Health inequity in pandemic anxiety about COVID-19 infection and socioeconomic consequences in Japan: A structural equation modeling approach

BACKGROUND: Health inequity in relation to COVID-19 infection and socioeconomic consequences is a major global concern. Mental health issues in vulnerable populations have received special attention in research and practice during the COVID-19 pandemic. However, there is limited evidence on the nature of the anxieties experienced as a result of COVID-19, and how such concerns vary across demographic groups. AIM: This study examines anxiety among the working population of Japan (aged 18–59), in terms of both COVID-19 infection and socioeconomic consequences, using an internationally validated tool, the Pandemic Anxiety Scale (PAS). METHODS: Data were collected using an online survey (n = 2,764). The analyses included an exploratory factor analysis (EFA), a confirmatory factor analysis (CFA), and structural equation modeling (SEM), followed by validation of the Japanese version of the PAS. RESULTS: A two-factor latent variable model shows the multidimensionality of anxiety in regard to the COVID-19 pandemic and the disparity across population groups in predicting the two defined anxiety dimensions. Several path coefficients showed somewhat unexpected and/or unique results from Japan compared with previous European studies. Specifically, self-reported health status was not significantly related to disease anxiety, and those who were not in paid employment reported lower consequence anxiety. The SEM results showed a greater number of significant exogenous variables for consequence anxiety compared to disease anxiety, highlighting disparities in pandemic anxiety by socioeconomic status in regard to socioeconomic consequences of the pandemic. CONCLUSION: In contrast to existing European studies, evidence from the current study suggests contextual patterns of health inequity. Due to the prolonged socioeconomic consequences of the pandemic, multidisciplinary research on mental health issues and the quality of life remains an important research agenda in exploring socioeconomic measures in context, towards addressing inequity concerns

Wealth inequalities in physical and cognitive impairments across Japan and Europe: the role of health expenditure and infrastructure

Although prior research has provided insights into the association between country-level factors and health inequalities, key research gaps remain. First, most previous studies examine subjective rather than objective health measures. Second, the wealth dimension in health inequalities is understudied. Third, a handful of studies explicitly focus on older adults. To bridge these research gaps, this study measures wealth-related inequalities in physical and cognitive impairments and examines the extent to which welfare states moderate wealth inequalities in physical and cognitive impairments among older people across Japan and Europe. We utilized harmonized data on non-institutionalized individuals aged 50–75 from the Japanese Study of Aging and Retirement (JSTAR) and the Survey of Health, Ageing and Retirement in Europe (SHARE) (N = 31,969 for physical impairments and 31,348 for cognitive impairments). Our multilevel linear regression analyses examined whether national public health spending and healthcare access resources explained cross-country differences in wealth inequalities in physical and cognitive impairments. We applied a concentration index to quantify the degree of wealth inequalities in impairments. The findings indicate that inequalities in both impairment outcomes favored wealthier individuals in all countries, but the magnitude of inequality varied by country. Furthermore, a higher share of public health spending, lower out-of-pocket expenditure, and higher investment in healthcare resources were associated with lower wealth inequalities, especially for physical impairments. Our findings suggest that different health interventions and policies may be needed to mitigate specific impairment inequalities

Social contacts, vaccination decisions and influenza in Japan.

BACKGROUND: Contact patterns and vaccination decisions are fundamental to transmission dynamics of infectious diseases. We report on age-specific contact patterns in Japan and their effect on influenza vaccination behaviour. METHODS: Japanese adults (N=3146) were surveyed in Spring 2011 to assess the number of their social contacts within a 24 h period, defined as face-to-face conversations within 2 m, and gain insight into their influenza-related behaviour. We analysed the duration and location of contacts according to age. Additionally, we analysed the probability of vaccination and influenza infection in relation to the number of contacts controlling for individual's characteristics. RESULTS: The mean and median reported numbers of daily contacts were 15.3 and 12.0, respectively. School-aged children and young adults reported the greatest number of daily contacts, and individuals had the most contacts with those in the same age group. The age-specific contact patterns were different between men and women, and differed between weekdays and weekends. Children had fewer contacts between the same age groups during weekends than during weekdays, due to reduced contacts at school. The probability of vaccination increased with the number of contacts, controlling for age and household size. Influenza infection among unvaccinated individuals was higher than for those vaccinated, and increased with the number of contacts. CONCLUSIONS: Contact patterns in Japan are age and gender specific. These contact patterns, as well as their interplay with vaccination decisions and infection risks, can help inform the parameterisation of mathematical models of disease transmission and the design of public health policies, to control disease transmission

Inventory of Data Sources for Estimating Health Care Costs in the United States

To develop an inventory of data sources for estimating health care costs in the United States and provide information to aid researchers in identifying appropriate data sources for their specific research questions

The dynamics of risk perceptions and precautionary behavior in response to 2009 (H1N1) pandemic influenza

<p>Abstract</p> <p>Background</p> <p>The trajectory of an infectious disease outbreak is affected by the behavior of individuals, and the behavior is often related to individuals' risk perception. We assessed temporal changes and geographical differences in risk perceptions and precautionary behaviors in response to H1N1 influenza.</p> <p>Methods</p> <p>1,290 US adults completed an online survey on risk perceptions, interests in pharmaceutical interventions (preventive intervention and curative intervention), and engagement in precautionary activities (information seeking activities and taking quarantine measures) in response to H1N1 influenza between April 28 and May 27 2009. Associations of risk perceptions and precautionary behaviors with respondents' sex, age, and household size were analyzed. Linear and quadratic time trends were assessed by regression analyses. Geographic differences in risk perception and precautionary behaviors were evaluated. Predictors of willingness to take pharmaceutical intervention were analyzed.</p> <p>Results</p> <p>Respondents from larger households reported stronger interest in taking medications and engaged in more precautionary activities, as would be normatively predicted. Perceived risk increased over time, whereas interest in pharmaceutical preventive interventions and the engagement in some precautionary activities decreased over time. Respondents who live in states with higher H1N1 incidence per population perceived a higher likelihood of influenza infection, but did not express greater interests in pharmaceutical interventions, nor did they engage in a higher degree of precautionary activities. Perceived likelihood of influenza infection, willingness to take medications and engagement in information seeking activities were higher for women than men.</p> <p>Conclusions</p> <p>Perceived risk of infection and precautionary behavior can be dynamic in time, and differ by demographic characteristics and geographical locations. These patterns will likely influence the effectiveness of disease control measures.</p

Models in finance and medicine using Bayesian inference

The purpose of this dissertation is to analyze three models in medicine and finance using Bayesian inference with the Markov chain Monte Carlo method. The model in medicine addresses cost-effectiveness analysis using copulas, and the two models in finance include discrete-time asset pricing models and a short-term interest rate model with stochastic volatility. The first chapter develops the model that allows dependence between cost and effectiveness using copulas in cost-effectiveness analysis. The model was applied with sample of adults from the NHANES I Epidemiologic Follow-up Study, assuming a lognormal distribution for cost and a Weibull distribution for effectiveness as the marginals. Cost-effectiveness analysis is conducted for two types of patients using the estimated posterior densities of parameters regarding the hypothetical intervention for hypertension. A simulation based on Bayesian predictive densities is also performed to analyze cost and effectiveness at an individual patient level. The empirical result indicated a negative dependence between measures of effectiveness and cost. The second chapter conducts a Bayesian analysis of discrete-time asset pricing model. The chapter particularly discusses the naive discretization problem, which arises from using discrete-time data to estimate continuous-time models. Our results using generated data showed that the naive discretization would not work well when data generating process is unknown, when the data is sampled at low frequency, and averaged data is used. The final chapter develops a Bayesian analysis of a short-term interest rate model with stochastic volatility. The model was developed based on the CKLS model (Chan et al. 1992). We constructed MCMC algorithms suitable for the model based on the Jacquire, Polson and Rossi(1994) algorithm. The empirical results with the 3-month Treasury constant maturity rate suggested that there was high autocorrelation in volatility of the error terms. Finally, the developed model was compared with the model with a GARCH error, using Bayesian predictive densities. The predictive densities obtained by CKLS with stochastic volatility have wider variance than the ones from CKLS-GARCH, and the realized value did not fall in the support of the predicted values for the CKLS GARCH model because of the tight variance in prediction.Ph.D.Includes bibliographical references (p. 96-99)

An Analysis of Peer Effects on Vaccination Behavior Using a Model of Privately Provided Public Goods

Traditional economic models of vaccination behavior simply assume that agents free-ride on the vaccination decisions of others. We provide three different models of private provision of a public good, such as a joint production model and a conjectural variation model, to explain how a positive peer effect regarding vaccination behavior arises. We conduct two empirical studies using Japanese data in these models. The first empirical analysis, using a data set on the vaccination behavior of neighbors residing in the same block of a city, finds the existence of positive peer effects on individuals' vaccination decisions. The second empirical analysis also confirms that there are peer effects on the vaccination decisions of members of the same household using a dataset from the national survey we conduct

Socioeconomic disparities in risk perceptions and precautionary actions against COVID-19 among the working age population aged 18–59 in Japan: a cross-sectional study

Introduction Risk perceptions and precautionary actions against COVID-19 have been reported to be generally insufficient globally, and differences by subpopulation group have been concerning, as a key driver to widening health gaps. Although a body of literature examined these key constructs, critical comparative examinations of various risk perceptions and precautionary actions by socioeconomic group are still limited in Japan and Asia.Methods This study examines subjective and objective risk perceptions and precautionary actions against COVID-19 infection among the general working age population aged 18–59 in Japan, focusing on the differences by socioeconomic group and health status. A cross-sectional survey was conducted in March 2021, using an online self-reporting questionnaire, in selected prefectures in Japan where COVID-19 infection cases ranked the highest. Participants were randomly recruited, and quota sampling methods were employed with the weighting of the sample distribution by geographic location (n=2764).Results Subjective and objective risk perceptions and precautionary actions were significantly related to several of the socioeconomic variables, including gender, income, employment and household composition, as well as self-reported health status. These disparities were substantial even with the key basic preventive behaviour including mask wearing, avoidance of large gatherings and hand washing. Further, these risk perceptions and precautionary actions showed unexpected relationships with socioeconomic position and health status, contrary to existing evidence or theory, particularly among younger generations and worse health populations.Conclusions This evidence suggests that risk perceptions and precautionary actions do not always seem to align, and their disparities by socioeconomic group and health status have been underscored in Japan, which may suggest complex and distinct pathways by subpopulation group. Further evidence and strategies for COVID-19 and other infectious disease prevention would be critical in transitions of the infectious disease prevention and control strategy, targeting both the high-risk population group and higher risk-taking group

Mixing age and risk groups for accessing COVID-19 vaccines: a modelling study

Objective To characterise the optimal targeting of age and risk groups for COVID-19 vaccines.Design Motivated by policies in Japan and elsewhere, we consider rollouts that target a mix of age and risk groups when distributing the vaccines. We identify the optimal group mix for three policy objectives: reducing deaths, reducing cases and reducing severe cases.Setting Japan, a country where the rollout occurred over multiple stages targeting a mix of age and risk groups in each stage.Primary outcomes We use official statistics on COVID-19 deaths to quantify the virus transmission patterns in Japan. We then search over all possible group mix across rollout stages to identify the optimal strategies under different policy objectives and virus and vaccination conditions.Results Low-risk young adults can be targeted together with the high-risk population and the elderly to optimally reduce deaths, cases and severe cases under high virus transmissibility. Compared with targeting the elderly or the high-risk population only, applying optimal group mix can further reduce deaths and severe cases by over 60%. High-efficacy vaccines can mitigate the health loss under suboptimal targeting in the rollout.Conclusions Mixing age and risk groups outperforms targeting individual groups separately, and optimising the group mix can substantially increase the health benefits of vaccines. Additional policy measures boosting vaccine efficacy are necessary under outbreaks of transmissible variants