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News dissemination plays a vital role in supporting people to incorporate beneficial actions during public health emergencies, thereby significantly reducing the adverse influences of events. Based on big data from YouTube, this research study takes the declaration of COVID-19 National Public Health Emergency (PHE) as the event impact and employs a DiD model to investigate the effect of PHE on the news dissemination strength of relevant videos. The study findings indicate that the views, comments, and likes on relevant videos significantly increased during the COVID-19 public health emergency. Moreover, the public's response to PHE has been rapid, with the highest growth in comments and views on videos observed within the first week of the public health emergency, followed by a gradual decline and returning to normal levels within four weeks. In addition, during the COVID-19 public health emergency, in the context of different types of media, lifestyle bloggers, local media, and institutional media demonstrated higher growth in the news dissemination strength of relevant videos as compared to news & political bloggers, foreign media, and personal media, respectively. Further, the audience attracted by related news tends to display a certain level of stickiness, therefore this audience may subscribe to these channels during public health emergencies, which confirms the incentive mechanisms of social media platforms to foster relevant news dissemination during public health emergencies. The proposed findings provide essential insights into effective news dissemination in potential future public health events. [ABSTRACT FROM AUTHOR]

The success of mass vaccination programs against SARS-CoV-2 hinges on the public's acceptance of the vaccines. During a vaccine roll-out, individuals have limited information about the potential side-effects and benefits. Given the public health concern of the COVID pandemic, providing appropriate information fast matters for the success of the campaign. In this paper, time-trends in vaccine hesitancy were examined using a sample of 35,390 respondents from the Eurofound's Living, Working and COVID-19 (LWC) data collected between 12 February and 28 March 2021 across 28 European countries. The data cover the initial stage of the vaccine roll-out. We exploit the fact that during this period, news about rare cases of blood clots with low blood platelets were potentially linked to the Oxford/AstraZeneca vaccine (or Vaxzeveria). Multivariate regression models were used to analyze i) vaccine hesitancy trends, and whether any trend-change was associated with the link between the AstraZeneca vaccine ii) and blood clots (AstraZeneca controversy), and iii) the suspension among several European countries. Our estimates show that vaccine hesitancy increased over the early stage of the vaccine roll-out (0·002, 95% CI: [0·002 to 0·003]), a positive shift took place in the likelihood of hesitancy following the controversy (0·230, 95% CI: [0·157 to 0·302]), with the trend subsequently turning negative (-0·007, 95% CI: [-0·010 to -0·005]). Countries deciding to suspend the AstraZeneca vaccine experienced an increase in vaccine hesitancy after the suspensions (0·068, 95% CI: [0·04 to 0·095]). Trust in institutions is negatively associated with vaccine hesitancy. The results suggest that SARS-CoV-2 vaccine hesitancy increased steadily since the beginning of the vaccine roll-out and the AstraZeneca controversy and its suspension, made modest (though significant) contributions to increased hesitancy. [ABSTRACT FROM AUTHOR]

Background: COVID-19 has rapidly emerged as a global public health threat with infections recorded in nearly every country. Responses to COVID-19 have varied in intensity and breadth, but generally have included domestic and international travel limitations, closure of non-essential businesses, and repurposing of health services. While these interventions have focused on testing, treatment, and mitigation of COVID-19, there have been reports of interruptions to diagnostic, prevention, and treatment services for other public health threats. Objectives: We conducted a scoping review to characterize the early impact of COVID-19 on HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition. Methods: A scoping literature review was completed using searches of PubMed and preprint servers (medRxiv/bioRxiv) from November 1st, 2019 to October 31st, 2020, using Medical Subject Headings (MeSH) terms related to SARS-CoV-2 or COVID-19 and HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition. Empiric studies reporting original data collection or mathematical models were included, and available data synthesized by region. Studies were excluded if they were not written in English. Results: A total of 1604 published papers and 205 preprints were retrieved in the search. Overall, 8.0% (129/1604) of published studies and 10.2% (21/205) of preprints met the inclusion criteria and were included in this review: 7.3% (68/931) on HIV, 7.1% (24/339) on tuberculosis, 11.6% (26/224) on malaria, 7.8% (19/183) on sexual and reproductive health, and 9.8% (13/132) on malnutrition. Thematic results were similar across competing health risks, with substantial indirect effects of the COVID-19 pandemic and response on diagnostic, prevention, and treatment services for HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition. Discussion: COVID-19 emerged in the context of existing public health threats that result in millions of deaths every year. Thus, effectively responding to COVID-19 while minimizing the negative impacts of COVID-19 necessitates innovation and integration of existing programs that are often siloed across health systems. Inequities have been a consistent driver of existing health threats; COVID-19 has worsened disparities, reinforcing the need for programs that address structural risks. The data reviewed here suggest that effective strengthening of health systems should include investment and planning focused on ensuring the continuity of care for both rapidly emergent and existing public health threats. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has highlighted the importance of citizens' behaviors in the containment of the virus. Individuals might change their intention to adhere to public health prescriptions depending on various personal characteristics, including their own emotional status, which has been recognized to be a crucial psychological factor in orienting people's adherence to public health recommendation during emergency settings. In particular, it is crucial to support citizens' alliance with authorities and feeling of trust: public engagement is a concept that refers to the general involvement of citizens into public affairs which is generally considered an effective approach to enhance citizens' understanding of their crucial role in public affairs. However, so far there is no agreement on the metrics and indexes that should be used to measures public engagement during a health crisis. The aim of this paper is to validate a psychometric scale (PHEs-E), which intends to measure the readiness of individuals to adhere to the prescribed behavioral change to contain the emergency. Data were collected throughout the pandemic in Italy: in particular, five independent samples were recruited starting from March 2020 to March 2021. Results showed that the proposed measure has good psychometric characteristics. A general linear model was computed to assess the differences of public engagement across the different data points and among citizens with different sociodemographic characteristics. Correlations with other psychological constructs (i.e. Anxiety, Depression and Self-Efficacy) were also tested, showing that more engaged citizens have a lower level of anxiety and depression, and a higher self-efficacy. This study's findings indicate that individuals' characteristics may differentiate citizens' motivation to engage in public health behavioral recommendation to prevent the COVID-19 contagion. However the scale could be useful to perform a psychological monitoring of psychological readiness to engage in public health strategies to face critical events and settings. [ABSTRACT FROM AUTHOR]

With the spread of COVID-19, more countries now recommend their citizens to wear facemasks in public. The uptake of facemasks, however, remains far from universal in countries where this practice lacks cultural roots. In this paper, we aim to identify the barriers to mask-wearing in Spain, a country with no mask-wearing culture. We conduct one of the first nationally representative surveys (n = 4,000) about this unprecedented public health emergency and identify the profile of citizens who are more resistant to face-masking: young, educated, unconcerned with being infected, and with an introverted personality. Our results further indicate a positive correlation between a social norm of mask-wearing and mask uptake and demonstrate that uptake of facemasks is especially high among the elderly living in localities where mask-wearing behavior is popular. These results are robust when controlling for respondents' demographics, time spent at home, and occupation fixed effects. Our findings can be useful for policymakers to devise effective programs for improving public compliance. [ABSTRACT FROM AUTHOR]

Existing barriers to care were exacerbated by the development and implementation of necessary public health restrictions during the COVID-19 pandemic. Children with complex care needs and their families represent a small portion of the paediatric population, and yet they require disproportionately high access to services. Little is known about the impact of COVID-19 public health measures on this population. This study will generate evidence to uncover the wider impact of COVID-19 measures on the lives of children with complex care needs and their families in relation to policy and service changes. This multi-site sequential mixed methods study will take place across the Canadian Maritime provinces and use an integrated knowledge translation approach. There are two phases to this study: 1) map COVID-19 public health restrictions and service changes impacting children with complex care needs by conducting an environmental scan of public health restrictions and service changes between March 2020 and March 2022 and interviewing key informants involved in the development or implementation of restrictions and service changes, and 2) explore how children with complex care needs and their families experienced public health restrictions and service changes to understand how their health and well-being were impacted. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has highlighted the importance of local evidence ecosystems in which academia and practice in the Public Health Service (PHS) are interconnected. However, appropriate organizational structures and well-trained staff are lacking and evidence use in local public health decision-making has to be integrated into training programs in Germany. To address this issue, we developed a framework incorporating a toolbox to conceptualize training programs designed to qualify public health professionals for working at the interface between academia and practice. We conducted a scoping review of training programs, key-informant interviews with public health experts, and a multi-professional stakeholder workshop and triangulated their output. The resulting toolbox consists of four core elements, encompassing 15 parameters: (1) content-related aspects, (2) context-related aspects, (3) aspects relevant for determining the training format, and (4) aspects relevant for consolidation and further development. Guiding questions with examples supports the application of the toolbox. Additionally, we introduced a how-to-use guidance to streamline the creation of new training programs, fostering knowledge transfer at the academia-practice interface, equipping public health researchers and practitioners with relevant skills for needs-based PHS research. By promoting collaborative training development across institutions, our approach encourages cross-institutional cooperation, enhances evidence utilization, and enables efficient resource allocation. This collaborative effort in developing training programs within local evidence ecosystems not only strengthens the scientific and practical impact but also lays a foundation for implementing complex public health measures effectively at the local level. [ABSTRACT FROM AUTHOR]

This 'cohort profile' aims to provide a description of the study design, methodology, and baseline characteristics of the participants in the Corona Behavioral Unit cohort. This cohort was established in response to the COVID-19 pandemic by the Dutch National Institute for Public Health and the Environment (RIVM) and the regional public health services. The aim was to investigate adherence of and support for COVID-19 prevention measures, psychosocial determinants of COVID-19 behaviors, well-being, COVID-19 vaccination, and media use. The cohort also examined specific motivations and beliefs, such as for vaccination, which were collected through either closed-ended items or open text responses. In April 2020, 89,943 participants aged 16 years and older were recruited from existing nation-wide panels. Between May 2020 and September 2022, 99,676 additional participants were recruited through online social media platforms and mailing lists of higher education organizations. Participants who consented were initially invited every three weeks (5 rounds), then every six weeks (13 rounds), and since the summer of 2022 every 12 weeks (3 rounds). To date, 66% of participants were female, 30% were 39 years and younger, and 54% completed two or more questionnaires, with an average of 9.2 (SD = 5.7) questionnaires. The Corona Behavioral Unit COVID-19 cohort has published detailed insights into longitudinal patterns of COVID-19 related behaviors, support of COVID-19 preventive measures, as well as peoples' mental wellbeing in relation to the stringency of these measures. The results have informed COVID-19 policy making and pandemic communication in the Netherlands throughout the COVID-19 pandemic. The cohort data will continuously be used to examine COVID-19 related outcomes for scientific analyses, as well as to inform future pandemic preparedness plans. [ABSTRACT FROM AUTHOR]

The success of personal non-pharmaceutical interventions as a public health strategy requires a high level of compliance from individuals in private social settings. Strategies to increase compliance in these hard-to-reach settings depend upon a comprehensive understanding of the patterns and predictors of protective social behavior. Social cognitive models of protective behavior emphasize the contribution of individual-level factors while social-ecological models emphasize the contribution of environmental factors. This study draws on 28 waves of survey data from the Understanding Coronavirus in America survey to measure patterns of adherence to two protective social behaviors–private social-distancing behavior and private masking behavior–during the COVID-19 pandemic and to assess the role individual and environmental factors play in predicting adherence. Results show that patterns of adherence fall into three categories marked by high, moderate, and low levels of adherence, with just under half of respondents exhibiting a high level of adherence. Health beliefs emerge as the single strongest predictor of adherence. All other environmental and individual-level predictors have relatively poor predictive power or primarily indirect effects. [ABSTRACT FROM AUTHOR]

The article focuses on measuring the fluctuations in countries' development as a result of the COVID-19 pandemic. The obtained measures make it possible to predict the extent of the impact of risks to public health on the economy, financial-budgetary, political-institutional development of states in the future, as well as the social determinants of public health. This assessment represents a new paradigm that makes it possible to effectively evaluate the manifestations of the consequences of COVID-19 and to identify the relevant determinants of the lack of resilience of the medical and social security systems to the coronavirus pandemic around the world. We picked the determinant of national development indicators of the 59 countries in order to measure the fluctuations in their economic development. In addition, we applied the binary response model for identifying the economic, financial-budgetary, and political-institutional development change with the happiness index of the countries being the dependent variable. The analysis of our empirical model made it possible for us to conclude that economic and financial-budgetary components have significantly increased the influence on well-being during the COVID-19 pandemic. In contrast, we observed the decrease in the impact of political and institutional indicators during the same period. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has had broad impacts on individuals, families and communities which will continue to require multidimensional responses from service providers, program developers, and policy makers. Objectives: The purpose of this study was to use Life Course theory to understand and imagine public health and policy responses to the multiple and varied impacts of the COVID-19 pandemic on different groups. Methods: "The Cost of COVID-19" was a research study carried out in Kingston, Frontenac, Lennox and Addington counties in South Eastern Ontario, Canada, between June and December 2020. Data included 210 micronarrative stories collected from community members, and 31 in-depth interviews with health and social service providers. Data were analyzed using directed content analysis to explore the fit between data and the constructs of Life Course theory. Results: Social pathways were significantly disrupted by changes to education and employment, as well as changes to roles which further altered anticipated pathways. Transitions were by and large missed, creating a sense of loss. While some respondents articulated positive turning points, most of the turning points reported were negative, including fundamental changes to relationships, family structure, education, and employment with lifelong implications. Participants' trajectories varied based on principles including when they occurred in their lifespan, the amount of agency they felt or did not feel over circumstances, where they lived (rural versus urban), what else was going on in their lives at the time the pandemic struck, how their lives were connected with others, as well as how the pandemic impacted the lives of those dear to them. An additional principle, that of Culture, was felt to be missing from the Life Course theory as currently outlined. Conclusions: A Life Course analysis may improve our understanding of the multidimensional long-term impacts of the COVID-19 pandemic and associated public health countermeasures. This analysis could help us to anticipate services that will require development, training, and funding to support the recovery of those who have been particularly affected. Resources needed will include education, mental health and job creation supports, as well as programs that support the development of individual and community agency. [ABSTRACT FROM AUTHOR]

Public health measures (PHMs) proactively and reactively reduce the spread of disease. While these measures target individual behaviour, they require broad adherence to be effective. Consequently, the World Health Organization issued a special appeal to young adults, a known non-adherent population, for increased adherence with COVID-19 guidelines. However, little is known about why these low-risk individuals do or do not adhere to PHMs. This study investigates why young adults in a low-risk setting adhered to PHMs implemented during the COVID-19 pandemic. A qualitative research approach was chosen to gain an in-depth understanding of participants' thoughts and experiences related to PHM adherence. Semi-structured interviews were conducted in April-May 2021 with 30 young adults living in Prince Edward Island (PEI), the province with the lowest COVID-19 case rate in Canada at that time. Thematic analysis was used to create a codebook based on the Theoretical Domains Framework, which was then inductively modified. The analysis identified eight themes that explained the adherence of young adults: (1) clear, purpose-driven adherence rationale, (2) developing trust in the local leadership, (3) adapting to novel measures, (4) manageable disruption, (5) adhering to reduce anxiety, (6) collective duty towards one's community, (7) moral culpability and (8) using caution rather than compliance. Together, these themes demonstrate that young adults adhered to PHMs because of their sense of connection to their community, public health leadership, and concerns over stigma. We further argue that clear guidelines and communication from public health officials during both periods of high and low COVID-19 cases facilitate adherence. These findings are important for mitigating future public health emergencies as they explain why young adults, an important segment of the population whose adherence is critical to the success of PHMs, follow PHMs. Further, these findings can inform public health officials and other stakeholders aiming to develop successful adherence strategies. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic has become a global major public health concern. Examining the meteorological risk factors and accurately predicting the incidence of the COVID-19 pandemic is an extremely important challenge. Therefore, in this study, we analyzed the relationship between meteorological factors and COVID-19 transmission in SAARC countries. We also compared the predictive accuracy of Autoregressive Integrated Moving Average (ARIMAX) and eXtreme Gradient Boosting (XGBoost) methods for precise modelling of COVID-19 incidence. We compiled a daily dataset including confirmed COVID-19 case counts, minimum and maximum temperature (°C), relative humidity (%), surface pressure (kPa), precipitation (mm/day) and maximum wind speed (m/s) from the onset of the disease to January 29, 2022, in each country. The data were divided into training and test sets. The training data were used to fit ARIMAX model for examining significant meteorological risk factors. All significant factors were then used as covariates in ARIMAX and XGBoost models to predict the COVID-19 confirmed cases. We found that maximum temperature had a positive impact on the COVID-19 transmission in Afghanistan (β = 11.91, 95% CI: 4.77, 19.05) and India (β = 0.18, 95% CI: 0.01, 0.35). Surface pressure had a positive influence in Pakistan (β = 25.77, 95% CI: 7.85, 43.69) and Sri Lanka (β = 411.63, 95% CI: 49.04, 774.23). We also found that the XGBoost model can help improve prediction of COVID-19 cases in SAARC countries over the ARIMAX model. The study findings will help the scientific communities and policymakers to establish a more accurate early warning system to control the spread of the pandemic. [ABSTRACT FROM AUTHOR]

Preventive and modeling approaches to address the COVID-19 pandemic have been primarily based on the age or occupation, and often disregard the importance of heterogeneity in population contact structure and individual connectivity. To address this gap, we developed models based on Erdős-Rényi and a power law degree distribution that first incorporate the role of heterogeneity and connectivity and then can be expanded to make assumptions about demographic characteristics. Results demonstrate that variations in the number of connections of individuals within a population modify the impact of public health interventions such as lockdown or vaccination approaches. We conclude that the most effective strategy will vary depending on the underlying contact structure of individuals within a population and on timing of the interventions. [ABSTRACT FROM AUTHOR]

Background: Confidence in the central UK Government has declined since the beginning of the COVID-19 pandemic, and while this may be linked to specific government actions to curb the spread of the virus, understanding is still incomplete. Examining public opinion is important, as research suggests that low confidence in government increases the extent of non-compliance with infection-dampening rules (for instance, social distancing); however, the detailed reasons for this association are still unclear. Methods: To understand public opinion on the central UK government during the first phase of the COVID-19 pandemic, we used structural topic modeling, a text mining technique, to extract themes from over 4000 free-text survey responses, collected between 14 October and 26 November 2020. Results: We identified eleven topics, among which were topics related to perceived government corruption and cronyism, complaints about inconsistency in rules and messaging, lack of clear planning, and lack of openness and transparency. Participants reported that elements of the government's approach had made it difficult to comply with guidelines (e.g., changing rules) or were having impacts on mental wellbeing (e.g., inability to plan for the future). Conclusions: Results suggested that consistent, transparent communication and messaging from the government is critical to improving compliance with measures to contain the virus, as well as protecting mental health during health emergencies. [ABSTRACT FROM AUTHOR]

A structural vector autoregressive model and spillover index analysis based on generalized prediction error variance decomposition were used to explore the impact of public health emergencies on the dry bulk shipping market and provide suggestions for addressing the impact of public health emergencies. Moreover, the risk fluctuation and spillover of the dry bulk shipping market during public health emergencies were analyzed to understand the ways in which public health emergencies impact the dry bulk shipping market and to quantify the impact intensity. In related studies, the influence of the international crude oil price index and dry bulk ship port berthing volume were also considered. The results show that considering the immediate impact, the increase of newly confirmed cases of COVID-19 has a significant impact on the dry bulk shipping market, which lasts for more than 3 weeks and is always a negative shock. Different types of public health emergencies have different effects on the dry bulk shipping segmented shipping market. Dry bulk shipping companies should fully understand the development of public health emergencies, make full use of risk aversion forecasting tools in financial markets and make deployments for different situations. [ABSTRACT FROM AUTHOR]

The global pandemic of COVID-19 revealed the dynamic heterogeneity in how individuals respond to infection risks, government orders, and community-specific social norms. Here we demonstrate how both individual observation and social learning are likely to shape behavioral, and therefore epidemiological, dynamics over time. Efforts to delay and reduce infections can compromise their own success, especially when disease risk and social learning interact within sub-populations, as when people observe others who are (a) infected and/or (b) socially distancing to protect themselves from infection. Simulating socially-learning agents who observe effects of a contagious virus, our modelling results are consistent with with 2020 data on mask-wearing in the U.S. and also concur with general observations of cohort induced differences in reactions to public health recommendations. We show how shifting reliance on types of learning affect the course of an outbreak, and could therefore factor into policy-based interventions incorporating age-based cohort differences in response behavior. [ABSTRACT FROM AUTHOR]

Non-Pharmaceutical Public Health Interventions (NPHIs) have been used by different countries to control the spread of the COVID-19. Despite available evidence regarding the effectiveness of NPHSs, there is still no consensus about how policymakers can trust these results. Studies on the effectiveness of NPHSs are single studies conducted in specific communities. Therefore, they cannot individually prove if these interventions have been effective in reducing the spread of the infection and its adverse health outcomes. In this systematic review, we aimed to examine the effects of NPHIs on the COVID-19 case growth rate, death growth rate, Intensive Care Unit (ICU) admission, and reproduction number in countries, where NPHIs have been implemented. We searched relevant electronic databases, including Medline (via PubMed), Scopus, CINAHL, Web of Science, etc. from late December 2019 to February 1, 2021. The key terms were primarily drawn from Medical Subject Heading (MeSh and Emtree), literature review, and opinions of experts. Peer-reviewed quasi-experimental studies were included in the review. The PROSPERO registration number is CRD42020186855. Interventions were NPHIs categorized as lockdown, stay-at-home orders, social distancing, and other interventions (mask-wearing, contact tracing, and school closure). We used PRISMA 2020 guidance for abstracting the data and used Cochrane Effective Practice and Organization of Practice (EPOC) Risk of Bias Tool for quality appraisal of the studies. Hartung-Knapp-Sidik-Jonkman random-effects model was performed. Main outcomes included COVID-19 case growth rate (percentage daily changes), COVID-19 mortality growth rate (percentage daily changes), COVID-19 ICU admission (percentage daily changes), and COVID-19 reproduction number changes. Our search strategies in major databases yielded 12,523 results, which decreased to 7,540 articles after eliminating duplicates. Finally, 35 articles qualified to be included in the systematic review among which 23 studies were included in the meta-analysis. Although studies were from both low-income and high-income countries, the majority of them were from the United States (13 studies) and China (five studies). Results of the meta-analysis showed that adoption of NPHIs has resulted in a 4.68% (95% CI, -6.94 to -2.78) decrease in daily case growth rates, 4.8% (95 CI, -8.34 to -1.40) decrease in daily death growth rates, 1.90 (95% CI, -2.23 to -1.58) decrease in the COVID-19 reproduction number, and 16.5% (95% CI, -19.68 to -13.32) decrease in COVID-19 daily ICU admission. A few studies showed that, early enforcement of lockdown, when the incidence rate is not high, contributed to a shorter duration of lockdown and a lower increase of the case growth rate in the post-lockdown era. The majority of NPHIs had positive effects on restraining the COVID-19 spread. With the problems that remain regarding universal access to vaccines and their effectiveness and considering the drastic impact of the nationwide lockdown and other harsh restrictions on the economy and people's life, such interventions should be mitigated by adopting other NPHIs such as mass mask-wearing, patient/suspected case isolation strategies, and contact tracing. Studies need to address the impact of NPHIs on the population's other health problems than COVID-19. [ABSTRACT FROM AUTHOR]

The COVID-19 global incidence rate among young adults (age 19–40) drastically increased since summer 2020, and young adults were often portrayed by popular media as the "main spreader" of the pandemic. However, young adults faced unique challenges during the pandemic due to working in high-risk, low-paying essential service occupations, as well as having higher levels of financial insecurity and mental burden. This qualitative study aims to examine the attitudes and perceptions of health orders of young adults to better inform public health messaging to reach this demographic and increase compliance to public health orders. A total of 50 young adults residing in British Columbia, Canada, were recruited to participate in focus group in groups of four to six. Focus group discussions were conducted via teleconferencing. Thematic analysis revealed four major themes: 1) risks of contracting the disease, 2) the perceived impact of COVID-19, 3) responsibility of institutions, 4) and effective public health messaging. Contrary to existing literature, our findings suggest young adults feel highly responsible for protecting themselves and others. They face a higher risk of depression and anxiety compared to other age groups, especially when they take on multiple social roles such as caregivers and parents. Our findings suggest young adults face confusion due to inconsistent messaging and are not reached due to the ineffectiveness of existing strategies. We recommend using evidence-based strategies proven to promote behaviour change to address the barriers identified by young adults through tailoring public health messages, specifically by using positive messaging, messaging that considers the context of the intended audiences, and utilizing digital platforms to facilitate two-way communication. [ABSTRACT FROM AUTHOR]

We examine how the earnings, time use, and subjective wellbeing of different social groups changed at different stages/waves of the pandemic in the United Kingdom (UK). We analyze longitudinal data from the latest UK Household Longitudinal Survey (UKHLS) COVID study and the earlier waves of the UKHLS to investigate within-individual changes in labor income, paid work time, housework time, childcare time, and distress level during the three lockdown periods and the easing period between them (from April 2020 to late March 2021). We find that as the pandemic developed, COVID-19 and its related lockdown measures in the UK had unequal and varying impacts on people's income, time use, and subjective well-being based on their gender, ethnicity, and educational level. In conclusion, the extent of the impacts of COVID-19 and COVID-induced measures as well as the speed at which these impacts developed, varied across social groups with different types of vulnerabilities. [ABSTRACT FROM AUTHOR]

We present a restricted infection rate inverse binomial-based approach to better predict COVID-19 cases after a family gathering. The traditional inverse binomial (IB) model is inappropriate to match the reality of COVID-19, because the collected data contradicts the model's requirement that variance should be larger than the expected value. Our version of an IB model is more appropriate, as it can accommodate all potential data scenarios in which the variance is smaller, equal, or larger than the mean. This is unlike the usual IB, which accommodates only the scenario in which the variance is more than the mean. Therefore, we propose a refined version of an IB model to be able to accommodate all potential data scenarios. The application of the approach is based on a restricted infectivity rate and methodology on COVID-19 data, which exhibit two clusters of infectivity. Cluster 1 has a smaller number of primary cases and exhibits larger variance than the expected cases with a negative correlation of 28%, implying that the number of secondary cases is lesser when the number of primary cases increases and vice versa. The traditional IB model is appropriate for Cluster 1. The probability of contracting COVID-19 is estimated to be 0.13 among the primary, but is 0.75 among the secondary in Cluster 1, with a wider gap. Cluster 2, with a larger number of primary cases, exhibits smaller variance than the expected cases with a correlation of 79%, implying that the number of primary and secondary cases do increase or decrease together. Cluster 2 disqualifies the traditional IB model and requires its refined version. The probability of contracting COVID-19 is estimated to be 0.74 among the primary, but is 0.72 among the secondary in Cluster 2, with a narrower gap. The advantages of the proposed approach include the model's ability to estimate the community's health system memory, as future policies might reduce COVID's spread. In our approach, the current hazard level to be infected with COVID-19 and the odds of not contracting COVID-19 among the primary in comparison to the secondary groups are estimable and interpretable. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, governments globally had to impose severe contact restriction measures and social mobility limitations in order to limit the exposure of the population to COVID-19. These public health policy decisions were informed by statistical models for infection rates in national populations. In this work, we are interested in modelling the temporal evolution of national-level infection counts for the United Kingdom (UK—Wales, England, Scotland), Germany (GM), Italy (IT), Spain (SP), Japan (JP), Australia (AU) and the United States (US). We model the national-level infection counts for the period January 2020 to January 2021, thus covering both the pre- and post-vaccine roll-out periods, in order to better understand the most reliable model structure for the COVID-19 epidemic growth curve. We achieve this by exploring a variety of stochastic population growth models and comparing their calibration, with respect to in-sample fitting and out-of-sample forecasting, both with and without exposure adjustment, to the most widely used and reported growth model, the Gompertz population model, often referred to in the public health policy discourse during the COVID-19 pandemic. Model risk as we explore it in this work manifests in the inability to adequately capture the behaviour of the disease progression growth rate curve. Therefore, our concept of model risk is formed relative to the standard reference Gompertz model used by decision-makers, and then we can characterise model risk mathematically as having two components: the dispersion of the observation distribution, and the structure of the intensity function over time for cumulative counts of new infections daily (i.e. the force of infection) attributed directly to the COVID-19 pandemic. We also explore how to incorporate in these population models the effect that governmental interventions have had on the number of infected cases. This is achieved through the development of an exposure adjustment to the force of infection comprised of a purpose-built sentiment index, which we construct from various authoritative public health news reporting. The news reporting media we employed were the New York Times, the Guardian, the Telegraph, Reuters global blog, as well as national and international health authorities: the European Centre for Disease Prevention and Control, the United Nations Economic Commission for Europe, the United States Centres for Disease Control and Prevention, and the World Health Organisation. We find that exposure adjustments that incorporate sentiment are better able to calibrate to early stages of infection spread in all countries under study. [ABSTRACT FROM AUTHOR]

Blaine County, Idaho, a rural area with a renowned resort, experienced a COVID-19 outbreak early in the pandemic. We undertook an epidemiologic investigation to describe the outbreak and guide public health action. Confirmed cases of COVID-19 were identified from reports of SARS-CoV-2-positive laboratory test results to South Central Public Health District. Information on symptoms, hospitalization, recent travel, healthcare worker status, and close contacts was obtained by medical record review and patient interviews. Viral sequence analysis was conducted on a subset of available specimens. During March 13–April 10, 2020, a total of 451 COVID-19 cases among Blaine County residents (1,959 cases per 100,000 population) were reported, with earliest illness onset March 1. The median patient age was 51 years (interquartile range [IQR]: 37–63), 52 (11.5%) were hospitalized, and 5 (1.1%) died. The median duration between specimen collection and a positive laboratory result was 9 days (IQR: 4–10). Forty-four (9.8%) patients reported recent travel and an additional 37 cases occurred in out-of-state residents. Healthcare workers comprised 56 (12.4%) cases; 33 of whom worked at the only hospital in the county, leading to a 15-day disruption of hospital services. Among 562 close contacts monitored by public health authorities, laboratory-confirmed COVID-19 or compatible symptoms were identified in 51 (9.1%). Sequencing results from 34 specimens supported epidemiologic findings indicating travel as a source of SARS-CoV-2, and identified multiple lineages among hospital workers. Community mitigation strategies included school and resort closure, stay-at-home orders, and restrictions on incoming travelers. COVID-19 outbreaks in rural communities can disrupt health services. Lack of local laboratory capacity led to long turnaround times for COVID-19 test results. Rural communities frequented by tourists face unique challenges during the COVID-19 pandemic. Implementing restrictions on incoming travelers and other mitigation strategies helped reduce COVID-19 transmission early in the pandemic. [ABSTRACT FROM AUTHOR]

Objective: Emergency Department (ED) attendances with chest pain reduced during the COVID-19 lockdown. We performed a service evaluation project in NHS Lothian to explore how and why the COVID-19 pandemic and public health advice had affected chest pain presentations and help-seeking behaviour at an individual patient level using a qualitative interview approach. Methods: We carried out 28 semi-structured telephone interviews with a convenience sample of patients who presented with chest pain during lockdown and in patients with known coronary heart disease under the outpatient care of a cardiologist in April and May 2020. Interviews were audio recorded and voice files listened to while making detailed notes. Salient themes and issues were documented as verbatim extracts. Interviews were analysed thematically. Results: Patient interviews revealed three main themes. 1) pandemic help-seeking behaviour; describing how participants made the decision to seek professional healthcare assessment. 2) COVID-19 exposure concerns; describing how the subthemes of perceived vulnerability, wishing to protect others and adding pressure to the health service shaped their decision making for an episode of acute chest pain. 3) hospital experience; describing the difference between the imagined and actual experience in hospital. Conclusions: Qualitative interviews revealed how the pandemic shaped help-seeking practices, how patients interpreted their personal vulnerability to the virus, and described patient experience of attending hospital for assessment during this time. As patient numbers presenting to hospital appeared to mirror public health messaging, dynamic monitoring of this messaging should evaluate public response to healthcare campaigns to ensure the net impact on health, pandemic and non-pandemic related, is optimised. [ABSTRACT FROM AUTHOR]

Background: In dealing with community spread of COVID-19, two active interventions have been attempted or advocated—containment, and mitigation. Given the extensive impact of COVID-19 globally, there is international interest to learn from best practices that have been shown to work in controlling community spread to inform future outbreaks. This study explores the trajectory of COVID-19 infection in Singapore had the government intervention not focused on containment, but rather on mitigation. In addition, we estimate the actual COVID-19 infection cases in Singapore, given that confirmed cases are publicly available. Methods and findings: We developed a COVID-19 infection model, which is a modified SIR model that differentiate between detected (diagnosed) and undetected (undiagnosed) individuals and segments total population into seven health states: susceptible (S), infected asymptomatic undiagnosed (A), infected asymptomatic diagnosed (I), infected symptomatic undiagnosed (U), infected symptomatic diagnosed (E), recovered (R), and dead (D). To account for the infection stages of the asymptomatic and symptomatic infected individuals, the asymptomatic infected individuals were further disaggregated into three infection stages: (a) latent (b) infectious and (c) non-infectious; while the symptomatic infected were disaggregated into two stages: (a) infectious and (b) non-infectious. The simulation result shows that by the end of the current epidemic cycle without considering the possibility of a second wave, under the containment intervention implemented in Singapore, the confirmed number of Singaporeans infected with COVID-19 (diagnosed asymptomatic and symptomatic cases) is projected to be 52,053 (with 95% confidence range of 49,370–54,735) representing 0.87% (0.83%-0.92%) of the total population; while the actual number of Singaporeans infected with COVID-19 (diagnosed and undiagnosed asymptomatic and symptomatic infected cases) is projected to be 86,041 (81,097–90,986), which is 1.65 times the confirmed cases and represents 1.45% (1.36%-1.53%) of the total population. A peak in infected cases is projected to have occurred on around day 125 (27/05/2020) for the confirmed infected cases and around day 115 (17/05/2020) for the actual infected cases. The number of deaths is estimated to be 37 (34–39) among those infected with COVID-19 by the end of the epidemic cycle; consequently, the perceived case fatality rate is projected to be 0.07%, while the actual case fatality rate is estimated to be 0.043%. Importantly, our simulation model results suggest that there about 65% more COVID-19 infection cases in Singapore that have not been captured in the official reported numbers which could be uncovered via a serological study. Compared to the containment intervention, a mitigation intervention would have resulted in early peak infection, and increase both the cumulative confirmed and actual infection cases and deaths. Conclusion: Early public health measures in the context of targeted, aggressive containment including swift and effective contact tracing and quarantine, was likely responsible for suppressing the number of COVID-19 infections in Singapore. [ABSTRACT FROM AUTHOR]

Introduction: With over 500 000 infections and nearly 12 000 deaths, South Africa (SA) is the African epicenter of the current Coronavirus (COVID-19) pandemic. SA has implemented a 5-stage Risk-Adjusted Strategy which includes a phased national lockdown, requiring social distancing, frequent hand washing and wearing face masks. Strict adherence to this strategy is crucial to reducing COVID-19 transmission, flattening the curve, and preventing resurgence. As part of the 22-country International Citizens Project COVID-19 (ICPcovid), this study aimed to describe the SA adherence to the Risk-Adjusted Strategy and identify determinants of adherence. Method: During 24 April-15 May 2020, people were electronically invited, through social media platforms and a text blast, to complete an online survey, accessible via www.icpcovid.com. The survey investigated COVID-19 testing and preventative adherence measures, then used logistic regression analysis to identify predictors of adherence. Results: There were 951 participants, with 731(76.9%) 25 to 54 years. Most (672;70.7%) were female, and 705(74.1%) had a university degree. Since the epidemic started, 529(55.6%) and 436(45.9%) participants stated they were eating healthier and taking more vitamins, respectively. Only 82(8.6%) had been COVID-19 tested, and 1(1.2%) tested positive. In public, 905(95.2%) socially distanced, however 99(10.4%) participants had recently attended meetings with over ten people. Regular hand washing was practiced by 907(95.4%) participants, 774(81.4%) wore face masks and 854(89.8%) stayed home when they experienced flu-like symptoms. The odds of adhering to the guidelines were lower among men versus women (AOR 0.72, 95% confidence interval [CI] = 0.528, 0.971) and those who had flu-like symptoms (AOR 0.42, 95% CI = 0.277, 0.628). In contrast, increased odds were reported for those who reported increased vitamin intake (AOR 1.37, 95% CI = 1.044,1.798), and were either cohabiting or married (AOR 1.39, 95% CI = 1.042,1.847). Conclusion: Despite high reported adherence, face mask use and symptomatic individuals not self-isolating, were areas for improvement. However, these factors cannot solely account for SA's increasing COVID-19 cases. Larger general population studies are needed to identify other adherence predictors for a strengthened SA COVID-19 response. While the government must continue to educate the entire population on preventative measures, provide personal protective equipment and stress the importance of adherence, there also needs to be implementation of prioritised prevention strategies for men and single individuals to address their demonstrated lower adherence. [ABSTRACT FROM AUTHOR]

A novel infectious respiratory disease was recognized in Wuhan (Hubei Province, China) in December 2019. In February 2020, the disease was named "coronavirus disease 2019" (COVID-19). COVID-19 became a pandemic in March 2020, and, since then, different countries have implemented a broad spectrum of policies. Thailand is considered to be among the top countries in handling its first wave of the outbreak—12 January to 31 July 2020. Here, we illustrate how Thailand tackled the COVID-19 outbreak, particularly the effects of public health interventions on the epidemiological spread. This study shows how the available data from the outbreak can be analyzed and visualized to quantify the severity of the outbreak, the effectiveness of the interventions, and the level of risk of allowed activities during an easing of a "lockdown." This study shows how a well-organized governmental apparatus can overcome the havoc caused by a pandemic. [ABSTRACT FROM AUTHOR]

It is urgent to understand how to effectively communicate public health messages during the COVID-19 pandemic. Previous work has focused on how to formulate messages in terms of style and content, rather than on who should send them. In particular, little is known about the impact of spokesperson selection on message propagation during times of crisis. We report on the effectiveness of different public figures at promoting social distancing among 12,194 respondents from six countries that were severely affected by the COVID-19 pandemic at the time of data collection. Across countries and demographic strata, immunology expert Dr. Anthony Fauci achieved the highest level of respondents' willingness to reshare a call to social distancing, followed by a government spokesperson. Celebrity spokespersons were least effective. The likelihood of message resharing increased with age and when respondents expressed positive sentiments towards the spokesperson. These results contribute to the development of evidence-based knowledge regarding the effectiveness of prominent official and non-official public figures in communicating public health messaging in times of crisis. Our findings serve as a reminder that scientific experts and governments should not underestimate their power to inform and persuade in times of crisis and underscore the crucial importance of selecting the most effective messenger in propagating messages of lifesaving information during a pandemic. [ABSTRACT FROM AUTHOR]

In the frontline of the pandemic stand healthcare workers and public service providers, occupations which have proven to be associated with increased mental health problems during pandemic crises. This cross-sectional, survey-based study collected data from 1773 healthcare workers and public service providers throughout Norway between March 31, 2020 and April 7, 2020, which encompasses a timeframe where all non-pharmacological interventions (NPIs) were held constant. Post-traumatic stress disorder (PTSD), anxiety and depression were assessed by the Norwegian version of the PTSD checklist (PCL-5), General Anxiety Disorder –7, and Patient Health Questionnaire-9 (PHQ-9), respectively. Health anxiety and specific predictors were assessed with specific items. Multiple regression analysis was used for predictor analysis. A total of 28.9% of the sample had clinical or subclinical symptoms of PTSD, and 21.2% and 20.5% were above the established cut-offs for anxiety and depression. Those working directly in contrast to indirectly with COVID-19 patients had significantly higher PTSD symptoms. Worries about job and economy, negative metacognitions, burnout, health anxiety and emotional support were significantly associated with PTSD symptoms, after controlling for demographic variables and psychological symptoms. Health workers and public service providers are experiencing high levels of PTSD symptoms, anxiety and depression during the COVID-19 pandemic. Health workers working directly with COVID-19 patients have significantly higher levels of PTSD symptoms and depression compared to those working indirectly. Appropriate action to monitor and reduce PTSD, anxiety, and depression among these groups of individuals working in the frontline of pandemic with crucial societal roles should be taken immediately. [ABSTRACT FROM AUTHOR]