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Objective: To survey the knowledge, attitude, and practices of Vietnamese pharmacists regarding the COVID-19 pandemic. Method: This cross-sectional, paper-based study was conducted from June to August 2020. A validated questionnaire (Cronbach's alpha = 0.84) was used to interview 1,023 pharmacists in nine provinces of Vietnam. Analysis of covariance was employed to identify factors associated with the knowledge of pharmacists. The best model was chosen by using the Bayesian Model Averaging method in R software version 4.0.4. Results: The mean knowledge score was 12.02 ± 1.64 (range: 6–15), which indicated that 93.4% of pharmacists had good knowledge of COVID-19. There was no difference in the average score between males and females (p > 0.05). The multivariate linear regression model revealed that the knowledge was significantly associated with pharmacists' age, education level, and residence (p < 0.001). About attitude and practices, pharmacists daily sought and updated information on the COVID-19 pandemic through mass media and the internet (social network and online newspapers). Nearly 48% of them conceded that they communicated with customers when at least one person did not wear a face mask at the time of the COVID-19 outbreak. At medicine outlets, many measures were applied to protect pharmacists and customers, such as equipping pharmacists with face masks and hand sanitizers (95.0%), using glass shields (83.0%), and maintaining at least one-meter distance between two people (85.2%). Conclusion: The pharmacists' knowledge of COVID-19 transmission, symptoms, and prevention was good. Many useful measures against the spread of this perilous virus were applied in medicine outlets. However, pharmacists should restrict forgetting to wear face masks in communication with medicine purchasers. The government and health agencies should have practical remedies to reduce the significant differences in the COVID-19 knowledge of pharmacists among provinces and education-level groups. [ABSTRACT FROM AUTHOR]

The Coronavirus Disease 2019(COVID-19) has caused widespread and significant harm globally. In order to address the urgent demand for a rapid and reliable diagnostic approach to mitigate transmission, the application of deep learning stands as a viable solution. The impracticality of many existing models is attributed to excessively large parameters, significantly limiting their utility. Additionally, the classification accuracy of the model with few parameters falls short of desirable levels. Motivated by this observation, the present study employs the lightweight network MobileNetV3 as the underlying architecture. This paper incorporates the dense block to capture intricate spatial information in images, as well as the transition layer designed to reduce the size and channel number of the feature map. Furthermore, this paper employs label smoothing loss to address the inter-class similarity effects and uses class weighting to tackle the problem of data imbalance. Additionally, this study applies the pruning technique to eliminate unnecessary structures and further reduce the number of parameters. As a result, this improved model achieves an impressive 98.71% accuracy on an openly accessible database, while utilizing only 5.94 million parameters. Compared to the previous method, this maximum improvement reaches 5.41%. Moreover, this research successfully reduces the parameter count by up to 24 times, showcasing the efficacy of our approach. This demonstrates the significant benefits in regions with limited availability of medical resources. [ABSTRACT FROM AUTHOR]

Online research methods have grown in popularity due in part to the globalised and far-reaching nature of the internet but also linked to the Covid-19 pandemic whereby restrictions to travel and face to face contact necessitated a shift in methods of research recruitment and data collection. Ethical guidance exists to support researchers in conducting online research, however this is lacking within health fields. This scoping review aims to synthesise formal ethical guidance for applying online methods within health research as well as provide examples of where guidance has been used. A systematic search of literature was conducted, restricted to English language records between 2013 and 2022. Eligibility focused on whether the records were providing ethical guidance or recommendations, were situated or relevant to health disciplines, and involved the use or discussion of online research methods. Following exclusion of ineligible records and duplicate removal, three organisational ethical guidance and 24 research papers were charted and thematically analysed. Four key themes were identified within the guidance documents, 1) consent, 2) confidentiality and privacy, 3) protecting participants from harm and 4) protecting researchers from harm with the research papers describing additional context and understanding around these issues. The review identified that there are currently no specific guidelines aimed at health researchers, with the most cited guidance coming from broader methodological perspectives and disciplines or auxiliary fields. All guidance discussed each of the four key themes within the wider context of sensitive topics and vulnerable populations, areas and issues which are often prominent within health research thus highlighting the need for unifying guidance specific for health researchers. Further research should aim to understand better how online health studies apply ethical principles, to support in informing gaps across both research and guidance. [ABSTRACT FROM AUTHOR]

Brazil counts among the countries the hardest hit by the Covid-19 pandemic. A great deal has been said about the negative role played by President Bolsonaro's denialism, but relatively few studies have attempted to measure precisely what impact it actually had on the pandemic. Our paper conducts econometric estimates based on observational data at municipal level to quantitatively assess the 'Bolsonaro effect' over time from March 2020 to December 2022. To our knowledge, this paper presents the most comprehensive investigation of Bolsonaro's influence in the spread of the pandemic from two angles: considering Covid-19 mortality and two key transmission mitigation channels (social distancing and vaccination); and exploring the full pandemic cycle (2020–2022) and its dynamics over time. Controlling for a rich set of relevant variables, our results find a strong and persistent 'Bolsonaro effect' on the death rate: municipalities that were more pro-Bolsonaro recorded significantly more fatalities. Furthermore, evidence suggests that the president's attitude and decisions negatively influenced the population's behaviour. Firstly, pro-Bolsonaro municipalities presented a lower level of compliance with social distancing measures. Secondly, vaccination was relatively less widespread in places more in favour of the former president. Finally, our analysis points to longer-lasting and damaging repercussions. Regression results are consistent with the hypothesis that the 'Bolsonaro effect' impacted not only on Covid-19 vaccination, but has affected vaccination campaigns in general thereby jeopardizing the historical success of the National Immunization Program in Brazil. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, concerns were raised that face covering use may elicit risk compensation; a false sense of security resulting in reduced adherence to other protective behaviours such as physical distancing. This systematic review aimed to investigate the effect of face covering use on adherence to other COVID-19 related protective behaviours. Medline, Embase, PsychInfo, EmCare, medRxiv preprints, Research Square and WHO COVID-19 Research Database were searched for all primary research studies published from 1st January 2020 to 17th May 2022 that investigated the effect of face covering use on adherence to other protective behaviours in public settings during the COVID-19 pandemic. Papers were selected and screened in accordance with the PRISMA framework. Backwards and forwards citation searches of included papers were also conducted on 16th September 2022, with eligible papers published between 1st January 2020 and that date being included. A quality appraisal including risk of bias was assessed using the Academy of Nutrition and Dietetics' Quality Criteria Checklist. This review is registered on PROSPERO, number CRD42022331961. 47 papers were included, with quality ranging from low to high. These papers investigated the effects of face covering use and face covering policies on adherence to six categories of behaviour: physical distancing; mobility; face-touching; hand hygiene; close contacts; and generalised protective behaviour. Results reveal no consistent evidence for or against risk compensation, with findings varying according to behaviour and across study types, and therefore confident conclusions cannot be made. Any policy decisions related to face coverings must consider the inconsistencies and caveats in this evidence base. [ABSTRACT FROM AUTHOR]

Background: The global outbreak of COVID-19 has brought to light the profound impact that large-scale disease outbreaks can have on healthcare systems and the dedicated professionals who serve within them. It becomes increasingly important to explore strategies for retaining nurses and physicians within hospital settings during such challenging times. This paper aims to investigate the determinants of retention among nurses and physicians during the COVID-19 pandemic. Method: A systematic review of other potential determinants impacting retention rates during the pandemic was carried out. Secondly, a meta-analysis on the prevalence of intention to leave for nurses and physicians during the COVID-19 pandemic. Findings: A comprehensive search was performed within four electronic databases on March 17 2023. Fifty-five papers were included in the systematic review, whereas thirty-three papers fulfilled the eligibility criteria for the meta-analysis. The systematic review resulted in six themes of determinants impacting intention to leave: personal characteristics, job demands, employment services, working conditions, work relationships, and organisational culture. The main determinants impacting the intention to leave are the fear of COVID-19, age, experience, burnout symptoms and support. Meta-analysis showed a prevalence of intent to leave the current job of 38% for nurses (95% CI: 26%-51%) and 29% for physicians (95% CI: 21%-39%), whereas intention to leave the profession for nurses 28% (95% CI: 21%-34%) and 24% for physicians (95% CI: 23%-25%). Conclusion: The findings of this paper showed the critical need for hospital managers to address the concerning increase in nurses' and physicians' intentions to leave during the COVID-19 pandemic. This intention to leave is affected by a complex conjunction of multiple determinants, including the fear of COVID-19 and the confidence in and availability of personal protective equipment. Moreover, individual factors like age, experience, burnout symptoms, and support are maintained in this review. Understanding the influence of determinants on retention during the COVID-19 pandemic offers an opportunity to formulate prospective strategies for retaining nurses and physicians within hospital settings. [ABSTRACT FROM AUTHOR]

Objective: Much research on the early stages of the COVID-19 pandemic demonstrates the unequal impact on men and women in many countries but empirical evidence on later stages of the pandemic remains limited. The objective of this paper is to study differences between men and women in work location, the relative division of childcare, and perceived work-life balance across and throughout different phases of the pandemic using six waves of probability-based survey data collected in the Netherlands between April 2020 and April 2022 (including retrospective pre-pandemic measures). Method: The study used descriptive methods (longitudinal crosstabulations) and multivariate modelling (cross-sectional multinomial logits, with and without moderators) in a repeated cross-sectional design. Results: Results suggest the pandemic is associated with several phase-specific differences between men and women in where they worked and their relative division of childcare in the Netherlands. Men were less likely than women to work fully from home at the start of each lockdown and to work on location during the first lockdown. Amongst parents, fathers increased their share of childcare throughout the first phase of the pandemic, and this increase remains visible at the end of the pandemic. Women in the Netherlands did not experience worse work-life balance than men throughout the pandemic, but mothers did experience worse work-life balance than fathers at various points during the pandemic. Discussion: Our results suggest varying long-term implications for gender inequality in society. Gender differences in work location raise concerns about the possible longer-term impact on gender inequalities in career development. Our findings on childcare suggest that many households have experienced different divisions of childcare at different stages of the pandemic, with some potential for longer-term change. Conclusion: Inequalities between men and women in work, childcare, and wellbeing have neither been alleviated by nor unilaterally worsened during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

As a response to the damage caused by the spread of COVID-19, the Chinese government has implemented severe quarantine measures that have greatly affected the operational patterns of small and medium-sized enterprises (SMEs). This paper explores the critical role of dynamic capabilities (DCs) in helping Chinese SMEs manage crises, adjust their business strategies, and mitigate the uncertainty caused by the epidemic. Although the importance of DCs in promoting organizational resilience is well recognized, academic research on their specific contributions to business model innovation (BMI) and SME performance improvement during crises remains scarce. Our study fills this gap by pioneering the development and empirical testing of a microintegrated mediation model linking DCs, BMI and organizational performance. By surveying 257 Chinese SMEs severely affected by a pandemic, we verify our hypotheses using partial least squares structural equation modeling (PLS-SEM). Our results strongly show a positive relationship between DCs and BMI and SME performance. In addition, we found that BMI plays a partial mediating role in the interrelationship between DCs and SME performance. Our findings clarify the critical role of BMI as a channel through which SMEs' DCs can be transformed into higher performance in the face of sudden crises. Thus, our results not only contribute to the broader discussion of strategic management and organizational theory but also provide theoretical and practical insights into the mechanisms by which SMEs can increase their flexibility and resilience in a crisis. Thus, our results not only contribute to the broader discussion of strategic management and organizational theory but also provide theoretical and practical insights into the mechanisms by which SMEs can increase their flexibility and resilience in a crisis. Importantly, this study suggests policy and market strategies that can support SMEs in leveraging DCs and BMI for sustained performance, thereby contributing valuable insights for policymakers and business leaders aiming to fortify economic stability and growth in the face of global health emergencies. [ABSTRACT FROM AUTHOR]

As an emerging business modality and Internet format, live streaming e-commerce has developed rapidly since its emergence in 2016, especially since the outbreak of the COVID-19 epidemic in late 2019, when an increasing number of businesses from other industries attracted participation. However, with the development of the live streaming e-commerce industry, the industry's market environment is becoming increasingly chaotic. Therefore, during this period, government departments continuously formulate and implement relevant industry policies. In order to exploring the cooperation network structure, policy content distribution, and implementation effectiveness characteristics among publishers, this paper constructs a three-dimensional analysis framework of policy from the perspective of policy tools, policy effectiveness evaluation and policy publishers. The results show that in terms of policy tools, the overall structure of policy tools in the live streaming e-commerce industry is unreasonable, and different types of policy tools are significantly diverse. The proportion of environmental policy tools is greater than that of demand-based and supply-based policy tools, accounting for 62.97%, and among them, the tools related to industry regulation and management account for the largest proportion of the total, which greatly suppresses the enthusiasm of various entities in the industry for development. In terms of policy effectiveness evaluation, most of the policies do not formulate detailed long-, medium-, or short-term goals, nor are the policy priorities, incentive measures, or action modes perfect, indicating that the government's pushing and pulling forces for the live streaming e-commerce industry are insufficient. Finally, in the subject dimension of policy release, the synergy of relevant subjects is constantly improving, but there is also a phenomenon of over-concentration in the synergistic departments. [ABSTRACT FROM AUTHOR]

Introduction: Studies indicate that individuals with chronic conditions and specific baseline characteristics may not mount a robust humoral antibody response to SARS-CoV-2 vaccines. In this paper, we used data from the Texas Coronavirus Antibody REsponse Survey (Texas CARES), a longitudinal state-wide seroprevalence program that has enrolled more than 90,000 participants, to evaluate the role of chronic diseases as the potential risk factors of non-response to SARS-CoV-2 vaccines in a large epidemiologic cohort. Methods: A participant needed to complete an online survey and a blood draw to test for SARS-CoV-2 circulating plasma antibodies at four-time points spaced at least three months apart. Chronic disease predictors of vaccine non-response are evaluated using logistic regression with non-response as the outcome and each chronic disease + age as the predictors. Results: As of April 24, 2023, 18,240 participants met the inclusion criteria; 0.58% (N = 105) of these are non-responders. Adjusting for age, our results show that participants with self-reported immunocompromised status, kidney disease, cancer, and "other" non-specified comorbidity were 15.43, 5.11, 2.59, and 3.13 times more likely to fail to mount a complete response to a vaccine, respectively. Furthermore, having two or more chronic diseases doubled the prevalence of non-response. Conclusion: Consistent with smaller targeted studies, a large epidemiologic cohort bears the same conclusion and demonstrates immunocompromised, cancer, kidney disease, and the number of diseases are associated with vaccine non-response. This study suggests that those individuals, with chronic diseases with the potential to affect their immune system response, may need increased doses or repeated doses of COVID-19 vaccines to develop a protective antibody level. [ABSTRACT FROM AUTHOR]

To manage the negative impact of job burnout for the researchers, especially during COVID-19 pandemic, is not easy. Thus, it is essential for educational institutions to provide them with the support they need to improve the person-organization (P-O) fit. Drawing upon the data from the Nature's Global Survey initiated in 2021, this paper analyzed 2,424 effective samples from eleven countries in the world to investigate how P-O fit impacts researchers' job burnout in different countries and their career stages during the COVID-19 pandemic. The findings show that both organizational support and P-O fit have significantly assisted researchers in all career stages to reduce job burnout. Moreover, P-O fit has a greater inhibitory effect on job burnout than organizational support. However, when resources are relatively scarce in some developing countries, it is more important to provide organizational support for researchers. Therefore, in order to improve the efficiency of organizational support and reduce researchers' job burnout, those aspects which are less fit but helpful should be increased appropriately. Moreover, it implies that it would be significant to emphasize the differentiated and career-stage-sensitive resources and support to researchers in different countries in the post-pandemic era to improve researchers' well-being and organizational performance. [ABSTRACT FROM AUTHOR]

Selecting an appropriate intensity of epidemic prevention and control measures is of vital significance to promoting the two-way dynamic coordination of epidemic prevention and control and economic development. In order to balance epidemic control and economic development and suggest scientific and reasonable traffic control measures, this paper proposes a SEIQR model considering population migration and the propagation characteristics of the exposed and the asymptomatic, based on the data of COVID-19 cases, Baidu Migration, and the tourist economy. Further, the factor traffic control intensity is included in the model. After determining the functional relationship between the control intensity and the number of tourists and the cumulative number of confirmed cases, the NSGA-II algorithm is employed to perform multi-objective optimization with consideration of the requirements for epidemic prevention and control and for economic development to get an appropriate traffic control intensity and suggest scientific traffic control measures. With Xi'an City as an example. The results show that the Pearson correlation coefficient between the predicted data of this improved model and the actual data is 0.996, the R-square in the regression analysis is 0.993, with a significance level of below 0.001, suggesting that the predicted data of the model are more accurate. With the continuous rise of traffic control intensity in different simulation scenarios, the cumulative number of cases decreases by a significant amplitude. While balancing the requirements for epidemic prevention and control and for tourist economy development, the model works out the control intensity to be 0.68, under which some traffic control measures are suggested. The model presented in this paper can be used to analyze the impacts of different traffic control intensities on epidemic transmission. The research results in this paper reveal the traffic control measures balancing the requirements for epidemic prevention and control and for economic development. [ABSTRACT FROM AUTHOR]

Questionnaires are among the most basic and widespread tools to assess the mental health of a population in epidemiological and public health studies. Their most obvious advantage (firsthand self-report) is also the source of their main problems: the raw data requires interpretation, and are a snapshot of the specific sample's status at a given time. Efforts to deal with both issues created a bi-dimensional space defined by two orthogonal axes, in which most of the quantitative mental health research can be located. Methods aimed to assure that mental health diagnoses are solidly grounded on existing raw data are part of the individual validity axis. Tools allowing the generalization of the results across the entire population compose the collective validity axis. This paper raises a different question. Since one goal of mental health assessments is to obtain results that can be generalized to some extent, an important question is how robust is a questionnaire result when applied to a different population or to the same population at a different time. In this case, there is deep uncertainty, without any a priori probabilistic information. The main claim of this paper is that this task requires the development of a new robustness to deep uncertainty axis, defining a three-dimensional research space. We demonstrate the analysis of deep uncertainty using the concept of robustness in info-gap decision theory. Based on data from questionnaires collected before and during the Covid-19 pandemic, we first locate a mental health assessment in the space defined by the individual validity axis and the collective validity axis. Then we develop a model of info-gap robustness to uncertainty in mental health assessment, showing how the robustness to deep uncertainty axis interacts with the other two axes, highlighting the contributions and the limitations of this approach. The ability to measure robustness to deep uncertainty in the mental health realm is important particularly in troubled and changing times. In this paper, we provide the basic methodological building blocks of the suggested approach using the outbreak of Covid-19 as a recent example. [ABSTRACT FROM AUTHOR]

To control the SARS-CoV-2 pandemic, healthcare systems have focused on ramping up their capacity for epidemiological surveillance through viral whole genome sequencing. In this paper, we tested the performance of two protocols of SARS-CoV-2 nucleic acid enrichment, an amplicon enrichment using different versions of the ARTIC primer panel and a hybrid-capture method using KAPA RNA Hypercap. We focused on the challenge of the Omicron variant sequencing, the advantages of automated library preparation and the influence of the bioinformatic analysis in the final consensus sequence. All 94 samples were sequenced using Illumina iSeq 100 and analysed with two bioinformatic pipelines: a custom-made pipeline and an Illumina-owned pipeline. We were unsuccessful in sequencing six samples using the capture enrichment due to low reads. On the other hand, amplicon dropout and mispriming caused the loss of mutation G21987A and the erroneous addition of mutation T15521A respectively using amplicon enrichment. Overall, we found high sequence agreement regardless of method of enrichment, bioinformatic pipeline or the use of automation for library preparation in eight different SARS-CoV-2 variants. Automation and the use of a simple app for bioinformatic analysis can simplify the genotyping process, making it available for more diagnostic facilities and increasing global vigilance. [ABSTRACT FROM AUTHOR]

Background: Health communication in the COVID-19 pandemic can be effectively implemented if all members of the populations, including marginalized population such as migrant domestic workers (MDWs), have good eHealth literacy. Lessons learned during this critical period may help improve planning and mitigation of the impacts of future health crises. Methods: This study aimed to examine and explore the eHealth literacy levels of the MDWs in Hong Kong during the COVID-19 pandemic by using a convergent mixed methods research design. A total of 1156 Hong Kong MDWs participated in a paper-based survey using a multistage cluster random sampling design for the quantitative component. eHealth literacy was measured using an eHealth literacy Scale (eHEALS). For the qualitative component, a purposive sampling of 19 MDWs participated in face-to-face, semi-structured, in-depth interviews. Descriptive statistics and multiple regression analyses were used to carry out the quantitative analysis, while thematic analysis was used for the qualitative analysis. Both quantitative and qualitative data were merged and integrated for mixed-methods analysis. Results: The meta-inferences of the quantitative and qualitative results mainly confirmed that MDWs in Hong Kong had good levels of eHealth literacy. The use of Instagram, YouTube and WhatsApp as the COVID-19 information sources, in addition to having an interest in the topic of the current spread of COVID-19 together with the Hong Kong government's policies related to COVID-19, were found to be associated with eHealth literacy. Conclusions: The eHealth literacy level of MDWs in Hong Kong was shown to be good and it was influenced by the use of popular social media platforms including Instagram, YouTube, and WhatsApp. It is realistic to suggest that such platforms should be harnessed for health communication during the pandemic. Yet, regulations to combat false information on these media are also urgently needed. [ABSTRACT FROM AUTHOR]

The aim of the paper is to provide an ex-post assessment of the impact of the COVID-19 pandemic on food insecurity in the EU-27 countries expressed by physical and economic food access. We analysed trade and price effects, together with food insecurity and malnutrition indicators. Actual levels of the indicators were compared with their pre-pandemic magnitudes and/or with counterfactual levels derived from predictive models. We also aimed to compare the objective statistics with the subjective consumers' perception of their households' food security. Our research indicates that the EU food trade was more resilient to COVID-19 impacts than the trade in non-food products, while food trade decreases were of a temporary nature. This did not affect the trade balance significantly; however, the import reduction threatened the physical food access in most EU countries. Regarding economic food access, the results indicate that the increase in food prices was offset by the increase in disposable income. It may suggest that the COVID-19 pandemic did not significantly affect the deterioration of economic access to food in the EU countries. However, the prevalence of severe food insecurity in the total population or the proportion of households reporting inability to afford a meal with meat, chicken, fish, or a vegetarian equivalent increased in 2020–2021 compared to 2019. This means that the comparative analysis of the real data on prices and households' income, as well as consumer financial situation and food consumption affordability, does not offer a clear answer concerning the impact of the COVID-19 pandemic on the food security of EU households. [ABSTRACT FROM AUTHOR]

The NIMH-funded Multilevel Community-Based Mental Health Intervention to Address Structural Inequities and Adverse Disparate Consequences of COVID-19 Pandemic on Latinx Immigrants and African Refugees study aims to advance the science of multilevel interventions to reduce the disparate, adverse mental health, behavioral, and socioeconomic consequences of the COVID-19 pandemic that are a result of complex interactions between underlying structural inequities and barriers to health care. The study tests three nested levels of intervention: 1) an efficacious 4-month advocacy and mutual learning model (Refugee and Immigrant Well-being Project, RIWP); 2) engagement with community-based organizations (CBOs); and 3) structural policy changes enacted in response to the pandemic. This community-based participatory research (CBPR) study builds on long-standing collaboration with five CBOs. By including 240 Latinx immigrants and 60 African refugees recruited from CBO partners who are randomly assigned to treatment-as-usual CBO involvement or the RIWP intervention and a comparison group comprised of a random sample of 300 Latinx immigrants, this mixed methods longitudinal waitlist control group design study with seven time points over 36 months tests the effectiveness of the RIWP intervention and engagement with CBOs to reduce psychological distress, daily stressors, and economic precarity and increase protective factors (social support, access to resources, English proficiency, cultural connectedness). The study also tests the ability of the RIWP intervention and engagement with CBOs to increase access to the direct benefits of structural interventions. This paper reports on the theoretical basis, design, qualitative and quantitative analysis plan, and power for the study. [ABSTRACT FROM AUTHOR]

Human-to-human contact plays a leading role in the transmission of infectious diseases, and the contact pattern between individuals has an important influence on the intensity and trend of disease transmission. In this paper, we define regular contacts and random contacts. Then, taking the COVID-19 outbreak in Yangzhou City, China as an example, we consider age heterogeneity, household structure and two contact patterns to establish discrete dynamic models with switching between daytime and nighttime to depict the transmission mechanism of COVID-19 in population. We studied the changes in the reproduction number with different age groups and household sizes at different stages. The effects of the proportion of two contacts patterns on reproduction number were also studied. Furthermore, taking the final size, the peak value of infected individuals in community and the peak value of quarantine infected individuals and nucleic acid test positive individuals as indicators, we evaluate the impact of the number of random contacts, the duration of the free transmission stage and summer vacation on the spread of the disease. The results show that a series of prevention and control measures taken by the Chinese government in response to the epidemic situation are reasonable and effective, and the young and middle-aged adults (aged 18-59) with household size of 6 have the strongest transmission ability. In addition, the results also indicate that increasing the proportion of random contact is beneficial to the control of the infectious disease in the phase with interventions. This work enriches the content of infectious disease modeling and provides theoretical guidance for the prevention and control of follow-up major infectious diseases. [ABSTRACT FROM AUTHOR]

The spread of the COVID-19 had profoundly affected the development of the air transportation. In order to determine the changes in air transportation volume associated with the development of the epidemic, this paper takes Southwest China as the study area. Monthly data and methods, such as the coefficient of variation, rank-size analysis and spatial matching index, were applied. The results found that: (1) during 2020–2022, there was a positive relationship between passenger volume and epidemic development, while freight volume increased for most airports in the first quarter of 2020–2022, particularly in the eastern region; (2) From the perspective of changes in air transportation volume under the development of the COVID-19, among various types of airports, the changes in transportation volume of main trunk airports were more significant than those of regional feeder airports in remote areas; (3) however, under the influence of the epidemic, main trunk airports still exhibited stronger attraction in passenger volume. That is to say, the passengers who chose to travel by air still tended to choose the main trunk airports and formed the agglomeration distribution pattern which around high-level airports in the provincial capital. Whereas the freight volume had a tendency of equalization among airports in Southwest China; (4) Over the course of time, the consistency of the spatial distribution of the number of cases and the passenger or freight volume in southwest China gradually increased. Among them, the spatial matching rate of the passenger volume and the number of COVID-19 cases was always higher than that of the cases and freight volume, which might indicate that there was a stronger correlation relationship. Therefore, it is proposed that the construction of multi-center airport system should be strengthened, the resilience of the route network for passenger transportation should be moderately enhanced, and the risk-resistant capacity of mainline airports and airports in tourist cities should be upgraded, so as to provide references for the orderly recovery of civil aviation and regional development. [ABSTRACT FROM AUTHOR]

Disinformation–false information intended to cause harm or for profit–is pervasive. While disinformation exists in several domains, one area with great potential for personal harm from disinformation is healthcare. The amount of disinformation about health issues on social media has grown dramatically over the past several years, particularly in response to the COVID-19 pandemic. The study described in this paper sought to determine the characteristics of multimedia social network posts that lead them to believe and potentially act on healthcare disinformation. The study was conducted in a neuroscience laboratory in early 2022. Twenty-six study participants each viewed a series of 20 either honest or dishonest social media posts, dealing with various aspects of healthcare. They were asked to determine if the posts were true or false and then to provide the reasoning behind their choices. Participant gaze was captured through eye tracking technology and investigated through "area of interest" analysis. This approach has the potential to discover the elements of disinformation that help convince the viewer a given post is true. Participants detected the true nature of the posts they were exposed to 69% of the time. Overall, the source of the post, whether its claims seemed reasonable, and the look and feel of the post were the most important reasons they cited for determining whether it was true or false. Based on the eye tracking data collected, the factors most associated with successfully detecting disinformation were the total number of fixations on key words and the total number of revisits to source information. The findings suggest the outlines of generalizations about why people believe online disinformation, suggesting a basis for the development of mid-range theory. [ABSTRACT FROM AUTHOR]

Vaccine "unnaturalness" (artificiality) is one of the major anti-vaccine arguments raised in public debate. Therefore, health communication should rebut unnaturalness arguments and be cautious when emphasizing human intervention (e.g., advanced vaccine technology), which may entail perceiving vaccines as artificial. Understanding how the relationship between perceived vaccine artificiality and vaccination intent differs across social groups can help enforce the above health communication efforts by focusing them on specific audiences. The objective of the current paper is to assess the moderating role of a particular socio-cultural factor—vertical collectivism (reflecting the orientation on social hierarchy)—in the relationship between perceived vaccine artificiality and vaccination intent. It is proposed that vertical collectivism diminishes the negative effect of perceived vaccine artificiality. Two studies with European young adults measured COVID-19 vaccination intent and vertical collectivism. Study 1 (N = 418) was correlational, measuring perceived vaccine artificiality. The data were analyzed with a moderation model. Study 2 (N = 203) was experimental, manipulating perceived vaccine artificiality by human-intervention appeal (i.e., emphasizing human intervention in vaccine development and operation). The data were analyzed with moderation and moderated mediation models. Study 1 demonstrated that the effect of perceived vaccine artificiality on vaccination intent was less negative when the level of vertical collectivism was higher. In Study 2, with higher levels of vertical collectivism, the effect of human-intervention appeal on vaccination intent was less negative, and the indirect effect through perceived vaccine artificiality turned even positive. Those results contribute to the fields of perceived naturalness/artificiality, vaccination behavior, health communication, and cultural dimensions theory, providing empirical evidence that the negative effect of perceived vaccine artificiality on vaccination intent is diminished by vertical collectivism, as proposed. Health practitioners are guided on how to consider different levels of collectivism of their audiences while referring to vaccine artificiality in their communication. Specifically, it is suggested that rebutting "unnaturalness" anti-vaccine arguments should be focused on people low in vertical collectivism, and messages featuring human intervention (e.g., a vaccine's technological advancement) should be targeted at people high in vertical collectivism. [ABSTRACT FROM AUTHOR]

The linkages between the US and China, the world's two major agricultural powers, have brought great uncertainty to the global food markets. Inspired by these, this paper examines the extreme risk spillovers between US and Chinese agricultural futures markets during significant crises. We use a copula-conditional value at risk (CoVaR) model with Markov-switching regimes to capture the tail dependence in their pair markets. The study covers the period from January 2006 to December 2022 and identifies two distinct dependence regimes (stable and crisis periods). Moreover, we find significant and asymmetric upside/downside extreme risk spillovers between the US and Chinese markets, which are highly volatile in crises. Additionally, the impact of international capital flows (the financial channel) on risk spillovers is particularly pronounced during the global financial crisis. During the period of the COVID-19 pandemic and the Russia-Ukraine 2022 war, the impact of supply chain disruptions (the non-financial channel) is highlighted. Our findings provide a theoretical reference for monitoring the co-movements in agricultural futures markets and practical insights for managing investment portfolios and enhancing food market stability during crises. [ABSTRACT FROM AUTHOR]

Background: Data on SARS-CoV-2 infection in pregnancy and infancy has accumulated throughout the course of the pandemic, though evidence regarding asymptomatic SARS-CoV-2 infection and adverse birth outcomes are scarce. Limited information is available from countries in sub-Saharan Africa (SSA). The pregnant woman and infant COVID in Africa study (PeriCOVID Africa) is a South-South-North partnership involving hospitals and health centres in five countries: Malawi, Uganda, Mozambique, The Gambia, and Kenya. The study leveraged data from three ongoing prospective cohort studies: Preparing for Group B Streptococcal Vaccines (GBS PREPARE), SARS-CoV-2 infection and COVID-19 in women and their infants in Kampala and Mukono (COMAC) and Pregnancy Care Integrating Translational Science Everywhere (PRECISE). In this paper we describe the seroepidemiology of SARS-CoV-2 infection in pregnant women enrolled in sites in Uganda and Malawi, and the impact of SARS-CoV-2 infection on pregnancy and infant outcomes. Outcome: Seroprevalence of SARS-CoV-2 antibodies in maternal blood, reported as the proportion of seropositive women by study site and wave of COVID-19 within each country. Methods: The PeriCOVID study was a prospective mother-infant cohort study that recruited pregnant women at any gestation antenatally or on the day of delivery. Maternal and cord blood samples were tested for SARS-CoV-2 antibodies using Wantai and Euroimmune ELISA. In periCOVID Uganda and Malawi nose and throat swabs for SARS-Cov-2 RT-PCR were obtained. Results: In total, 1379 women were enrolled, giving birth to 1387 infants. Overall, 63% of pregnant women had a SARS-CoV-2 positive serology. Over subsequent waves (delta and omicron), in the absence of vaccination, seropositivity rose from 20% to over 80%. The placental transfer GMR was 1.7, indicating active placental transfer of anti-spike IgG. There was no association between SARS-CoV-2 antibody positivity and adverse pregnancy or infancy outcomes. [ABSTRACT FROM AUTHOR]

Using qualitative interview data (n = 142 interviews) generated with 50 nurses, over the course of the COVID-19 pandemic, this paper traces the trajectories of nurses in the UK and attempts to unpick the interplay between structure and agency in their narratives. Interviews were inductively analysed for themes and an additional narrative analysis was undertaken to preserve the form of each participant's narrative. We argue that nurses' pandemic trajectories occurred within the 'psychological vulnerability-stigma nexus' which operates within health and social care providers in the UK and whilst constraining nurses' agency at times it could also provide an impetus to act agentically. We found that the nurses' COVID-19 trajectories were characterised by: getting by, getting out (job-hopping) getting needs met and getting organised. We call for more considered systemic support to be generated and consistently provided to nurses to ensure retention of nurses and the security of society to avoid exacerbating existing workforce shortages. [ABSTRACT FROM AUTHOR]

Introduction: The COVID-19 pandemic disproportionately affected older adults, particularly those with pre-existing chronic health conditions. To address the health disparity and challenges faced by under-resourced African American older adults in South Los Angeles during this period, we implemented a hybrid (virtual/in-person), pre-post, community-based participatory intervention research project utilizing a faith-based lay health advisor model (COVID-19 Health Ambassador Program (CHAP)). We recruited COVID-19 Health Ambassadors (CHAs) and African American older adults (participants) from faith-based organizations who partook in CHA-led meetings and follow-ups that educated and supported the participants. This paper seeks to evaluate this intervention's implementation using the Consolidated Framework for Implementation Research (CFIR) as a reporting tool with an emphasis on fidelity, challenges, and adaptations based on data collected via stakeholder interviews and surveys. Results: CHAP was delivered to 152 participants by 19 CHAs from 17 faith-based organizations. CHAs assisted with chronic disease management, resolved medication-related challenges, encouraged COVID-19 vaccination, reduced psychological stress and addressed healthcare avoidance behaviors such as COVID-19 vaccine hesitancy among the participants. Challenges encountered include ensuring participant engagement and retention in the virtual format and addressing technological barriers for CHAs and participants. Adaptations made to better suit the needs of participants included providing communication tools and additional training to CHAs to improve their proficiency in using virtual platforms in addition to adapting scientific/educational materials to suit our participants' diverse cultural and linguistic needs. Conclusion: The community-centered hybrid approach in addition to our partnership with faith-based organizations and their respective COVID-19 health ambassadors proved to be essential in assisting underserved African American older adults manage chronic health conditions and address community-wide health disparities during the COVID-19 pandemic. Adaptability, cultural sensitivity, and teamwork are key to implementing health interventions especially in underserved populations. [ABSTRACT FROM AUTHOR]

The paper examines the health system's response to COVID-19 in Sierra Leone. It aims to explore how the pandemic affected service delivery, health workers, patient access to services, leadership, and governance. It also examines to what extent the legacy of the 2013–16 Ebola outbreak influenced the COVID-19 response and public perception. Using the WHO Health System Building Blocks Framework, we conducted a qualitative study in Sierra Leone where semi-structured interviews were conducted with health workers, policymakers, and patients between Oct-Dec 2020. We applied thematic analysis using both deductive and inductive approaches. Twelve themes emerged from the analysis: nine on the WHO building blocks, two on patients' experiences, and one on Ebola. We found that routine services were impacted by enhanced infection prevention control measures. Health workers faced additional responsibilities and training needs. Communication and decision-making within facilities were reported to be coordinated and effective, although updates cascading from the national level to facilities were lacking. In contrast with previous health emergencies which were heavily influenced by international organisations, we found that the COVID-19 response was led by the national leadership. Experiences of Ebola resulted in less fear of COVID-19 and a greater understanding of public health measures. However, these measures also negatively affected patients' livelihoods and their willingness to visit facilities. We conclude, it is important to address existing challenges in the health system such as resources that affect the capacity of health systems to respond to emergencies. Prioritising the well-being of health workers and the continued provision of essential routine health services is important. The socio-economic impact of public health measures on the population needs to be considered before measures are implemented. [ABSTRACT FROM AUTHOR]

Background: The outbreak of the COVID-19 pandemic compelled the closure of educational institutions and forced students to complete nearly two years of schooling online, impacting their physical and emotional development tremendously. This exploratory study investigates the wide-ranging impact of online education on Indian students during the COVID-19 pandemic and discusses the challenges exacerbated by disparities in access to digital devices and reliable internet service. The paper also focuses on the physical and mental health issues that arose in student cohorts as a result of the abrupt shift to online learning, and investigates the relationship between students' socioeconomic status and the nature and frequency of health issues experienced by them. Methods: A total of 832 respondents completed a 40-item survey that was administered online and through interviews. The paper analysed the impact of access to digital resources and teachers' training in information and communication technology on the perception of the quality of education provided by the institutions. We further analysed the impact of the adoption of online educational platforms on students' mental and physical health. Results: The study found a positive relationship between the number of hours spent online, and the physical and mental health issues experienced by students. Participants reported an overall higher perception of stress and anxiety, loss of concentration, and dissatisfaction with the quality of education. Our data suggest that COVID-19 has exacerbated the digital divide. Discussion: Urgent investments are needed to provide universal access to reliable internet services, and to develop a pedagogy that supports an agile and adaptable educational system, capable of providing effective learning and evaluation, while supporting students' physical and mental health. [ABSTRACT FROM AUTHOR]

Understanding the dynamic link between the development of COVID-19 pandemic and industry sector risk spillovers is crucial to explore the underlying mechanisms by which major public health events affect economic systems. This paper applies ElasticNet method proposed by Diebold and Yilmaz (2009, 2012, 2014) to estimate the dynamic risk spillover indicators of 20 industrial sectors in China from 2016 to 2022, and systematically examines the impact of industry risk network fluctuations and the transmission path caused by COVID-19 shock. The findings reveal that risk spillovers of Chinese industries show a dynamic change of "decline-fluctuation-rebound" with the three phases of COVID-19 epidemic. At the beginning of the epidemic, machinery and equipment, paper and printing, tourism and hotels, media and information services, and agriculture were the exporters of epidemic risk, while materials, transportation equipment, commercial trade, health care, and environmental protection were the importers of epidemic risk; However, as the epidemic developed further, the direction and effect of risk transmission in the industry was reversed. Examining the network characteristics of the pair sectors, we found that under the epidemic shock, the positive risk spillover from tourism and hotels, culture, education and sports to consumer goods, finance, and energy industries was significantly increased, and finance and real estate industries were affected by the risk impact of more industries, while the number of industries affected by information technology and computer industry was significantly reduced. This paper shows that there is inter-industry risk transmission of the COVID-19 epidemic shock, and the risk transmission feeds back in a cycle between industries as the epidemic develops, driving the economy into a vicious circle. The role of the service sector in blocking the spread of negative shocks from the epidemic should be emphasized and brought into play to avoid increasing the overall economic vulnerability. This study will help to deepen the understanding of scholars and policy makers on the network transmission effects of the epidemic. [ABSTRACT FROM AUTHOR]

Background: Face to face mode of delivery has been a standard method of teaching courses in the majority of African Universities Tanzania included. The COVID-19 pandemic has caused the closure of all schools and universities worldwide; therefore, face-to-face teaching is no longer the only appropriate and feasible teaching method. This requires changes in the teaching method with the remarkable rise of e-learning, whereby teaching must be undertaken remotely and on digital platforms. Objective: The main objective of this study is to determine the perceived factors that hinder the adoption of online teaching in Tanzanian universities. Method: A mixed method dominated by a quantitative approach was used to answer the research questions. A total of 173 academic and ICT staff from nineteen universities in Tanzania participated in this study. Descriptive statistics (univariate analysis) and binary logistic regression were applied to analyse the frequency and compare the mean to describe the characteristics of respondents and determine the factors influencing the academic staff to have an online course. This was followed by content analysis to analyse the academic staff's proposed adaptation to online classes. Results: The findings indicated that the main hindrances to online teaching are lack of capacity; knowledge on how to conduct online courses; knowledge and technological factors; environmental factors; staff attitudes towards delivering online courses, and years spent using eLearning. The academic staff proposed improving ICT infrastructure and strengthening the capacity of academic staff to provide online courses. Conclusion: The study concludes that most academic staff are willing to adopt online teaching while suggesting improving the organisational and individual factors to enhance online education. The paper recommends that the university use freely available online teaching tools and platforms while simultaneously focusing on addressing the corporate and individual factors identified in this paper to enhance online teaching, which is mandatory in response to lockdown measures. [ABSTRACT FROM AUTHOR]

Addressing risks and pandemics at a country level is a complex task that requires transdisciplinary approaches. The paper aims to identify groups of the European Union countries characterized by a similar COVID-19 Resilience Index (CRI). Developed in the paper CRI index reflects the countries' COVID-19 risk and their readiness for a crisis situation, including a pandemic. Moreover, the study detects the factors that significantly differentiate the distinguished groups. According to our research, Bulgaria, Hungary, Malta, and Poland have the lowest COVID-19 Resilience Index score, with Croatia, Greece, Czechia, and Slovakia following close. At the same time, Ireland and Scandinavian countries occupy the top of the leader board, followed by Luxemburg. The Kruskal-Wallis test results indicate four COVID-19 risk indicators that significantly differentiate the countries in the first year of the COVID-19 pandemic. Among the significant factors are not only COVID-19-related factors, i.e., the changes in residential human mobility, the stringency of anti-COVID-19 policy, but also strictly environmental factors, namely pollution and material footprint. It indicates that the most critical global environmental issues might be crucial in the phase of a future pandemic. Moreover, we detect eight readiness factors that significantly differentiate the analysed country groups. Among the significant factors are the economic indicators such as GDP per capita and labour markets, the governance indicators such as Rule of Law, Access to Information, Implementation and Adaptability measures, and social indicators such as Tertiary Attainment and Research, Innovation, and Infrastructure. [ABSTRACT FROM AUTHOR]

The 2019 novel coronavirus (SARS-CoV-2 / COVID-19), with a point of origin in Wuhan, China, has spread rapidly all over the world. It turned into a raging pandemic wrecking havoc on health care facilities, world economy and affecting everyone's life to date. With every new variant, rate of transmission, spread of infections and the number of cases continues to rise at an international level and scale. There are limited reliable researches that study microdroplets spread and transmissions from human sneeze or cough in the airborne space. In this paper, we propose an intelligent technique to visualize, detect, measure the distance of spread in a real-world settings of microdroplet transmissions in airborne space, called "COVNET45". In this paper, we investigate the microdroplet transmission and validate the measurements accuracy compared to published researches, by examining several microscopic and visual images taken to investigate the novel coronavirus (SARS-CoV-2 / COVID-19). The ultimate contribution is to calculate the spread of the microdroplets, measure it precisely and provide a graphical presentation. Additionally, the work employs machine learning and five algorithms for image optimization, detection and measurement. [ABSTRACT FROM AUTHOR]

Introduction: Lebanon has battled the COVID-19 pandemic in the midst of an economic crisis. The evolution of the pandemic and a fragile health system have meant that public health policy has had to rely heavily on non-pharmaceutical interventions for disease control. However, changes in disease dynamics, an unraveling economy, and pandemic fatigue have meant that disease control policies need to be updated. Methods: Using recent and timely data on older (50 years and above) Syrian refugees in Lebanon, this paper uses multivariate linear probability models to explore the determinants of adherence to two non-pharmaceutical COVID-19 prevention measures (wearing a mask and avoiding social gatherings) among this high-risk subgroup in a vulnerable population. Among respondents who report adhering to these measures, the paper also investigates the determinants of sustained adherence over a period of 6 months. Results: The findings suggest that no individual-level characteristics were robustly associated with mask wearing. For avoiding social gatherings, education was inversely associated with adherence to this preventive measure. Avoiding social gatherings was also significantly lower for residents of informal tented settlements (ITSs). Among initial adherents, and for both preventive practices, ITS dwellers were also significantly less likely to maintain adherence. Conclusion: Identifying variables associated with adherence to non-pharmaceutical preventive practices, particularly for vulnerable groups, can help inform and refine interventions in the face of changing conditions. The material, physical, administrative and socio-economic constraints of life in an ITS suggest that avoiding social gatherings is hardly feasible. Yet despite the challenging conditions of ITSs, the indication to wear a mask is initially complied with, suggesting that tailoring policies to the limits and constrains of context can lead to successful outcomes even in very adverse settings. [ABSTRACT FROM AUTHOR]

During pandemics like COVID-19, both the quality and quantity of services offered by businesses and organizations have been severely impacted. They often have applied a hybrid home office setup to overcome this problem, although in some situations, working from home lowers employee productivity. So, increasing the rate of presence in the office is frequently desired from the manager's standpoint. On the other hand, as the virus spreads through interpersonal contact, the risk of infection increases when workplace occupancy rises. Motivated by this trade-off, in this paper, we model this problem as a bi-objective optimization problem and propose a practical approach to find the trade-off solutions. We present a new probabilistic framework to compute the expected number of infected employees for a setting of the influential parameters, such as the incidence level in the neighborhood of the company, transmission rate of the virus, number of employees, rate of vaccination, testing frequency, and rate of contacts among the employees. The results show a wide range of trade-offs between the expected number of infections and productivity, for example, from 1 to 6 weekly infections in 100 employees and a productivity level of 65% to 85%. This depends on the configuration of influential parameters and the occupancy level. We implement the model and the algorithm and perform several experiments with different settings of the parameters. Moreover, we developed an online application based on the result in this paper which can be used as a recommender for the optimal rate of occupancy in companies/workplaces. [ABSTRACT FROM AUTHOR]

Since 2020, the world has faced two unprecedented shocks: lockdowns (regulation) and the invasion of Ukraine (war). Although we realise the health and economic effects of these shocks, more research is needed on the effect on happiness and whether the type of shock plays a role. Therefore, in this paper, we determine whether these macro-level shocks affected happiness, how these effects differ, and how long it takes for happiness to adapt to previous levels. The latter will allow us to test whether adaptation theory holds at the macro level. We use a unique dataset of ten countries spanning the Northern and Southern hemispheres derived from tweets extracted in real-time per country. Applying Natural Language Processing, we obtain these tweets' underlying sentiment scores, after which we calculate a happiness score (Gross National Happiness) and derive daily time series data. Our Twitter dataset is combined with Oxford's COVID-19 Government Response Tracker data. Considering the results of the Difference-in-Differences and event studies jointly, we are confident that the shocks led to lower happiness levels, both with the lockdown and the invasion shock. We find that the effect size is significant and that the lockdown shock had a bigger effect than the invasion. Considering both types of shocks, the adaptation to previous happiness levels occurred within two to three weeks. Following our findings of similar behaviour in happiness to both types of shocks, the question of whether other types of shocks will have similar effects is posited. Regardless of the length of the adaptation period, understanding the effects of macro-level shocks on happiness is essential for policymakers, as happiness has a spillover effect on other variables such as production, safety and trust. [ABSTRACT FROM AUTHOR]

Africa has been known to experience series of problems among which are poverty, food insecurity, lack of access to energy, lack of infrastructure among others. These problems were exacerbated by the COVID-19 pandemic, which has had a severe impact on the socioeconomic status of households in Africa. This paper examines the relationship between socioeconomic shocks, social protection, and household food security during the pandemic in Nigeria, the Africa's largest economy. Using the World Bank's COVID-19 national longitudinal baseline phone survey (2020) for the analysis and applied the multinomial logit regression, the study finds that socioeconomic shocks resulting from the pandemic have led to an increased level of food insecurity. Social protection programmes have played a crucial role in mitigating the impact of these shocks on households. However, the study also highlights the need for more targeted and effective social protection policies to ensure that vulnerable households are adequately protected from the adverse effects of the pandemic. The findings of this study have important implications for policymakers and stakeholders in Africa's largest economy, as they seek to address the challenges posed by the pandemic and promote household food security for the actualisation the United Nations (UN) Sustainable Development Goal (SDG) of food and nutrition security (SDG2). The study, therefore, recommends that efforts be made to preserve food supply chains by mitigating the pandemic's effect on food systems, increasing food production, and looking forward beyond the pandemic by building resilient food systems with the use of social protection interventions. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic was accompanied by an "infodemic" of misinformation. Misleading narratives around the virus, its origin, and treatments have had serious implications for public health. In March 2021, concerns were raised about links between the Oxford/AstraZeneca (AZ) COVID-19 vaccine and recipients developing blood clots. This paper aims to identify whether this prompted any reaction in the diffusion of low-credibility COVID-19-relate information on Twitter. Twitter's application programming interface was used to collect data containing COVID-19-related keywords between 4th and 25th March 2021, a period centred on the peak of new coverage linking rare blood clots with the AZ vaccine. We analysed and visualised the data using temporal analysis and social network analysis tools. We subsequently analysed the data to determine the most influential users and domains in the propagation of low-credibility information about COVID-19 and the AZ vaccine. This research presents evidence that the peak of news coverage linking rare blood clots with the AZ vaccine correlated with an increased volume and proportion of low-credibility AZ-related content propagated on Twitter. However, no equivalent changes to the volume, propagation, or network structure for the full dataset of COVID-19-related information or misinformation were observed. The research identified RT.com as the most prolific creator of low-credibility COVID-19-related content. It also highlighted the crucial role of self-promotion in the successful propagation of low-credibility content on Twitter. The findings suggest that the simple approach adopted within the research to identify the most popular and influential sources of low-credibility content presents a valuable opportunity for public health authorities and social media platforms to develop bespoke strategies to counter the propagation of misinformation in the aftermath of a breaking news event. [ABSTRACT FROM AUTHOR]

The aftermath of COVID changed how students learn, mainly moving to a distance learning model. The research reported in this paper investigated the organizational and individual factors that influence the preference for continuing with distance / online learning post-COVID. Partial least squares structural equation modeling was applied to a model developed for this research, based on data from 452 students from residential universities in South Africa. The key results reveal an overall reluctance to continue with distance learning. This is despite the technological and faculty support offered to university students and how distance learning fits their learning styles. This is likely due to student living conditions and their perception of low institutional concern. On the other hand, faculty support has a more substantial impact on continuance, compared with a generally negative perception of support from the universities. The research underscores the importance of addressing student reluctance to continue with distance learning by improving institutional support and tailoring learning styles. The research enhances our understanding of crucial factors influencing students' preference for distance/online learning post-COVID. It also underscores the pedagogical shifts brought about by the pandemic, particularly highlighting the changing roles of faculty support and the impact on students' living conditions. [ABSTRACT FROM AUTHOR]

Objectives: The COVID-19 pandemic showed distinct waves where cases ebbed and flowed. While each country had slight, nuanced differences, lessons from each wave with country-specific details provides important lessons for prevention, understanding medical outcomes and the role of vaccines. This paper compares key characteristics from the five different COVID-19 waves in Pakistan. Methods: Data was sourced from daily national situation reports (Sitreps) prepared by the National Emergency Operations Centre (NEOC) in Islamabad. We use specific criteria to define COVID-19 waves. The start of each COVID-19 wave is marked by the day of the lowest number of daily cases preceding a sustained increase, while the end is the day with the lowest number of cases following a 7-days decline, which should be lower than the 7 days following it. Key variables such as COVID-19 tests, cases, and deaths with their rates of change to the peak and then to the trough are used to draw descriptive comparisons. Additionally, a linear regression model estimates daily new COVID-19 deaths in Pakistan. Results: Pakistan saw five distinct waves, each of which displayed the typical topology of a complete infectious disease epidemic. The time from wave-start to peak became progressively shorter, and from wave-peak to trough, progressively longer. Each wave appears to also be getting shorter, except for wave 4, which lasted longer than wave 3. A one percent increase in vaccinations decreased deaths by 0.38% (95% CI: -0.67, -0.08) in wave 5 and the association is statistically significant. Conclusion: Each wave displayed distinct characteristics that must be interpreted in the context of the level of response and the variant driving the epidemic. Key indicators suggest that COVID-19 preventive measures kept pace with the disease. Waves 1 and 2 were mainly about prevention and learning how to clinically manage patients. Vaccination started late during wave 3 and its impact on hospitalizations and deaths became visible in wave 5. The impact of highly virulent strains Alpha/B.1.1.7 and Delta/B.1.617.2 variants during wave 3 and milder but more infectious Omicron/B.1.1.529 during wave 5 are apparent. [ABSTRACT FROM AUTHOR]

Objectives: To explore experiences of U.S. (United States) nursing home leadership during the COVID-19 pandemic in their efforts to address resident loneliness and social isolation and to elicit stories about personal and professional impacts on themselves and staff. Design: Qualitative inquiry via three optional open-ended questions appended to a national self-administered survey of American nursing home leaders was employed. Textual data was analyzed using an iterative reflexive thematic approach. Setting and participants: A stratified sample frame defined by facility size (beds: 30–99, 100+) and quality ratings (1, 2–4, 5) was employed. Web survey links and paper surveys were sent to 1,676 nursing home directors of nursing between February and May 2022. Results: Open text responses were collected from 271 nursing homes. Broad themes included: 1) Addressing needs of residents & families; 2) Challenges; and 3) Personal experiences of nursing home leadership/staff. Respondents described trauma to residents, staff, and leadership. Resident loneliness was addressed using existing and newer technologies and innovative indoor and outdoor activities. Residents experienced fear, illness, loss, and sometimes death. Isolation from family and lack of touch were particularly difficult. Regulations were seen as punitive while ignoring emotional needs of residents. Staffing challenges and pressures to do more with less created additional stress. Leadership and staff made significant sacrifices resulting in physical, social, and emotional consequences. Beneficial outcomes included staff bonding, professional growth, and permanent implementation of new interventions. Conclusions and implications: New and creative interventions were successfully implemented to address social isolation and loneliness. Improved Wi-Fi and other nursing home infrastructure upgrades are needed to maintain them. Reimagining often conflicting overlapping federal, state, and local regulations, grounding them in good clinical judgement, and incentivizing performance improvement should be considered. Trauma experienced by staff needs to be addressed to deal with current and future workforce needs. [ABSTRACT FROM AUTHOR]

Against the background of the global active pursuit of carbon neutrality, this paper uses the DY spillover index method to analyze the spillover network effects between carbon, fossil energy and financial markets. The research results show that the spillover effects between these three markets change over time, with an average spillover index of 25.30%, showing a significant mutual influence. Further analysis found that the EU carbon market plays an important role in spillover effects. Especially under the influence of extreme events, the spillover effects reach their peak. At this time, the degree of mutual influence between markets is as high as 60.01%. In addition, during the COVID-19 epidemic, the spillover effect of the EU carbon market on other markets also reached its maximum, indicating that the epidemic increased the contagion of cross-market risks and caused the carbon market to bear greater risks. The research results of this article have important guiding significance for environmental protection investment and emphasize the importance of formulating differentiated environmental protection policies in different time frames. Facing the dual challenges of global climate change and promoting the goal of carbon neutrality, governments and relevant institutions should pay close attention to changes in spillover effects between markets and timely adjust environmental protection policies to achieve maximum results. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic in Brazil has brought many challenges, particularly regarding the management of hospital capacity, and a new demand for healthcare that added to the preexisting demands, such as neoplasms, cardiovascular diseases and births. In this paper, we estimate the impact of the pandemic on the number of deaths and hospitalizations for other diseases. We construct a monthly panel data of deaths and hospitalizations for various causes by the municipality of residence and relate them to COVID-19 hospitalizations using regression models that control for municipalities fixed-effects and interactions between State and month fixed-effects. The standard errors are clustered at the municipality level. Our estimates imply that 100 more hospitalizations by COVID-19 is associated with a drop of 49 non-COVID-19 hospitalizations and an additional four deaths for other reasons (all measured per 100,000 pop.). The impact of intensive care units COVID-19 hospitalizations on mortality is larger. The groups most affected are the African Brazilians, less-educated and the elderly. Additional deaths occurred both at households and at hospitals. The main causes of additional deaths were diseases related to the circulatory and endocrine system. The decline in hospitalizations for other causes seems to be related to the overcrowding of hospitals in periods of surge in the COVID-19, alongside with the fall in the demand for care by the citizens who were afraid of COVID-19 infection. These mechanisms affected more strongly the vulnerable groups of the population. Our results highlight the importance of promoting the awareness of heightened risk of non-communicable chronic diseases during a health emergency context. This should be done preferably through already established channels with community outreach, such as the Family Health Program in Brazil. [ABSTRACT FROM AUTHOR]

Objective: A scoping review of studies published in the first year of the COVID-19 pandemic focused on individuals with pre-existing symptoms of depression, anxiety, and specified stressor-related disorders, with the objective of mapping the research conducted. Eligibility criteria: (1) direct study of individuals with pre-existing depressive, anxiety, and/or specified stressor-related (i.e., posttraumatic stress, acute stress) disorders/issues; (2) focus on mental health-related pandemic effects, and; (3) direct study of mental health symptoms related to depression, anxiety, or psychological distress. Sources of evidence: Database-specific subject headings and natural language keywords were searched in Medline, Embase, APA PsycInfo, and Cumulative Index to Nursing & Allied Health Literature (CINAHL) up to March 3, 2021. Review of potentially relevant studies was conducted by two independent reviewers and proceeded in two stages: (1) title and abstract review, and; (2) full paper review. Data charting: Study details (i.e., location, design and methodology, sample or population, outcome measures, and key findings) were extracted from included studies by one reviewer and confirmed by the Principal Investigator. Results: 66 relevant articles from 26 countries were identified. Most studies adopted a cross-sectional design and were conducted via online survey. About half relied on general population samples, with the remainder assessing special populations, primarily mental health patients. The most commonly reported pre-existing category of disorders or symptoms was depression, followed closely by anxiety. Most studies included depressive and anxiety symptoms as outcome measures and demonstrated increased vulnerability to mental health symptoms among individuals with a pre-existing mental health issue. Conclusion: These findings suggest that improved mental health supports are needed during the pandemic and point to future research needs, including reviews of other diagnostic categories and reviews of research published in subsequent years of the pandemic. [ABSTRACT FROM AUTHOR]

When the COVID-19 pandemic first emerged in early 2020, healthcare and bureaucratic systems worldwide were caught off guard and largely unprepared to deal with the scale and severity of the outbreak. In Italy, this led to a severe underreporting of infections during the first wave of the spread. The lack of accurate data is critical as it hampers the retrospective assessment of nonpharmacological interventions, the comparison with the following waves, and the estimation and validation of epidemiological models. In particular, during the first wave, reported cases of new infections were strikingly low if compared with their effects in terms of deaths, hospitalizations and intensive care admissions. In this paper, we observe that the hospital admissions during the second wave were very well explained by the convolution of the reported daily infections with an exponential kernel. By formulating the estimation of the actual infections during the first wave as an inverse problem, its solution by a regularization approach is proposed and validated. In this way, it was possible to compute corrected time series of daily infections for each age class. The new estimates are consistent with the serological survey published in June 2020 by the National Institute of Statistics (ISTAT) and can be used to speculate on the total number of infections occurring in Italy during 2020, which appears to be about double the number officially recorded. [ABSTRACT FROM AUTHOR]

The COVID-19 epidemic had an appropriate impact on tourists' trip psychology and their subsequent behavior in participating in rural tourism activities. The purpose of this paper is to explore the types of motivations Chinese tourists have for participating in rural tourism in the context of COVID-19, and to comparatively analyze the similarities and differences in motivations for rural tourism during the epidemic and in normal times. An interpretive paradigm qualitative data collection method was used: semi-structured interviews and focus group discussions. Respondents were 21 tourists, who were selected through purposive and snowball sampling. Through content analysis, we found that rural tourism motivations during the epidemic included both diversified and singular motivations. The pull effect of rural destinations is related to distance and ease of realization. For rural areas in close proximity, a single motivation is sufficient to drive tourists. In addition, we found that there was no "altruistic motivation" for rural tourism during the COVID-19 period, but "altruistic feelings" for the preservation of ancient villages were generated during rural tourism. Finally, we discuss the theoretical and practical significance of this study and make suggestions for future research. The study explains tourists' companionship preferences, activity choices, and affective changes, and provides a basis for the operation and advertising strategies of rural destinations to attract tourists and promote their sustainable development. [ABSTRACT FROM AUTHOR]

This paper examines the linkage between Chinese stock market volatility and investor attention fluctuation. In Heterogeneous autoregressive (HAR) model, first, we analyzed the linkage between both decomposed and undecomposed stock market realized volatility and investor attention fluctuations across full-sample and two-year moving window sub-samples. Second, we compare the predictive power of four models in short-, medium-, and long-term volatility forecasting. Empirical results show large positive attention fluctuation amplified Chinese stock market volatility after the outbreak of COVID-19, and negative small attention fluctuation significantly stabilized stock market volatility before COVID-19, and the impact dwindled in after COVID-19. The model incorporating decomposed realized volatility and decomposed attention fluctuation performs better in volatility Forecasting. This research underscores a shift in the dynamics between stock market volatility and investor attention fluctuations, and investor attention fluctuation improves the volatility forecasting accuracy of the Chinese stock market. [ABSTRACT FROM AUTHOR]

This paper conducts a systematic statistical analysis of the characteristics of the geographical empirical distributions for the numbers of both cumulative and daily confirmed COVID-19 cases and deaths at county, city, and state levels over a time span from January 2020 to June 2022. The mathematical heavy-tailed distributions can be used for fitting the empirical distributions observed in different temporal stages and geographical scales. The estimations of the shape parameter of the tail distributions using the Generalized Pareto Distribution also support the observations of the heavy-tailed distributions. According to the characteristics of the heavy-tailed distributions, the evolution course of the geographical empirical distributions can be divided into three distinct phases, namely the power-law phase, the lognormal phase I, and the lognormal phase II. These three phases could serve as an indicator of the severity degree of the COVID-19 pandemic within an area. The empirical results suggest important intrinsic dynamics of a human infectious virus spread in the human interconnected physical complex network. The findings extend previous empirical studies and could provide more strict constraints for current mathematical and physical modeling studies, such as the SIR model and its variants based on the theory of complex networks. [ABSTRACT FROM AUTHOR]

This paper estimated the impact of intervention effects (state of emergency (SOE) or quasi-SOE requirements) and information effects (publicized increases in the number of coronavirus disease 2019 (COVID-19) deaths and fear of infection) on preventive behaviors and telecommuting during the COVID-19 pandemic using the Japan Household Panel Survey. Our results indicated that SOEs and quasi-SOEs had positive effects on the adoption of preventive behaviors among individuals, including handwashing, which indicates that an SOE has a direct effect and an indirect effect. Although SOEs in Japan were less enforceable and more lenient than those in other countries, they still had a certain effect on people's adoption of preventive behaviors. However, the contribution of information effects was much larger than that of intervention effects, suggesting the importance of how and when information should be communicated to the public to prevent the spread of infection. [ABSTRACT FROM AUTHOR]

Background: South Asians are a rapidly growing population in the United States. Breast cancer is a major concern among South Asian American women, who are an understudied population. We established the South Asian Breast Cancer (SABCa) study in New Jersey during early 2020 to gain insights into their breast cancer-related health attitudes. Shortly after we started planning for the study, the COVID-19 disease spread throughout the world. In this paper, we describe our experiences and lessons learned from recruiting study participants by partnering with New Jersey's community organizations during the COVID-19 pandemic. Methods: We used a cross-sectional design. We contacted 12 community organizations and 7 (58%) disseminated our study information. However, these organizations became considerably busy with pandemic-related needs. Therefore, we had to pivot to alternative recruitment strategies through community radio, Rutgers Cancer Institute of New Jersey's Community Outreach and Engagement Program, and Rutgers Cooperative Extension's community health programs. We recruited participants through these alternative strategies, obtained written informed consent, and collected demographic information using a structured survey. Results: Twenty five women expressed interest in the study, of which 22 (88%) participated. Nine (41%) participants learned about the study through the radio, 5 (23%) through these participants, 1 (4.5%) through a non-radio community organization, and 7 (32%) through community health programs. Two (9%) participants heard about the study from their spouse. All participants were born outside the US, their average age was 52.4 years (range: 39–72 years), and they have lived in the US for an average of 26 years (range: 5–51 years). Conclusion: Pivoting to alternative strategies were crucial for successful recruitment. Findings suggest the significant potential of broadcast media for community-based recruitment. Family dynamics and the community's trust in our partners also encouraged participation. Such strategies must be considered when working with understudied populations. [ABSTRACT FROM AUTHOR]

Previous studies have examined WATER metaphors in different discourses, yet there has been limited focus on understanding the functions of these metaphors in constructing discourses. To address this research gap, the present paper utilised the metaphor identification procedure developed by the Pragglejaz Group and the Weak Differentiating Model to investigate WATER metaphors in the Coronavirus Corpus. The study reveals that WATER metaphors can be used flexibly for multiple purposes. These include explaining the many pandemic stages, describing the occurrence and performance of the pandemic, explaining how COVID-19 affects human life, rallying the public to take precautions against contagion, and communicating risk. This research highlights the diverse functions that WATER metaphors served in conveying intricate information and influencing public perceptions throughout the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Introduction: During the COVID-19 pandemic, general practitioners (GPs) continued to be a main point of contact for patients. For GP practices, it was and still is a challenge to meet constantly changing requirements due to the various phases of the pandemic. The aim of the study is to explore retrospectively the subjective experience with supply and utilization of health care services from the perspective of general practitioners, medical practice assistants and patients, in particular regarding instances of underutilization of services for non-Covid related conditions, adjustments due to the pandemic, and the appropriateness of care. Methods: The study is carried out within the RESPoNsE research practice network in three of Germany's federal states: Berlin, Brandenburg, and Thuringia (RESPoNsE—Research practice network east). The study follows a convergent mixed method design, and consists of the following sections: a) two anonymous paper-based questionnaires filled out by GPs and medical practice assistants (MPAs), at an interval of 12 to 18 months; b) in-depth qualitative interviews conducted among a subgroup of GPs and MPAs; c) anonymous paper-based questionnaires among patients of participating practices. The idea for the study was derived from discussions with the practice advisory board of the RESPoNsE network. The themes and issues to be explored in the surveys and interviews are developed and discussed in the practice advisory board, the patient advisory board, and with interested MPAs. The questionnaires will be analyzed descriptively, exploring the effect of demographic variables. Qualitative content analysis is used to analyze the data from the interviews and focus groups. Discussion: The study focuses on the conditions of GP care during the COVID-19 pandemic. A broad insight is provided as GPs and MPAs, as well as patients, are involved. It provides the opportunity to express needs and concerns. The results can support future discussions on lessons learned from the pandemic and necessary changes in health care delivery. Trial registration: Trial registration at the German Clinical Trials Register: DRKS00028095. [ABSTRACT FROM AUTHOR]