree of protection afforded by humoral immune responses following natural infection of the ancestral SARS-CoV-2 strain during the early stages of the outbreak. We found that antibody-mediated neutralization activity was partially reduced for B.1.1.7 variant and significantly attenuated for the B.1.351 strain. We also found that mutations outside the receptor-binding domain (RBD) can strongly influence antibody binding and neutralization, cautioning the use of solely RBD mutations in evaluating vaccine efficacy. These findings highlight an urgent need to develop new SARS-CoV-2 vaccines that are not based exclusively on the ancestral SARS-CoV-2 Spike gene sequence.