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Despite the public health value of immunizations, vaccine hesitancy is a widespread phenomenon and received special attention during the global COVID-19 pandemic. The Vaccination Attitudes Examination (VAX) Scale aims to identify anti-vaccination attitudes for understanding vaccine hesitancy. The present study is the validation of the German version of the VAX scale in pre-/mid-pandemic samples. All individuals completed an online-survey assessing prior and expected future vaccination behaviors, further constructs associated with vaccine hesitancy, as well as anti-vaccination attitudes using the translated VAX scale among others. In a first study, 297 individuals were surveyed before the COVID-19 pandemic. A second study included 260 individuals recruited during the COVID-19 pandemic. For validation, two confirmatory factor analyses have been conducted. Reliability measures (internal consistency, test–retest-correlation) were determined. The four subscales were confirmed by Confirmation Factor Analysis with a very good to excellent fit. The subscales showed good to excellent reliability and convergent validity determinants. Average VAX values significantly distinguished between individuals who had previously received or refused immunization and predicted expected vaccination behavior. The German translation of the VAX scale is effective in identifying anti-vaccination attitudes and can be used for further research on anti-vaccination attitudes and vaccine hesitancy. [ABSTRACT FROM AUTHOR]

Vaccine hesitancy is an inevitable risk for societies as it contributes to outbreaks of diseases. Prior research suggests that vaccination decisions of individuals tend to spread within social networks, resulting in a tendency to vaccination homophily. The clustering of individuals resistant to vaccination can substantially make the threshold necessary to achieve herd immunity harder to reach. In this study, we examined the extent of vaccination homophily among social contacts and its association with vaccine uptake during the COVID-19 pandemic in Hungary using a contact diary approach in two cross-sectional surveys. The results indicate strong clustering among both vaccinated and unvaccinated groups. The most powerful predictor of vaccine uptake was the perceived vaccination rate within the egos' social contact network. Vaccination homophily and the role of the interpersonal contact network in vaccine uptake were particularly pronounced in the networks of close relationships, including family, kinship, and strong social ties of the ego. Our findings have important implications for understanding COVID-19 spread dynamics by showing that the strong clustering of unvaccinated individuals posed a great risk in preventing the spread of the disease. [ABSTRACT FROM AUTHOR]

Trust in vaccines and in the institutions responsible for their management is a key asset in the global response to the COVID-19 pandemic. By means of a structured multi-scales survey based on the socio-cognitive model of trust, this study investigates the interplay of institutional trust, confidence in COVID-19 vaccines, information habits, personal motivations, and background beliefs on the pandemic in determining willingness to vaccinate in a sample of Italian respondents (N = 4096). We observe substantial trust in public institutions and a strong vaccination intention. Theory-driven structural equation analysis revealed what factors act as important predictors of willingness to vaccinate: trust in vaccine manufacturers (which in turn is supported by trust in regulators), collectivist goals, self-perceived knowledgeability, reliance on traditional media for information gathering, and trust in institutional and scientific sources. In contrast, vaccine hesitancy, while confined to a minority, is more prominent in less educated and less affluent respondents. These findings can inform institutional decisions on vaccine communication and vaccination campaigns. [ABSTRACT FROM AUTHOR]

Many countries have secured larger quantities of COVID-19 vaccines than their population is willing to take. The abundance and the large variety of vaccines created not only an unprecedented intensity of vaccine related public discourse, but also a historical moment to understand vaccine hesitancy better. Yet, the heterogeneity of hesitancy by vaccine types has been neglected in the existing literature so far. We address this problem by analysing the acceptance and the assessment of five vaccine types. We use information collected with a nationally representative survey at the end of the third wave of the COVID-19 pandemic in Hungary. During the vaccination campaign, individuals could reject the assigned vaccine to wait for a more preferred alternative that enables us to quantify revealed preferences across vaccine types. We find that hesitancy is heterogenous by vaccine types and is driven by individuals' trusted source of information. Believers of conspiracy theories are more likely to evaluate the mRNA vaccines (Pfizer and Moderna) unacceptable. Those who follow the advice of politicians are more likely to evaluate vector-based (AstraZeneca and Sputnik) or whole-virus vaccines (Sinopharm) acceptable. We argue that the greater selection of available vaccine types and the free choice of the individual are desirable conditions to increase the vaccination rate in societies. [ABSTRACT FROM AUTHOR]

Online misinformation is believed to have contributed to vaccine hesitancy during the Covid-19 pandemic, highlighting concerns about social media's destabilizing role in public life. Previous research identified a link between political conservatism and sharing misinformation; however, it is not clear how partisanship affects how much misinformation people see online. As a result, we do not know whether partisanship drives exposure to misinformation or people selectively share misinformation despite being exposed to factual content. To address this question, we study Twitter discussions about the Covid-19 pandemic, classifying users along the political and factual spectrum based on the information sources they share. In addition, we quantify exposure through retweet interactions. We uncover partisan asymmetries in the exposure to misinformation: conservatives are more likely to see and share misinformation, and while users' connections expose them to ideologically congruent content, the interactions between political and factual dimensions create conditions for the highly polarized users—hardline conservatives and liberals—to amplify misinformation. Overall, however, misinformation receives less attention than factual content and political moderates, the bulk of users in our sample, help filter out misinformation. Identifying the extent of polarization and how political ideology exacerbates misinformation can help public health experts and policy makers improve their messaging. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 vaccines are useful tools to combat the Coronavirus Disease 2019 (COVID-19) pandemic, but vaccine reluctance threatens these vaccines' effectiveness. To address COVID-19 vaccine reluctance and ensure equitable distribution, understanding the extent of and factors associated with vaccine acceptance and uptake is critical. We report the results of a large nationwide study in the US conducted December 2020-May 2021 of 36,711 users from COVID-19-focused smartphone-based app How We Feel on their willingness to receive a COVID-19 vaccine. We identified sociodemographic and behavioral factors that were associated with COVID-19 vaccine acceptance and uptake, and we found several vulnerable groups at increased risk of COVID-19 burden, morbidity, and mortality were more likely to be reluctant to accept a vaccine and had lower rates of vaccination. Our findings highlight specific populations in which targeted efforts to develop education and outreach programs are needed to overcome poor vaccine acceptance and improve equitable access, diversity, and inclusion in the national response to COVID-19. [ABSTRACT FROM AUTHOR]

Governments worldwide are implementing mass vaccination programs in an effort to end the novel coronavirus (COVID-19) pandemic. Here, we evaluated the effectiveness of the COVID-19 vaccination program in its early stage and predicted the path to herd immunity in the U.S. By early March 2021, we estimated that vaccination reduced the total number of new cases by 4.4 million (from 33.0 to 28.6 million), prevented approximately 0.12 million hospitalizations (from 0.89 to 0.78 million), and decreased the population infection rate by 1.34 percentage points (from 10.10 to 8.76%). We built a Susceptible-Infected-Recovered (SIR) model with vaccination to predict herd immunity, following the trends from the early-stage vaccination program. Herd immunity could be achieved earlier with a faster vaccination pace, lower vaccine hesitancy, and higher vaccine effectiveness. The Delta variant has substantially postponed the predicted herd immunity date, through a combination of reduced vaccine effectiveness, lowered recovery rate, and increased infection and death rates. These findings improve our understanding of the COVID-19 vaccination and can inform future public health policies. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic struck the world unguarded, some places outperformed others in COVID-19 containment. This longitudinal study considered a comparative evaluation of COVID-19 containment across 50 distinctly governed regions between March 2020 and November 2021. Our analysis distinguishes between a pre-vaccine phase (March–November 2020) and a vaccinating phase (December 2020–November 2021). In the first phase, we develop an indicator, termed lockdown efficiency (LE), to estimate the efficacy of measures against monthly case numbers. Nine other indicators were considered, including vaccine-related indicators in the second phase. Linear mixed models are used to explore the relationship between each government policy & hygiene education (GP&HE) indicator and each vital health & socioeconomic (VH&SE) measure. Our ranking shows that surveyed countries in Oceania and Asian outperformed countries in other regions for pandemic containment prior to vaccine development. Their success appears to be associated with non-pharmaceutical interventions, acting early, and adjusting policies as needed. After vaccines have been distributed, maintaining non-pharmacological intervention is the best way to achieve protection from variant viral strains, breakthrough infections, waning vaccine efficacy, and vaccine hesitancy limiting of herd immunity. The findings of the study provide insights into the effectiveness of emerging infectious disease containment policies worldwide. [ABSTRACT FROM AUTHOR]

Research on Guillain-Barré syndrome (GBS) as a neurological adverse effect of vaccines on a global scale is scarce, highlighting the need for further investigation to evaluate its long-term impact and associated risk factors comprehensively. Hence, this study aims to assess the global burden of vaccine-associated GBS and its associated vaccines. This study utilized data from VigiBase, the World Health Organization global database of adverse event reports of medicines and vaccines, encompassing the period from 1967 to 2023 (total reports, n = 131,255,418) to investigate vaccine-associated GBS. Reported odds ratios (ROR) and information components (IC) were analyzed to assess the association between 19 vaccines and the occurrence of vaccine-associated GBS over 170 countries. We identified 15,377 (8072 males [52.49%]) reports of vaccine-associated GBS among 22,616 reports of all drugs-cause GBS from 1978 to 2023. Cumulative reports of vaccine-associated GBS have been increasing steadily over time, with a notable surge observed since the commencement of COVID-19 vaccines administration in 2020. Most vaccines showed significant associations with GBS such as Ad5-vectored COVID-19 vaccines (ROR, 14.88; IC, 3.66), COVID-19 mRNA vaccines (ROR, 9.66; IC, 2.84), and inactivated whole-virus COVID-19 vaccines (ROR, 3,29; IC 1.69). Influenza vaccines showed the highest association (ROR, 77.91; IC 5.98). Regarding age-and sex-specific risks, the association remained similar regardless of sex, with an increased association observed with advancing age. The mean time to onset was 5.5 days. Amid the COVID-19 pandemic, the reports of GBS surged in response to widespread COVID-19 vaccination. Nonetheless, COVID-19 vaccines exhibited the lowest association compared to other vaccines. Vigilance for at least one-week post-vaccination is crucial, particularly for older adults. Further research is warranted to elucidate the underlying mechanisms linking vaccines and GBS. [ABSTRACT FROM AUTHOR]

The effects of the COVID-19 pandemic on comprehensive maternal deaths in Brazil have not been fully explored. Using publicly available data from the Brazilian Mortality Information (SIM) and Information System on Live Births (SINASC) databases, we used two complementary forecasting models to predict estimates of maternal mortality ratios using maternal deaths (MMR) and comprehensive maternal deaths (MMRc) in the years 2020 and 2021 based on data from 2008 to 2019. We calculated national and regional standardized mortality ratio estimates for maternal deaths (SMR) and comprehensive maternal deaths (SMRc) for 2020 and 2021. The observed MMRc in 2021 was more than double the predicted MMRc based on the Holt-Winters and autoregressive integrated moving average models (127.12 versus 60.89 and 59.12 per 100,000 live births, respectively). We found persisting sub-national variation in comprehensive maternal mortality: SMRc ranged from 1.74 (95% confidence interval [CI] 1.64, 1.86) in the Northeast to 2.70 (95% CI 2.45, 2.96) in the South in 2021. The observed national estimates for comprehensive maternal deaths in 2021 were the highest in Brazil in the past three decades. Increased resources for prenatal care, maternal health, and postpartum care may be needed to reverse the national trend in comprehensive maternal deaths. [ABSTRACT FROM AUTHOR]

Combining the frameworks of fundamental causes theory and diffusion of innovation, scholars had anticipated a delayed COVID-19 vaccination uptake for people in lower socioeconomic position depending on the socioeconomic context. We qualify these propositions and analyze educational differences in COVID-19 vaccination status over the first ten months of Germany's vaccination campaign in 2021. Data from the study "Corona Monitoring Nationwide" (RKI-SOEP-2), collected between November 2021 and February 2022, is linked with district-level data of the German Index of Socioeconomic Deprivation (GISD). We estimated the proportion of people with at least one vaccination dose stratified by educational groups and within different settings of regional socioeconomic deprivation at three time points. Logistic multilevel regression models were applied to adjust for multiple covariates and to test cross-level-interactions between educational levels and levels of area-level socioeconomic deprivation. Vaccination rates were lower among respondents with lower education. With increasing area-level socioeconomic deprivation, educational differences were larger due to particularly low vaccination rates in groups with low education levels. The analysis of vaccination timing reveals that educational gaps and gaps by area-level socioeconomic deprivation had appeared early in the vaccination campaign and did not close completely before the 4th wave of COVID-19 infections [ABSTRACT FROM AUTHOR]

This study aims to quantify the effectiveness of lockdown as a non-pharmacological solution for managing the COVID-19 pandemic. Daily COVID-19 death counts were collected for four states: California, Georgia, New Jersey, and South Carolina. The effectiveness of the lockdown was studied and the number of people saved during 7 days was evaluated. Five neural network models (MLP, FFNN, CFNN, ENN, and NARX) were implemented, and the results indicate that FFNN is the best prediction model. Based on this model, the total number of survivors over a 7-day period is 211, 270, 989, and 60 in California, Georgia, New Jersey, and South Carolina, respectively. The coefficients and weights of the FFNN for each state differ due to various factors, including socio-demographic conditions and the behavior of citizens towards lockdown laws. New Jersey and South Carolina have the most lockdowns and the least. [ABSTRACT FROM AUTHOR]

Post COVID-19 Condition (PCC) is a clinical syndrome following COVID-19 disease. PCC symptoms in adults entail significant productivity loss and reduced quality of life. This study aimed at estimating the epidemiological and economic burden of PCC among the working-age population of Italy and the US. This ecological analysis was conducted on data from January 2020 to April 2023, regarding population aged 18–64. PCC incidence for the US was retrieved from publicly reported estimates, while for Italy it was estimated from COVID-19 cases. Prevalence of factors associated with PCC and parameters to calculate temporary productivity losses (TPL) were retrieved. An estimated incidence rate ratio (eIRR) of PCC incidence in Italy and the US was calculated. TPL for reduced earnings and total quality-adjusted life years (QALYs) lost were also estimated. The ecological eIRR Italy/US was 0.842 [95%CI 0.672–1.015], suggesting that, holding COVID-19 cases constant, 15.8% fewer PCC cases have occurred in Italy compared to the US. Overall PCC cases were found to be 12.0 [95%CI 9.9–14.1] million in the US, with 1.9 [95%CI 1.6–2.3] million QALYs lost, and 2.4 [95%CI 1.8–3.0] million in Italy, with 0.4 [95%CI 0.3–0.5] million QALYs lost. Up to April 2023, the TPL was estimated to be Int$7.5 [95%CI 5.8–10.1] billion in Italy and $41.5 [95%CI 34.3–48.7] billion in the US. PCC has had a significant epidemiological and economic impact on the working-age population. The findings from this study may be of use for health planning and policy regarding PCC in working-age adults. [ABSTRACT FROM AUTHOR]

Today, advertising science is a tool that helps advertisers to design their advertising to meet the needs of the audience. In this regard, knowing and understanding the audience is one of the most important points that advertisers should pay attention to before advertising in order to better attract the audience. This study has been done with the aim of billboards and infographics analysis related to promoting preventive behaviors and vaccination against the Coronavirus disease pandemic and investigating the opinion of the general adult population of Iran. The method used in this research is the qualitative method. In this research, according to the type of data and research goals, Kress and Van Leeuwen's discourse theory method has been used. The sample size includes 36 advertising billboards and infographics. Data collection has been done through searching the sites and websites of health networks and medical education centers in Iran, taking pictures of infographics and billboards in public places, and also receiving archive files of pictures from the public relations of health networks and medical services. The data was collected from February 19, 2020 to December 30, 2022 (the time frame of the pandemic and public vaccination program in Iran). Then, an online survey about promoting preventive behaviors and taking vaccination against the Coronavirus disease pandemic was designed in SurveyMonkey and its link was provided to the audience through virtual networks and other platforms. The assessment of validity involved experts in infection control and linguistics. The reliability of the measurement, determined through the Cronbach's alpha internal consistency coefficient, yielded a coefficient of 0.968. In this study, data analysis was conducted using IBM SPSS Statistics software, version 15.0 (IBM Corp., Armonk, NY, USA). Finally, users' opinions about of billboards and infographics were analyzed using descriptive statistics. The results of component analysis and surveys show that visual components such as «The staring look at the spectator (Demand)», «Head-on Shot (inclusion)», «Down Shot (Creating a sense of participation for the represented person)», «Close-up (intimate/individual relationship)», «Level Shot (equality)» and «High-Angle Shot (Presenting power)» in medical advertising has had a great impact in arousing public opinion to create a positive attitude towards preventive measures and vaccination during the Coronavirus disease epidemic. The results of this research show that in visual communication, visual components play a significant role in creating and maintaining target ideologies. Also, advertising in the field of preventive measures in medical sciences requires certain rules that determine people's culture and the main foundation of their attitude and thinking. Therefore, it is necessary to know such knowledge and learn it by the medical staff to deal with critical situations. [ABSTRACT FROM AUTHOR]

Teachers in Japanese schools employ alphabetical surname lists that call students sooner, with surnames appearing early on these lists. We conducted Internet surveys nearly every month from March 2020 to September 2022 with the same participants, wherein we asked participants where the alphabetical columns of their childhood and adult surnames were located. We aimed to identify how surname order is important for the formation of noncognitive skills. During the data collection period, the COVID-19 vaccines became available; Japanese people could receive their third dose starting in December 2021. The 19th wave of the survey was conducted in January 2022. Therefore, to examine how a surname's alphabetical order could influence intention to revaccinate, we used a subsample of data from December 2021 to September 2022. The major findings were as follows. Women with early surnames had an approximately 4% stronger likelihood of having such intentions than men with early surnames. Early name order was more strongly correlated with revaccination intention among women than among men. The surname effect for women was larger when a mixed-gender list was used compared with when it was not used. This effect was only observed for childhood surnames and not for adult surnames. [ABSTRACT FROM AUTHOR]

Many countries worldwide had difficulties reaching a sufficiently high vaccination uptake during the COVID-19 pandemic. Given this context, we collected data from a panel of 30,000 individuals, which were representative of the population of Romania (a country in Eastern Europe with a low 42.6% vaccination rate) to determine whether people are more likely to be connected to peers displaying similar opinions about COVID-19 vaccination. We extracted 443 personal networks, amounting to 4430 alters. We estimated multilevel logistic regression models with random-ego-level intercepts to predict individual opinions about COVID-19 vaccination. Our evidence indicates positive opinions about the COVID-19 vaccination cluster. Namely, the likelihood of having a positive opinion about COVID-19 vaccination increases when peers have, on average, a more positive attitude than the rest of the nodes in the network (OR 1.31, p < 0.001). We also found that individuals with higher education and age are more likely to hold a positive opinion about COVID-19 vaccination. With the given empirical data, our study cannot reveal whether this assortative mixing of opinions is due to social influence or social selection. However, it may nevertheless have implications for public health interventions, especially in countries that strive to reach higher uptake rates. Understanding opinions about vaccination can act as an early warning system for potential outbreaks, inform predictions about vaccination uptake, or help supply chain management for vaccine distribution. [ABSTRACT FROM AUTHOR]

Previous studies have reported significant decreases in the incidence of mental health problems following SARS-CoV-2 vaccination. However, less relevant studies are published in China. We conducted a cross-sectional study involving Chinese adults aged 18–75 years with no known psychiatric diseases. The study used data from mental health of SARS-CoV-2 vaccinated and unvaccinated participants from May 2020 to July 2021.Three standardized scales, namely, the Generalized Anxiety Disorder-7 (GAD-7) for anxious symptoms, Patient Health Questionnaire-9 (PHQ-9) for depressive symptoms and Athens Insomnia Score-8 (AIS-8) for insomnia symptoms, as well as basic demographic questions were used. The hierarchical regression method was used for multivariate logistic regression analysis to explore the effects of SARS-CoV-2 vaccination on anxious, insomnia, and depressive symptoms. The results confirmed first that vaccinated participants experienced significantly lower anxious, insomnia, and depressive symptoms scores (P < 0.001) compared with unvaccinated participants. Second that vaccinated participants had a lower prevalence of anxious, insomnia, and depressive symptoms (P < 0.001). Third, after adjusting for potential confounders, we still observed a good correlation between vaccination and a reduced risk of anxious, insomnia, and depressive symptoms. The current study showed that SARS-CoV-2 vaccination may be helpful in improving anxious, insomnia, and depressive symptoms. [ABSTRACT FROM AUTHOR]

This study assessed the association between COVID-19 vaccines, SARS-CoV-2 infection and the risk of thrombocytopenia and venous thromboembolism (VTE). This self-controlled case series study used hospital records between 1st February 2021 and 28th February 2022 linked to the national immunisation registry and COVID-19 surveillance data in Malaysia. Conditional Poisson regression was used to estimate incidence rate ratios (IRR) of events in the risk period (day 1–21 post-exposure) relative to control period with the corresponding 95% confidence interval (CI) adjusted for calendar period. We found no significant increased risk of thrombocytopenia in 1–21 days following BNT162b2, CoronaVac and ChAdOx1 vaccines while the risk was increased following SARS-CoV-2 infection (IRR 15.52, 95% CI 13.38–18.00). Similarly, vaccination with BNT162b2, CoronaVac, or ChAdOx1 was not associated with an increased risk of VTE during the 1–21 days risk period. SARS-CoV-2 infection was associated with increased risk of VTE (IRR 39.84, 95% CI 27.45–32.44). Our findings showed low event rates of thrombocytopenia and VTE following booster vaccination with comparable safety profiles between those who received homologous and heterologous booster combinations. Our findings showed the risk of thrombocytopenia and VTE was not increased after COVID-19 vaccination while the risks were substantially higher after SARS-CoV-2 infection. [ABSTRACT FROM AUTHOR]

The spread of misinformation transgresses international boundaries, between languages and cultures. This is especially evident in times of global crises such as the Covid-19 pandemic. This study observes misinformation on Twitter in the Japanese and English languages regarding false claims that the drug Ivermectin is an effective treatment for Covid-19. Our exploratory cross-lingual analysis identifies key themes of discussion and influential users in both languages, finding English misinformation to be highly popular amongst Japanese users. Significantly, an analysis of the timing of retweets between languages reveals that Japanese users find and widely share English misinformation often before English users themselves. This contradicts expectations that users from other languages tend to pick up on popular misinformation in English. Instead, they seek out English language sources irrespective of their popularity to support their agenda. These results emphasise the importance of cross-lingual mitigation strategies for organizations trying to combat misinformation, and that they must look beyond their own language spheres. [ABSTRACT FROM AUTHOR]

COVID-19 vaccination during pregnancy is safe and effective in reducing the risk of complications. However, the uptake is still below targets worldwide. This study aimed to explore the factors associated with COVID-19 vaccination uptake among pregnant women since data on this topic is scarce in low-to-middle-income countries. A retrospective cohort study included linked data on COVID-19 vaccination and pregnant women who delivered a singleton live birth from August 1, 2021, to July 31, 2022, in Rio de Janeiro City, Brazil. Multiple logistic regression was performed to identify factors associated with vaccination during pregnancy, applying a hierarchical model and describing odds ratio with 95% confidence intervals. Of 65,304 pregnant women included in the study, 53.0% (95% CI, 52–53%) received at least one dose of COVID-19 vaccine during pregnancy. Higher uptake was observed among women aged older than 34 (aOR 1.21, 95%CI 1.15–1.28), black (aOR 1.10, 1.04–1.16), or parda/brown skin colour (aOR 1.05, 1.01–1.09), with less than eight years of education (aOR 1.09, 1.02–1.17), living without a partner (aOR 2.24, 2.16–2.34), more than six antenatal care appointments (aOR 1.92, 1.75–2.09), and having a previous child loss (OR 1.06, 1.02–1.11). These results highlight the need for targeted educational campaigns, trustful communication, and accessibility strategies for specific populations to improve vaccination uptake during pregnancy. [ABSTRACT FROM AUTHOR]

Following restrictions to control the spread of COVID-19, and subsequent vaccination campaigns, sentiments against such policies were quick to arise. While individual-level determinants that led to such attitudes have drawn much attention, there are also reasons to believe that the macro context in which these movements arose may contribute to their evolution. In this study, exploiting data on business activities which supported a major Italian anti-restriction and anti-vaccine movement, IoApro, using quantitative analysis that employs both a fractional response probit and logit model and a beta regression model, we investigate the relationship between socio-economic characteristics, institutional quality, and the flourishing of this movement. Our results suggest a U-shaped relationship between income and the proliferation of the movement, meaning that support for these movements increases the greater the degree of economic decline. Our results further indicate that the share of the population between 40 and 60 years old is positively related to support for such movements, as is institutional corruption. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has forced lifestyles changes and affected the relationships between fathers and their infants. However, the factors associated with paternal–infant bonding have not been clarified. This study aimed to explore the factors associated with father–infant bonding during the COVID-19 pandemic in Japan. This cross-sectional study used data from a nationwide survey and the Japanese version of the Mother-to-Infant Bonding Scale (MIBS) to measure father–infant bonding. The participants were divided into two groups depending on their partners' parity. A linear regression model (Gauss–Markov-type) was used for both groups. A total of 1055 men were included in the analysis. Of these men, 521 (49.4%) had a primipara partner, and 534 (50.6%) had a multipara partner. No significant differences were found between the two groups' MIBS-J scores. Fathers' mental health, relationship with the partner and family members, abusive behavior towards children, wanted pregnancy, and the youngest child's Neonatal Intensive Care Unit admission history were associated with father–infant bonding. Regarding factors related to COVID-19, caring for the child while the partner is at home has a negative impact on bonding, while fear related to infection with COVID-19 has no negative impact on bonding. [ABSTRACT FROM AUTHOR]

Human sociality is governed by two types of social norms: injunctive norms, which prescribe what people ought to do, and descriptive norms, which reflect what people actually do. The process by which these norms emerge and their causal influences on cooperative behavior over time are not well understood. Here, we study these questions through social norms influencing mask wearing during the COVID-19 pandemic. Leveraging 2 years of data from the United States (18 time points; n = 915), we tracked mask wearing and perceived injunctive and descriptive mask wearing norms as the pandemic unfolded. Longitudinal trends suggested that norms and behavior were tightly coupled, changing quickly in response to public health recommendations. In addition, longitudinal modeling revealed that descriptive norms caused future increases in mask wearing across multiple waves of data collection. These cross-lagged causal effects of descriptive norms were large, even after controlling for non-social beliefs and demographic variables. Injunctive norms, by contrast, had less frequent and generally weaker causal effects on future mask wearing. During uncertain times, cooperative behavior is more strongly driven by what others are actually doing, rather than what others think ought to be done. [ABSTRACT FROM AUTHOR]

Sleep is responsible for maintenance and regulatory functions in human physiology. Insufficient sleep has been associated with cardiovascular disease, weight gain, obesity, inflammation, and morbidity. University students are at high risk under normal circumstances of stress and anxiety due to extracurricular demands, competing pressures on student time, long study hours, and financial concerns. The COVID 19 pandemic has disrupted normal college students' lives adding stresses such as lost jobs and family responsibilities such as serving as caregivers, which disproportionally affect minority and rural student. This study aimed to assess the correlation of sleep disorders in New Mexico State University students during COVID 19 with selected variates including base demographics (e.g., gender, age, etc.), lifestyle metrics (e.g., employment status, discipline, class, etc.), living arrangements (e.g., housing type, number of children, etc.), alcohol and tobacco use, vaccination status, family COVID status, and family vaccination status. Single- and multi-factor logistic regressions were performed to analyze the data on the students. Qualtrics software was used to collect data on demographics and sleep disorders. R software was used for data analysis. Correlations were found between sleeping less, sleeping more, and disturbed sleep among several covariate categories. For all three responses, being married (sleeping less: OR = 0.342, 95% CI = 0.181–0.642, sleeping more: OR = 0.265, 95% CI = 0.111–0.591; disturbed sleeping: OR = 0.345, 95% CI = 0.182–0.650), frequency of feeling sleepy-very often (OR = 16.87, 95% CI = 6.571–47.434; OR = 8.393, 95% CI = 3.086–25.298; OR = 13.611, 95% CI = 5.409–36.975) and change in diet- quality decreased (OR = 7.304, 95% CI = 3.615–15.270; OR = 5.250, 95% CI = 2.309–12.558; OR = 4.181, 95% CI = 2.145–8.359) were all significant correlated to change in sleeping behavior. Other correlations were found among covariates and sleep changes. Several covariates were determined to be correlated with the effect of COVID-19 on sleeping. [ABSTRACT FROM AUTHOR]

According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a significant number of African Americans had been infected with the coronavirus disease, experiencing disproportionately higher death rates compared to other demographic groups. These disparities highlight the urgent need to examine the experiences, behaviors, and opinions of the African American population in relation to the COVID-19 pandemic. By understanding their unique challenges in navigating matters of health and well-being, we can work towards promoting health equity, eliminating disparities, and addressing persistent barriers to care. Since Twitter data has shown significant promise as a representation of human behavior and for opinion mining, this study leverages Twitter data published in 2020 to characterize the pandemic-related experiences of the United States' African American population using aspect-based sentiment analysis. Sentiment analysis is a common task in natural language processing that identifies the emotional tone (i.e., positive, negative, or neutral) of a text sample. Aspect-based sentiment analysis increases the granularity of sentiment analysis by also extracting the aspect for which sentiment is expressed. We developed a machine learning pipeline consisting of image and language-based classification models to filter out tweets not related to COVID-19 and those unlikely published by African American Twitter subscribers, leading to an analysis of nearly 4 million tweets. Overall, our results show that the majority of tweets had a negative tone, and that the days with larger numbers of published tweets often coincided with major U.S. events related to the pandemic as suggested by major news headlines (e.g., vaccine rollout). We also show how word usage evolved throughout the year (e.g., outbreak to pandemic and coronavirus to covid). This work also points to important issues like food insecurity and vaccine hesitation, along with exposing semantic relationships between words, such as covid and exhausted. As such, this work furthers understanding of how the nationwide progression of the pandemic may have impacted the narratives of African American Twitter users. [ABSTRACT FROM AUTHOR]

Containing a pandemic requires that individuals adhere to measures such as wearing face-masks and getting vaccinated. Therefore, identifying predictors and motives for both behaviors is of importance. Here, we study the decisions made by a cross-national sample in randomized hypothetical scenarios during the COVID-19 pandemic. Our results show that mask-wearing was predicted by empathic tendencies, germ aversion, and higher age, whilst belief in misinformation and presentation of an interaction partner as a family member lowered the safety standards. The main motives associated with taking the mask off included: rationalization, facilitating interaction, and comfort. Vaccination intention was positively predicted by empathy, and negatively predicted by belief in misinformation and higher costs of the vaccine. We found no effect of immunization status of the surrounding social group. The most common motive for vaccination was protection of oneself and others, whereas undecided and anti-vaccine groups reported doubts about the effectiveness and fear of side effects. Together, we identify social and psychological predictors and motives of mask-wearing behavior and vaccination intention. The results highlight the importance of social context for mask-wearing, easy access to vaccines, empathy, and trust in publicly distributed information. [ABSTRACT FROM AUTHOR]

When communicating about political issues, messages targeted to resonate with the core values of the receiver may be effective, an approach known as moral reframing. During the COVID-19 pandemic, we tested the relationships between moral values and mask-wearing in a sample (N = 540) of self-identified liberals, conservatives, and moderates in the United States. Anti-mask attitudes were stronger in conservatives, and were associated with increased concerns for in-group loyalty, national identity, and personal liberty. We then crafted messages about the benefits of mask-wearing framed to resonate with these moral concerns, and in a pre-registered study of N = 597 self-identified U.S. conservatives, tested the effect of moral reframing on anti-mask attitudes and behaviors. Messages framed in terms of loyalty, with appeals to the protection of the community and America, were effective in reducing anti-mask beliefs, compared with unrelated control messages and messages delivering purely scientific information, and these changes in belief persisted for at least 1 week. Exploratory analyses showed that participants who saw loyalty-framed messages reported wearing masks in public more frequently in the subsequent week. This study provides evidence that framing messages about health behaviors in terms of group loyalty may be one productive way of communicating with conservative audiences. [ABSTRACT FROM AUTHOR]

In this work, the COVID-19 pandemic burden in Ukraine is investigated retrospectively using the excess mortality measures during 2020–2021. In particular, the epidemic impact on the Ukrainian population is studied via the standardized both all-cause and cause-specific mortality scores before and during the epidemic. The excess mortality counts during the pandemic were predicted based on historic data using parametric and nonparametric modeling and then compared with the actual reported counts to quantify the excess. The corresponding standardized mortality P-score metrics were also compared with the neighboring countries. In summary, there were three "waves" of excess all-cause mortality in Ukraine in December 2020, April 2021 and November 2021 with excess of 32%, 43% and 83% above the expected mortality. Each new "wave" of the all-cause mortality was higher than the previous one and the mortality "peaks" corresponded in time to three "waves" of lab-confirmed COVID-19 mortality. The lab-confirmed COVID-19 mortality constituted 9% to 24% of the all-cause mortality during those three peak months. Overall, the mortality trends in Ukraine over time were similar to neighboring countries where vaccination coverage was similar to that in Ukraine. For cause-specific mortality, the excess observed was due to pneumonia as well as circulatory system disease categories that peaked at the same times as the all-cause and lab-confirmed COVID-19 mortality, which was expected. The pneumonias as well as circulatory system disease categories constituted the majority of all cases during those peak times. The seasonality in mortality due to the infectious and parasitic disease category became less pronounced during the pandemic. While the reported numbers were always relatively low, alcohol-related mortality also declined during the pandemic. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has produced widespread behaviour changes that shifted how people split their time between different environments, altering health risks. Here, we report an update of North American activity patterns before and after pandemic onset, and implications to radioactive radon gas exposure, a leading cause of lung cancer. We surveyed 4009 Canadian households home to people of varied age, gender, employment, community, and income. Whilst overall time spent indoors remained unchanged, time in primary residence increased from 66.4 to 77% of life (+ 1062 h/y) after pandemic onset, increasing annual radiation doses from residential radon by 19.2% (0.97 mSv/y). Disproportionately greater changes were experienced by younger people in newer urban or suburban properties with more occupants, and/or those employed in managerial, administrative, or professional roles excluding medicine. Microinfluencer-based public health messaging stimulated health-seeking behaviour amongst highly impacted, younger groups by > 50%. This work supports re-evaluating environmental health risks modified by still-changing activity patterns. [ABSTRACT FROM AUTHOR]

In the absence of real-time surveillance data, it is difficult to derive an early warning system and potential outbreak locations with the existing epidemiological models, especially in resource-constrained countries. We proposed a contagion risk index (CR-Index)—based on publicly available national statistics—founded on communicable disease spreadability vectors. Utilizing the daily COVID-19 data (positive cases and deaths) from 2020 to 2022, we developed country-specific and sub-national CR-Index for South Asia (India, Pakistan, and Bangladesh) and identified potential infection hotspots—aiding policymakers with efficient mitigation planning. Across the study period, the week-by-week and fixed-effects regression estimates demonstrate a strong correlation between the proposed CR-Index and sub-national (district-level) COVID-19 statistics. We validated the CR-Index using machine learning methods by evaluating the out-of-sample predictive performance. Machine learning driven validation showed that the CR-Index can correctly predict districts with high incidents of COVID-19 cases and deaths more than 85% of the time. This proposed CR-Index is a simple, replicable, and easily interpretable tool that can help low-income countries prioritize resource mobilization to contain the disease spread and associated crisis management with global relevance and applicability. This index can also help to contain future pandemics (and epidemics) and manage their far-reaching adverse consequences. [ABSTRACT FROM AUTHOR]

The COVID-19 Vaccines Global Access (COVAX) is a World Health Organization (WHO) initiative that aims for an equitable access of COVID-19 vaccines. Despite potential heterogeneous infection levels across a country, countries receiving allotments of vaccines may follow WHO's allocation guidelines and distribute vaccines based on a jurisdictions' relative population size. Utilizing economic—epidemiological modeling, we benchmark the performance of this pro rata allocation rule by comparing it to an optimal one that minimizes the economic damages and expenditures over time, including a penalty representing the social costs of deviating from the pro rata strategy. The pro rata rule performs better when the duration of naturally- and vaccine-acquired immunity is short, when there is population mixing, when the supply of vaccine is high, and when there is minimal heterogeneity in demographics. Despite behavioral and epidemiological uncertainty diminishing the performance of the optimal allocation, it generally outperforms the pro rata vaccine distribution rule. [ABSTRACT FROM AUTHOR]

The consistent increase of Coronavirus disease 2019 (COVID-19) cases parallel with the rate of deaths and the controversial response regarding the vaccines caused an increase in the burden of psychological diseases. This study aimed to evaluate the psychological condition of healthcare workers (HCWs) in a pediatric cancer hospital and to identify the knowledge, attitude, and perception (KAP) of HCWs toward COVID-19 vaccination. A cross-sectional observational study was conducted between April to May 2021. A validated, confidential survey was employed to measure the mental health of HCWs and the KAP toward COVID-19 vaccines. The total responses were 395, of which 11.4% physicians, 18.5% pharmacists, and 70.1% were nurses. Sixty-six percent of HCWs had different degrees of anxiety and depression. Nurses significantly accounted for the highest anxiety levels (P = 0.003), while the cumulative anxiety score was significantly higher in HCWs who had a positive history of COVID-19 infection (P = 0.026). Although 67.6% of HCWs believe that "vaccines are essential for us,", the vaccination rate was 21.3%. The Factors associated with not receiving the vaccine were younger ages (P = 0.014), nurses (P = 3.6987 × 10–7), negative history of COVID-19 infection (P = 0.043) and believing that infections can happen after taking the vaccine (P = 1.5833 × 10–7). Healthcare organizations must take serious intervention to decrease the mental load on HCWs and facilitate the vaccination process. [ABSTRACT FROM AUTHOR]

One year after the outbreak of COVID-19, medical staff are facing high anxiety due to multiple work stresses. Social support has become a protective factor for healthcare workers' anxiety symptoms, but the exact mechanism of action is not yet known. Based on the buffering model, this study aims to explore the impact and mechanisms of action of healthcare workers' perception of social support (PSS) on anxiety symptoms in the context of the epidemic and to further explore how the emotional characteristics of risk perception (ECRP) and resilience play their influence. To this end, this study measured 839 healthcare workers using an online questionnaire from 4 February to 1 March 2021. The results found that PSS among healthcare workers negatively predicted anxiety symptoms. ECRP partially mediated the relationship between PSS and anxiety symptoms, and resilience moderated the first half of the pathway in the model of PSS through ECRP on anxiety symptoms. The emotional characteristics of risk perception of COVID-19 in individuals with high resilience decrease significantly with the increase of PSS, while this change is not significant in individuals with low resilience. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic created enormous public health and socioeconomic challenges. The health effects of vaccination and non-pharmaceutical interventions (NPIs) were often contrasted with significant social and economic costs. We describe a general framework aimed to derive adaptive cost-effective interventions, adequate for both recent and emerging pandemic threats. We also quantify the net health benefits and propose a reinforcement learning approach to optimise adaptive NPIs. The approach utilises an agent-based model simulating pandemic responses in Australia, and accounts for a heterogeneous population with variable levels of compliance fluctuating over time and across individuals. Our analysis shows that a significant net health benefit may be attained by adaptive NPIs formed by partial social distancing measures, coupled with moderate levels of the society's willingness to pay for health gains (health losses averted). We demonstrate that a socially acceptable balance between health effects and incurred economic costs is achievable over a long term, despite possible early setbacks. [ABSTRACT FROM AUTHOR]

Considering the emergence of SARS-CoV-2 variants and low vaccine access and uptake, minimizing human interactions remains an effective strategy to mitigate the spread of SARS-CoV-2. Using a functional principal component analysis, we created a multidimensional mobility index (MI) using six metrics compiled by SafeGraph from all counties in Illinois, Ohio, Michigan and Indiana between January 1 to December 8, 2020. Changes in mobility were defined as a time-updated 7-day rolling average. Associations between our MI and COVID-19 cases were estimated using a quasi-Poisson hierarchical generalized additive model adjusted for population density and the COVID-19 Community Vulnerability Index. Individual mobility metrics varied significantly by counties and by calendar time. More than 50% of the variability in the data was explained by the first principal component by each state, indicating good dimension reduction. While an individual metric of mobility was not associated with surges of COVID-19, our MI was independently associated with COVID-19 cases in all four states given varying time-lags. Following the expiration of stay-at-home orders, a single metric of mobility was not sensitive enough to capture the complexity of human interactions. Monitoring mobility can be an important public health tool, however, it should be modelled as a multidimensional construct. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic had a negative impact on the mental health and well-being (WB) of citizens. This cross-sectional study included 4 waves of data collection aimed at identifying profiles of individuals with different levels of WB. The study included a representative stratified sample of 10,013 respondents in Italy. The WHO 5-item well-being scale (WHO-5) was used for the assessment of WB. Different supervised machine learning approaches (multinomial logistic regression, partial least-square discriminant analysis—PLS-DA—, classification tree—CT—) were applied to identify individual characteristics with different WB scores, first in waves 1–2 and, subsequently, in waves 3 and 4. Forty-one percent of participants reported "Good WB", 30% "Poor WB", and 28% "Depression". Findings carried out using multinomial logistic regression show that Resilience was the most important variable able for discriminating the WB across all waves. Through the PLS-DA, Increased Unhealthy Behaviours proved to be the more important feature in the first two waves, while Financial Situation gained most relevance in the last two. COVID-19 Perceived Risk was relevant, but less than the other variables, across all waves. Interestingly, using the CT we were able to establish a cut-off for Resilience (equal to 4.5) that discriminated good WB with a probability of 65% in wave 4. Concluding, we found that COVID-19 had negative implications for WB. Governments should support evidence-based strategies considering factors that influence WB (i.e., Resilience, Perceived Risk, Healthy Behaviours, and Financial Situation). [ABSTRACT FROM AUTHOR]

The outbreak of the pandemic Covid-19 has transformed the education system in most countries worldwide. Following the lockdown measures in Malaysia, the Malaysian education system has fully transformed from conventional learning to online learning or known as e-learning as an alternative to minimize social contacts and physical communication to curb the transmission of Covid-19. In this regard, this study aims to identify the challenges faced by students in higher learning institutions throughout Malaysia during the implementation of the e-learning program. This study is based on a large sampling consisting of 2394 students from both public and private universities. The result from this study is analyzed through inferential methods such as the Spatial Analysis, the Principal Component Analysis, and the Mann–Whitney U test and through descriptive methods using the frequency analysis and the percentage analysis. Findings from this study suggest that location significantly influenced the challenges faced by students throughout the implementation of e-learning in higher learning institutions. For example, students in rural areas which can be identified as "vulnerable groups" are more likely to face both technical and connection with the internet access, tend to have a declining focus on learning and are prone to physical health problems, facing social isolation and low digital literacy compared to students in urban areas. Based on geographical analysis, students in Sabah, Perlis, and Melaka are most at risk of facing e-learning challenges. An anomaly case of students in Kuala Lumpur, however, posed another different result compared to other cities as they confront similar challenges with students in rural areas. This study provides the nuances of location and its implications for vulnerable groups that may put them at disadvantage in the e-learning program. Findings from this study will help to inform the relevant authorities and policymakers in improving the implementation of e-learning in Malaysia, especially towards the vulnerable groups so that it can be delivered more systematically and efficiently. [ABSTRACT FROM AUTHOR]

Social distancing remains an effective nonpharmaceutical behavioral interventions to limit the spread of COVID-19 and other airborne diseases, but monitoring and enforcement create nontrivial challenges. Several jurisdictions have turned to "311" resident complaint platforms to engage the public in reporting social distancing non-compliance, but differences in sensitivity to social distancing behaviors can lead to a mis-allocation of resources and increased health risks for vulnerable communities. Using hourly visit data to designated establishments and more than 71,000 social distancing complaints in New York City during the first wave of the pandemic, we develop a method, derived from the Weber-Fechner law, to quantify neighborhood sensitivity and assess how tolerance to social distancing infractions and complaint reporting behaviors vary with neighborhood characteristics. We find that sensitivity to non-compliance is lower in minority and low-income neighborhoods, as well as in lower density areas, resulting in fewer reported complaints than expected given measured levels of overcrowding. [ABSTRACT FROM AUTHOR]

Vaccination is a key strategy for controlling the SARS-CoV-2 pandemic. Acceptance of SARS-CoV-2 vaccines by chronically ill patients, such as multiple sclerosis (MS) patients, plays an important role in prevention of complicated disease course. This longitudinal, prospective, multi-centre-study of German MS-patients aimed to detect socio-demographic, clinical, or psychological determinants of attitudes towards standard vaccines, SARS-CoV-2 vaccines, and governmental measures before/during the pandemic. Exactly 404 MS-patients were investigated by standardized questionnaires and structured interviews on socio-demographic, clinical-neurological, and psychological characteristics, vaccination status, and vaccination from June 2019. Data on SARS-CoV-2 vaccination willingness were collected in two follow-up assessments (1st: June to July 2020, before SARS-CoV-2 vaccine availability, N = 200; 2nd: March to May 2021, after SARS-CoV-2 vaccine availability, N = 157). Age, sex, MS course type, depression, and personality characteristics (Extraversion, Novelty seeking, Self-directedness, and Cooperativeness) were significantly associated with vaccination willingness. Although the majority of MS-patients showed SARS-CoV-2 vaccination willingness at both follow-ups (1st: 60%, 2nd: 61%), a substantial proportion had concerns and were undecided or opposed to vaccination. Socio-demographic variables like age and sex, psychopathological status, and various personality characteristics might influence vaccination willingness and should be considered when discussing with MS-patients about SARS-CoV-2 vaccination. [ABSTRACT FROM AUTHOR]

In several longitudinal studies, reduced willingness to show COVID-19-related preventive behavior (e.g., wearing masks, social distancing) has been partially attributed to misinformation and conspiracy beliefs. However, there is considerable uncertainty with respect to the strength of the relationship and whether the negative relationship exists in both directions (reciprocal effects). One explanation of the heterogeneity pertains to the fact that the time interval between consecutive measurement occasions varies (e.g., 1 month, 3 months) both between and within studies. Therefore, a continuous time meta-analysis based on longitudinal studies was conducted. This approach enables one to examine how the strength of the relationship between conspiracy beliefs and COVID-19 preventive behavior depends on the time interval. In total, 1035 correlations were coded for 17 samples (N = 16,350). The results for both the full set of studies and a subset consisting of 13 studies corroborated the existence of reciprocal effects. Furthermore, there was some evidence of publication bias. The largest cross-lagged effects were observed between 3 and 6 months, which can inform decision-makers and researchers when carrying out interventions or designing studies examining the consequences of new conspiracy theories. [ABSTRACT FROM AUTHOR]

The rapid spread of conspiracy ideas associated with the recent COVID-19 pandemic represents a major threat to the ongoing and coming vaccination programs. Yet, the cognitive factors underlying the pandemic-related conspiracy beliefs are not well described. We hypothesized that such cognitive style is driven by delusion proneness, a trait phenotype associated with formation of delusion-like beliefs that exists on a continuum in the normal population. To probe this hypothesis, we developed a COVID-19 conspiracy questionnaire (CCQ) and assessed 577 subjects online. Their responses clustered into three factors that included Conspiracy, Distrust and Fear/Action as identified using principal component analysis. We then showed that CCQ (in particular the Conspiracy and Distrust factors) related both to general delusion proneness assessed with Peter's Delusion Inventory (PDI) as well as resistance to belief update using a Bias Against Disconfirmatory Evidence (BADE) task. Further, linear regression and pathway analyses suggested a specific contribution of BADE to CCQ not directly explained by PDI. Importantly, the main results remained significant when using a truncated version of the PDI where questions on paranoia were removed (in order to avoid circular evidence), and when adjusting for ADHD- and autistic traits (that are known to be substantially related to delusion proneness). Altogether, our results strongly suggest that pandemic-related conspiracy ideation is associated with delusion proneness trait phenotype. [ABSTRACT FROM AUTHOR]

To assess the frequency of persisting symptoms after SARS-CoV-2 infection and assessment of the effects of COVID-19 pandemic on selected parameters of self-reported health status and well-being half a year after the disease. The study population consisted of 3 groups: post-COVID-19 group I—172 patients; group II—172 patients with chronic disease, who have not suffered from COVID-19; group III—81 patients from a population study cohort—Bialystok PLUS. A standardized interview questionnaire was used to collect data in the three groups using the CATI (computer assisted telephone interviewing) technique. Interviews were conducted between October 2020 and January 2021, thus during the second wave of the pandemic in Poland. The subjective state of health in comparison with the state of health before the COVID-19 pandemic deteriorated in COVID-19 convalescents. Patients, who suffered from symptomatic COVID-19 were more prone to nervousness, anxiousness, tension than patients with oligosymptomatic course of the disease. Moreover, anxiety, fear and irritability were more frequent in Group I and II in comparison to Group III, whereas Group I and II did not differ significantly. The decrease in physical activity observed in COVID-19 patients mirrored the changes in general population. The most frequent persistent symptoms after COVID-19 are: general malaise, cough, smell and taste disorder, dyspnea. COVID-19 convalescents who experienced symptomatic disease are more prone to development of nervousness, anxiousness, tension and anxiety than patients with oligosymptomatic course of the disease. Females and younger patients who suffered from COVID-19 are more prone to development of mental distress than healthy population. No significant differences between COVID-19 convalescents and healthy population was observed as far as the attitude towards physical activity is concerned. [ABSTRACT FROM AUTHOR]

In order to slow the spread of the CoViD-19 pandemic, governments around the world have enacted a wide set of policies limiting the transmission of the disease. Initially, these focused on non-pharmaceutical interventions; more recently, vaccinations and large-scale rapid testing have started to play a major role. The objective of this study is to explain the quantitative effects of these policies on determining the course of the pandemic, allowing for factors like seasonality or virus strains with different transmission profiles. To do so, the study develops an agent-based simulation model, which explicitly takes into account test demand and behavioral changes following positive tests. The model is estimated using data for the second and the third wave of the CoViD-19 pandemic in Germany. The paper finds that during a period where vaccination rates rose from 5 to 40%, seasonality and rapid testing had the largest effect on reducing infection numbers. Frequent large-scale rapid testing should remain part of strategies to contain CoViD-19; it can substitute for many non-pharmaceutical interventions that come at a much larger cost to individuals, society, and the economy. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, many countries implemented international travel restrictions that aimed to contain viral spread while still allowing necessary cross-border travel for social and economic reasons. The relative effectiveness of these approaches for controlling the pandemic has gone largely unstudied. Here we developed a flexible network meta-population model to compare the effectiveness of international travel policies, with a focus on evaluating the benefit of policy coordination. Because country-level epidemiological parameters are unknown, they need to be estimated from data; we accomplished this using approximate Bayesian computation, given the nature of our complex stochastic disease transmission model. Based on simulation and theoretical insights we find that, under our proposed policy, international airline travel may resume up to 58% of the pre-pandemic level with pandemic control comparable to that of a complete shutdown of all airline travel. Our results demonstrate that global coordination is necessary to allow for maximum travel with minimum effect on viral spread. [ABSTRACT FROM AUTHOR]

This population-based observational, cross-sectional, and descriptive survey was to investigate the relationship of increased face mask usage in the coronavirus disease (COVID-19) era with mask-associated dry eye (MADE). Participants aged 6–79 years old with formal school education were selected. All participants finished the 19-item questionnaire online, distributed through different social media platforms. From 6925 participants who submitted eligible questionnaires, MADE was reported in 547 participants, which included 419 participants who developed new dry eye symptoms after wearing face masks and 128 participants whose pre-existing dry eye symptoms worsened with mask wearing. Longer time of face mask wearing, nonstandard wearing of face masks, reduced outdoor time, decreased daily reading time, shortened visual display terminals time, and dry environment were positively associated with MADE. There were significant associations between perceived MADE and age, female sex, education, use of glasses and contact lenses, and pre-existing dry eye. MADE was more common in adults aged > 20 years than those aged ≤ 20 years or juveniles. MADE incidence increased. Standard wearing of face masks was suggested as a protective factor for MADE. Awareness about the possible risk of MADE should also be created and the clinical dry eye signs should be verified. Clinical trial registration number: NCT04744805. [ABSTRACT FROM AUTHOR]

How should health authorities communicate to motivate the public to comply with health advice during a prolonged health crisis such as a pandemic? During the SARS-CoV-2 pandemic, for example, people have had to comply with successive restrictions as the world faced multiple races between controlling new waves of the virus and the development and implementation of vaccines. Here, we examine how health authorities and governments most effectively motivate the public by focusing on a specific race: between the Alpha variant and the implementation of the first generation of COVID-19 vaccinations in the winter of 2021. Following prior research on crisis communication, we focus on appeals to fear and hope using communicative aids in the form of visualizations based on epidemiological modelling. Using a population-based experiment conducted in United States ( N = 3 , 022 ), we demonstrate that a hope-oriented visual communication aid, depicting the competing effects on the epidemic curve of (1) a more infectious variant and (2) vaccinations, motivates public action more effectively than a fear-oriented visual communication, focusing exclusively on the threat of the new variant. The importance of the implementation of such hope-oriented messages is further highlighted by cross-national representative surveys from eight countries ( N = 3 , 995 ), which demonstrate that feelings of fear towards the Alpha variant alone were insufficient to activate strong compliance. Overall, these findings provide general insights into the importance of hope as a health communication strategy during the COVID-19 pandemic and beyond. [ABSTRACT FROM AUTHOR]

For countries starting to receive steady supplies of vaccines against SARS-CoV-2, the course of Covid-19 for the following months will be determined by the emergence of new variants and successful roll-out of vaccination campaigns. To anticipate this scenario, we used a multilayer network model developed to forecast the transmission dynamics of Covid-19 in Costa Rica, and to estimate the impact of the introduction of the Delta variant in the country, under two plausible vaccination scenarios, one sustaining Costa Rica's July 2021 vaccination pace of 30,000 doses per day and with high acceptance from the population and another with declining vaccination pace to 13,000 doses per day and with lower acceptance. Results suggest that the introduction and gradual dominance of the Delta variant would increase Covid-19 hospitalizations and ICU admissions by 35 % and 33.25 % , respectively, from August 2021 to December 2021, depending on vaccine administration and acceptance. In the presence of the Delta variant, new Covid-19 hospitalizations and ICU admissions are estimated to increase around 24.26 % and 27.19 % , respectively, in the same period if the vaccination pace drops. Our results can help decision-makers better prepare for the Covid-19 pandemic in the months to come. [ABSTRACT FROM AUTHOR]

Pharmacological and non-pharmacological measures will overlap for a period after the onset of the pandemic, playing a strong role in virus containment. We explored which factors influence the likelihood to adopt two different preventive measures against the COVID-19 pandemic. An online snowball sampling (May–June 2020) collected a total of 448 questionnaires in Italy. A Bayesian bivariate Gaussian regression model jointly investigated the willingness to get vaccinated against COVID-19 and to download the national contact tracing app. A mixed-effects cumulative logistic model explored which factors affected the motivation to adopt one of the two preventive measures. Despite both COVID-19 vaccines and tracing apps being indispensable tools to contain the spread of SARS-CoV-2, our results suggest that adherence to the vaccine or to the national contact tracing app is not predicted by the same factors. Therefore, public communication on these measures needs to take in consideration not only the perceived risk associated with COVID-19, but also the trust people place in politics and science, their concerns and doubts about vaccinations, and their employment status. Further, the results suggest that the motivation to comply with these measurements was predominantly to protect others rather than self-protection. [ABSTRACT FROM AUTHOR]

Several vaccines with different efficacies and effectivenesses are currently being distributed across the world to control the COVID-19 pandemic. Having enough doses from the most efficient vaccines in a short time is not possible for all countries. Hence, policymakers may propose using various combinations of available vaccines to control the pandemic with vaccine-induced herd immunity by vaccinating a fraction of the population. The classic vaccine-induced herd-immunity threshold suggests that we can stop spreading the disease by vaccinating a fraction of the population. However, that classic threshold is defined only for a single vaccine and may be invalid and biased when we have multi-vaccine strategies for a disease or multiple variants, potentially leading policymakers to suboptimal vaccine-allocation policies. Here, we determine which combination of multiple vaccines may lead to herd immunity. We show that simplifying the problem and considering the vaccination of the population as a single-vaccine strategy whose effectiveness is the sample mean of all effectivenesses would not be ideal, because many multi-vaccine strategies with a smaller herd-immunity threshold can be proposed. We show that the herd-immunity threshold may vary due to changes in vaccine-uptake proportions. Moreover, we propose methods to determine the optimal combination of multiple vaccines in order to achieve herd immunity and apply our results to the issue of multiple variants. In addition, we determine a condition for reaching herd immunity in the presence of new emerging variants of concern. We show by example that new variants could influence our estimation of the vaccination reproduction number. It follows that the herd-immunity threshold must be updated not only when multi-vaccine strategies are used but also when multiple variants coexist in the population. [ABSTRACT FROM AUTHOR]

The COVID-19 global pandemic has significantly impacted every aspect of life all over the world. The United States is reported to have suffered more than 20% of the global casualties from this pandemic. It is imperative to investigate the growth dynamics of the disease in the US based on varying geographical and governmental factors that best manifest itself in each State of the Country. This paper utilizes a hybrid machine learning and continuum deformation-based approach for analyzing the stability and growth rate of the pandemic. To this end, principal stress values of the pandemic continuum body are obtained using Mohr's Circle method and overlapping, moving windows of data are analysed successively. This helps in finding the correlations between the growth rate and Governments' action/Public's reaction. Government actions include "state of emergency", "shelter at place", and "phase declarations". We also consider the vaccination rate milestones, which shows us the coordinated Governments' action/Public's reaction. Finally, a number of recommendations are made to the Governments and people for better management of future pandemics. [ABSTRACT FROM AUTHOR]