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High uptake of Covid-19 vaccination is required to reach herd immunity. A representative sample of 2,060 Belgians were surveyed in October 2020. Regression analyses identified the predictors associated with willingness to get vaccinated against Covid-19, and attitudes toward vaccination in general. 34% of the participants reported that they will definitely get vaccinated against Covid-19 and 39% that they would “probably”. Intended uptake was strongly associated with age, opinion on the government’s dealing with the Covid-19 pandemic, medical risk, spoken language, gender, and to a lesser extent with having known someone who was hospitalised because of Covid-19. Similar predictors were identified for attitudes to vaccination in general. Covid-19 vaccine hesitancy was more marked in age groups below 54 years old. We further analysed a sample of 17% (N = 349) found favourable to vaccination in general but not willing to be vaccinated against Covid-19. They were mainly female, young, French speaking, slightly less educated, working, and did not belong to a Covid-19 risk group. They were very dissatisfied with the government’s dealing with the pandemic, and did not know someone who was hospitalised because of Covid-19. Vaccine hesitancy was higher for Covid-19 vaccines than for other vaccines. The part of the population being convinced of the utility of vaccination in general but hesitant about the Covid-19 vaccine is a primary interest group for tailored communication campaigns in order to reach the vaccine coverage needed for herd immunity.

In 1919 and 1921 Raymond Pearl published four empirical studies on the Spanish Flu epidemic in which he explored the factors that might explain the explosiveness and destructiveness of the epidemic in America’s largest cities. Using partial correlation coefficients he tried to isolate the net effects of the possible explanatory factors, such as general demographic characteristics of the cities and death rates for various diseases, on the variables measuring the severity of the epidemic. Instead of Pearl’s correlation analysis, we apply a bootstrap simulation to forward variable selection with a null factor for generalized linear regression with AICc validation. The null factor or pseudo-variable is a random variable that is independent of the response. The number of times it is included in the model selection simulation provides an important metric for deciding which terms should remain in the model. Our results are largely consistent with Pearl’s conclusions in that the pre-pandemic death rates from organic heart disease and from all causes are most predictive of pandemic explosiveness or severity. However, our results also contain substantive nuances. Our paper contributes to the literature showing that state-of-the-art methodology for variable selection proves useful for historical epidemiology.

Background To optimize the focus of future public information campaigns in The Netherlands promoting the uptake of vaccines among adults and children, we quantified the contribution of several attributes to the vaccination decision. Method We performed a discrete choice experiment (DCE) among Dutch adults including six attributes, i.e. vaccine effectiveness, vaccine-preventable burden of disease (specified in severity and frequency), accessibility of vaccination in terms of co-payment and prescription requirements, frequency of mild side-effects, population-level vaccination coverage and local vaccination coverage among family and friends. Participants answered the DCE from their own perspective (‘oneself’ group) or with regard to a vaccine decision for their youngest child (‘child’ group). The data was analysed by means of panel mixed logit models. Results We included 1547 adult participants (825 ‘oneself’ and 722 ‘child’). Vaccine effectiveness was the most important attribute in the ‘oneself’ group, followed by burden of disease (relative importance (RI) 78%) and accessibility (RI 76%). In the ‘child’ group, burden of disease was most important, but tied closely with vaccine effectiveness (RI 97%). Of less importance was the risk of mild vaccine-related side-effects and both population and local vaccination coverage. Interestingly, participants were more willing to vaccinate when uptake among the population or family and friends was high, indicating that social influence and social norms plays a role. Conclusions Vaccine effectiveness and disease severity are key attributes in vaccination decision-making for adults making a decision for themselves and for parents who decide for their children. Hence, public information campaigns for both adult and child vaccination should primarily focus on these two attributes. In addition, reinforcing social norms may be considered.

Background Several studies have confirmed the existence of a significant positive relationship between income and health. Conventional regression techniques such as Ordinary Least Squares only help identify the effect of the covariates on the mean of the health variable. In this way, important information of the income-health relationship could be overlooked. As an alternative, we apply and compare unconventional regression techniques. Methods We adopt a distributional approach because we want to allow the effect of income on health to vary according to people’s health status. We start by analysing the income-health relationship using a distributional regression model that falls into the GAMLSS (Generalized Additive Models for Location, Scale and Shape) framework. We assume a gamma distribution to model the health variable and specify the parameters of this distribution as linear functions of a set of explanatory variables. For comparison, we also adopt a quantile regression analysis. Based on predicted health quantiles, we use both a parametric and a non-parametric approach to estimate the lower tail of the health distribution. Results Our data come from Wave 13 of the Household, Income and Labour Dynamics in Australia (HILDA) survey, collected in 2013-2014. According to GAMLSS, we find that the risk of ending up in poor, fair or average health is lower for those who have relatively high incomes ($80,000) than for those who have relatively low incomes ($20,000), for both smokers and non-smokers. In relative terms, the risk-lowering effect of income appears to be the largest for those who are in poor health, again for both smokers and non-smokers. The results obtained on the basis of quantile regression are to a large extent comparable to those obtained by means of GAMLSS regression. Conclusions Both distributional regression techniques point in the direction of a non-uniform effect of income on health, and are therefore promising complements to conventional regression techniques as far as the analysis of the income-health relationship is concerned.

To date, no attempt has been made to design efficient choice experiments by means of the G- and V-optimality criteria. These criteria are known to make precise response predictions, which is exactly what choice experiments aim to do. In this article, the authors elaborate on the G- and V-optimality criteria for the multinomial logit model and compare their prediction performances with those of the D- and A-optimality criteria. They make use of Bayesian design methods that integrate the optimality criteria over a prior distribution of likely parameter values. They employ a modified Fedorov algorithm to generate the optimal choice designs. They also discuss other aspects of the designs, such as level overlap, utility balance, estimation performance, and computational effectiveness.

We examine the effects of receiving remittances on household saving behaviour and expenditure patterns in Vietnam. We consider the amount of saving, the saving rate, and the share of expenditure, as well as per capita expenditure on education, health, assets, house repairs, food, non-food, and utilities. We apply propensity score matching to data from the Vietnam Household Living Standard Survey (VHLSS) of 2012. We find that remittances have a positive impact on household savings and increase both the amount of saving and the saving rate. As far as expenditure patterns are concerned, our results indicate that receiving households spend more on health, assets, and house repairs, and less on food. This finding suggests that households tend to use remittances productively, with receiving households increasing their investments in human and physical capital. For the economy as a whole, remittances can create more opportunities for the development of services provided by banks, financial institutions, hospitals and healthcare centres, and give incentives to the production of building materials and tangible assets.

Increased vaccine hesitancy and refusal negatively affects vaccine uptake, leading to the reemergence of vaccine preventable diseases. We aim to quantify the relative importance of factors people consider when making vaccine decisions for themselves, or for their child, with specific attention for underlying motives arising from context, such as required effort (accessibility) and opportunism (free riding on herd immunity). We documented attitudes towards vaccination and performed a discrete choice experiment in 4802 respondents in The United Kingdom, France and Belgium, eliciting preferences for six attributes: (1) vaccine effectiveness, (2) vaccine preventable disease burden, (3) vaccine accessibility in terms of copayment, vaccinator and administrative requirements, (4) frequency of mild vaccine-related side-effects, (5) vaccination coverage in the country’s population and (6) local vaccination coverage in personal networks. We distinguished adults deciding on vaccination for themselves from parents deciding for their youngest child. While all attributes were found to be significant, vaccine effectiveness and accessibility stood out in all (sub)samples, followed by vaccine preventable disease burden. We confirmed that people attach more value to severity of disease compared to its frequency, and discovered that peer influence dominates free-rider motives, especially for the vaccination of children. These behavioral data are insightful for policy and are essential to parameterize dynamic vaccination behavior in simulation models. In contrast to what most game theoretical models assume, social norms dominate free-rider incentives. Policy-makers and healthcare workers should actively communicate on high vaccination coverage, and draw attention to the effectiveness of vaccines while optimizing their practical accessibility.

In addition to more narrow criteria such as safety, effectiveness and cost-effectiveness, vaccines can also be evaluated based on broader criteria such as their economic impact, contribution to disease eradication objectives, caregiver aspects, financial protection offered, equity or social acceptability. We summarize a survey executed in a sample of the population (n = 1000) in Flanders, Belgium, in which we investigated support for using these broader criteria to evaluate vaccines for funding decisions. By means of both favourable and unfavourable framings of a hypothetical vaccine across 40 value dimensions, we find support for the view that people indeed consider a broad range of medical and socio-economic criteria relevant. Several of these are not incorporated in standard evaluation frameworks for vaccines. The different results we find for different framings highlight the importance of developing a consistent a priori value framework for vaccine evaluation, rather than evaluating vaccines on an ad hoc basis.

While Bayesian - and -optimal designs for the multinomial logit model have been shown to have better predictive performance than Bayesian - and -optimal designs, the algorithms for generating them have been too slow for commercial use. In this article, we present a much faster algorithm for generating Bayesian optimal designs for all four criteria while simultaneously improving the statistical efficiency of the designs. We also show how to augment a choice design allowing for correlated parameter estimates using a sports club membership study.

We suggest an alternative way to construct a family of indices of socioeconomic inequality of health. Our indices belong to the broad category of linear indices. In contrast to rank-dependent indices, which are defined in terms of the ranks of the socioeconomic variable and the levels of the health variable, our indices are based on the levels of both the socioeconomic and the health variable. We also indicate how the indices can be modified in order to introduce sensitivity to inequality in the socioeconomic distribution and to inequality in the health distribution. As an empirical illustration, we make a comparative study of the relation between income and well-being in 16 European countries using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 4.