Education versus anti-vaxxers: evidence from Europe

Vaccine skepticism and hesitancy – the distrust and skepticism that some members of the public feel for vaccines, as well as for institutions that deliver and encourage vaccination – has emerged as a major threat to world health. Vaccine skepticism is not limited to any particular place; it has been observed across a range of countries, cultures, and levels of prosperity. Vaccine skeptics have made themselves known in Hollywood, led protests in Washington D.C., and lashed out violently against vaccination in Pakistan and Northern Nigeria. Vaccine skepticism has truly gone global.

Vaccine skepticism comes at odds with the proven benefits that vaccines have brought to humanity. The widespread adoption and use of vaccines and antibiotics led to sharp declines in the incidence of, and mortality caused by, infectious diseases. Except for the 1918 global flu epidemic, infectious disease mortality in the United States fell linearly before plateauing in the 1950s, at under one-tenth of the rate seen in 1900.

Vacine hesitancy threatens to reverse years of progress towards reducing measles deaths and ultimately eliminating measles as a threat, as immunization levels in many communities are at or below the 95% level required for herd immunity. In fact, the World Health Organization has seen more cases reported in the first half of 2019 than in any year since 2006. It is clearly time to reappraise vaccine policies and programs.

The role of education

Many people may find it difficult to understand and assess risks and benefits of vaccination, especially in the presence of Wakefield’s fraudulent argument that the MMR vaccine causes autism, while vaccines have been so successful that more people have seen autism than the diseases targeted by the vaccines.

Since one might hope that education can provide both the facts needed to make intelligent decisions about vaccination and the ability to reason, we ask here what is the relation between education and vaccine skepticism.

We use 2017 education data from the United Nations Development Program Human Development Reports, and data on vaccination attitudes from the Vaccine Confidence Project, published in 2016. These data include 28 European countries, with wide ranges in the prevalence of vaccine skepticism (13.5% in the median country did not agree that vaccines were safe, with a range from 4.2% in Portugal, to 51% in France) and years of education (16.4 in the median country, with a range from 12.7 in Azerbaijan to 19.8 in Belgium).

We found a weak (R2 = 0.1847) but statistically significant (p = 0.022) inverse relationship between education level and vaccine skepticism: by country vaccine skepticism decreased by about 2% for each additional year of education.

The relationship between years of schooling and vaccine skepticism, by country.

However, there are significant outliers, consistent with the low coefficient of correlation. For example, among the least educated countries, vaccine skepticism in Bosnia and Herzegovina is 36%, compared with 13% in the less educated Azerbaijan. Vaccine skepticism is 51% in France but 4.2% in Portugal, again despite similar educational levels (16.3 years in Portugal, 16.4 in France). Among the most educated countries, vaccine skepticism was 5.5% in Israel but 14% in the more educated Belgium.

Questions for research

It is clearly important to understand the cultural and other reasons behind the outliers in these data, in order to address the health challenge of vaccine skepticism. Here we offer some speculations and questions for further study.

The European countries with the best systems of education are generally those that were the first to industrialize, reach developed status, and adopt nationwide vaccination programs. As such, their present populations may be very historically removed from the infectious diseases that once plagued the European continent. As such, people in these countries may be less appreciative of the difference that vaccines have made, and more likely to be influenced by anti-vaccine messages.

Another factor to consider may be the politicization of anti-vaccine attitudes. It is possible that vaccine skepticism has become more prevalent simply because more people subscribe to political ideologies that are distrustful of the medical establishment and, more generally, institutions typically associated with their governments. France is again one such country where people are increasingly doubtful of their political institutions and are therefore wary of completely trusting ideas promoted by their government. This is more apparent than ever with the recent yellow vest protests seen across the country.

Distrust is often rooted in real instances of the abuse of public trust by, as well as the failure of, institutions, such as the Tuskegee syphilis trials, the Thalidomide birth defect crisis of the 50s and 60s, as well as unethical pharmaceutical trials that modern drug companies have carried out in developing countries, such the meningitis antibiotic trials that Pfizer carried out in Northern Nigeria during the mid 1990s. Vaccine skeptics have also lobbied for religious exemptions to be upheld in places that were considering their removal due to the resurgence of certain diseases like measles.

A study conducted in Romania concluded that unfavorable information spread by the media regarding vaccines was the lead cause in increasing vaccine skepticism in the country. With one third of the population being skeptical about vaccines, politicians and the reputation of the pharmaceutical industry were also named as reasons people feared vaccines.

In some countries, such as Greece and Romania, medical professionals have often been found to be skeptical of vaccines themselves. These health care workers have expressed concerns regarding the guilt they would feel if patients were to experience negative side effects after receiving vaccines, claiming that certain hepatitis and HPV vaccines have been banned in other countries due to fears of patients developing tumors and autism. These claims are reminiscent of Wakefield’s false and damaging claims that the MMR vaccine caused autism.

Residents of former Yugoslav countries, such as Bosnia and Herzegovina, have attributed lack of vaccine confidence to a discomfort with the relationship between physicians and patients. By evoking the times when the practice of immunization went unquestioned, physicians appear to be advocating the reestablishment of the authoritative power relationship between physicians and patients under socialism.

Given the well-documented strong evidence of the benefits of vaccines, we are left with a communication challenge – how to communicate key scientific facts needed for intelligent decision-making in a respectful, non-threating, non-condescending way.

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Chris Sampson’s journal round-up for 6th January 2020

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Child sleep and mother labour market outcomes. Journal of Health Economics [PubMed] [RePEc] Published January 2020

It’s pretty clear that sleep is important to almost all aspects of our lives and our well-being. So it is perhaps surprising that economists have paid relatively little attention to the ways in which the quality of sleep influences the ‘economic’ aspects of our lives. Part of the explanation might be that almost anything that you can imagine having an effect on your sleep is also likely to be affected by your sleep. Identifying causality is a challenge. This paper shows us how it’s done.

The study is focussed on the relationship between sleep and labour market outcomes in new mothers. There’s good reason to care about new mothers’ sleep because many new mothers report that lack of sleep is a problem and many suffer from mental and physical health problems that might relate to this. But the major benefit to this study is that the context provides a very nice instrument to help identify causality – children’s sleep. The study uses data from the Avon Longitudinal Study of Parents and Children (ALSPAC), which seems like an impressive data set. The study recruited 14,541 pregnant women with due dates between 1991 and 1993, collecting data on mothers’ and children’s sleep quality and mothers’ labour market activity. The authors demonstrate that children’s sleep (in terms of duration and disturbances) affects the amount of sleep that mothers get. No surprise there. They then demonstrate that the amount of sleep that mothers get affects their labour market outcomes, in terms of their likelihood of being in employment, the number of hours they work, and household income. The authors also demonstrate that children’s sleep quality does not have a direct impact on mothers’ labour market outcomes except through its effect on mothers’ sleep. The causal mechanism seems difficult to refute.

Using a two-stage least squares model with a child’s sleep as an instrument for their mother’s sleep, the authors estimate the effect of mothers’ sleep on labour market outcomes. On average, a 30-minute increase in a mother’s sleep duration increases the number of hours she works by 8.3% and increases household income by 3.1%. But the study goes further (much further) by identifying the potential mechanisms for this effect, with numerous exploratory analyses. Less sleep makes mothers more likely to self-report having problems at work. It also makes mothers less likely to work full-time. Going even further, the authors test the impact of the UK Employment Rights Act 1996, which gave mothers the right to request flexible working. The effect of the Act was to reduce the impact of mothers’ sleep duration on labour market outcomes, with a 6 percentage points lower probability that mothers drop out of the labour force.

My only criticism of this paper is that the copy-editing is pretty poor! There are so many things in this study that are interesting in their own right but also signal need for further research. Unsurprisingly, the study identifies gender inequalities. No wonder men’s wages increase while women’s plateau. Personally, I don’t much care about labour market outcomes except insofar as they affect individuals’ well-being. Thanks to the impressive data set, the study can also show that the impact on women’s labour market outcomes is not simply a response to changing priorities with respect to work, implying that it is actually a problem. The study provides a lot of food for thought for policy-makers.

Health years in total: a new health objective function for cost-effectiveness analysis. Value in Health Published 23rd December 2019

It’s common for me to complain about papers on this blog, usually in relation to one of my (many) pet peeves. This paper is in a different category. It’s dangerous. I’m angry.

The authors introduce the concept of ‘health years in total’. It’s a simple idea that involves separating the QA and the LY parts of the QALY in order to make quality of life and life years additive instead of multiplicative. This creates the possibility of attaching value to life years over and above their value in terms of the quality of life that is experienced in them. ‘Health years’ can be generated at a rate of two per year because each life year is worth 1 and that 1 is added to what the authors call a ‘modified QALY’. This ‘modified QALY’ is based on the supposition that the number of life years in its estimation corresponds to the maximum number of life years available under any treatment scenario being considered. So, if treatment A provides 2 life years and treatment B provides 3 life years, you multiply the quality of life value of treatment A by 3 years and then add the number of actual life years (i.e. 2). On the face of it, this is as stupid as it sounds.

So why do it? Well, some people don’t like QALYs. A cabal of organisations, supposedly representing patients, has sought to undermine the use of cost-effectiveness analysis. For whatever reason, they have decided to pursue the argument that the QALY discriminates against people with disabilities, or anybody else who happens to be unwell. Depending on the scenario this is either untrue or patently desirable. But the authors of this paper seem happy to entertain the cabal. The foundation for the development of the ‘health years in total’ framework is explicitly based in the equity arguments forwarded by these groups. It’s designed to be a more meaningful alternative to the ‘equal value of life’ measure; a measure that has been used in the US context, which adds a value of 1 to life years regardless of their quality.

The paper does a nice job of illustrating the ‘health years in total’ approach compared with the QALY approach and the ‘equal value of life’ approach. There’s merit in considering alternatives to the QALY model, and there may be value in an ‘additive’ approach that in some way separates the valuation of life years from the valuation of health states. There may even be some ethical justification for the ‘health years in total’ framework. But, if there is, it isn’t provided by this paper. To frame the QALY as discriminatory in the way that the authors do, describing this feature as a ‘limitation’ of the QALY approach, and to present an alternative with no basis in ethics is, at best, foolish. In practice, the ‘health years in total’ calculation would favour life-extending treatments over those that improve health. There are some organisations with vested interests in this. Expect to see ‘health years in total’ obscuring decision-making in the United States in the near future.

The causal effect of education on chronic health conditions in the UK. Journal of Health Economics Published 23rd December 2019

Since the dawn of health economics, researchers have been interested in the ways in which education and health outcomes depend on one another. People with more education tend to be healthier. But identifying causal relationships in this context is almost impossible. Some studies have claimed that education has a positive (causal) effect on both general and specific health outcomes. But there are just as many studies that show no impact. This study attempts to solve the problem by throwing a lot of data at it.

The authors analyse the impact of two sets of reforms in the UK. First, the raising of the school leaving age in 1972, from 15 to 16 years. Second, the broader set of reforms that were implemented in the 1990s that resulted in a major increase in the number of people entering higher education. The study’s weapon is the Quarterly Labour Force Survey (QLFS), which includes over 5 million observations from 1.5 million people. Part of the challenge of identifying the impact of education on health outcomes is that the effects can be expected to be observed over the long-term and can therefore be obscured by other long-term trends. To address this, the authors limit their analyses to people in narrow age ranges in correspondence with the times of the reforms. Thanks to the size of the data set, they still have more than 350,000 observations for each reform. The QLFS asks people to self-report having any of a set of 17 different chronic health conditions. These can be grouped in a variety of ways, or looked at individually. The analysis uses a regression discontinuity framework to test the impact of raising the school leaving age, with birth date acting as an instrument for the number of years spent in education. The analysis of the second reform is less precise, as there is no single discontinuity, so the model identifies variation between the relevant cohorts over the period. The models are used to test a variety of combinations of the chronic condition indicators.

In short, the study finds that education does not seem to have a causal effect on health, in terms of the number of chronic conditions or the probability of having any chronic condition. But, even with their massive data set, the authors cannot exclude the possibility that education does have an effect on health (whether positive or negative). This non-finding is consistent across both reforms and is robust to various specifications. There is one potentially important exception to this. Diabetes. Looking at the school leaving age reform, an additional year of schooling reduces the likelihood of having diabetes by 3.6 percentage points. Given the potential for diabetes to depend heavily on an individual’s behaviour and choices, this seems to make sense. Kids, stay in school. Just don’t do it for the good of your health.

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Rita Faria’s journal round-up for 30th December 2019

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Value in hepatitis C virus treatment: a patient-centered cost-effectiveness analysis. PharmacoEconomics [PubMed] Published 2nd December 2019

There have been many economic evaluations of treatments for viral hepatitis C. The usual outcomes are costs and a measure of quality-adjusted survival, such as QALYs. But health-related quality of life and life expectancy may not be the only important outcomes for patients. This fascinating paper by Joe Mattingly II and colleagues fills in the gap by collaborating with patients in the development of an economic evaluation of treatments for viral hepatitis C.

Patient engagement was guided by a stakeholder advisory board including health care professionals, four patients and a representative of a national patient advocacy organisation. This board reviewed the model design, model inputs and presentation of results. To ensure that the economic evaluation included what is important to patients, the team conducted a Delphi process with patients who had received treatment or were considering treatment. This is reported in a separate paper.

The feedback from patients led to the inclusion of two outcomes beyond QALYs and costs: infected life-years, which relate to the patient’s fear of infecting others, and workdays missed, which relate to financial issues and impact on work and career.

I was impressed with the effort put into engaging with patients and stakeholders. For example, there were 11 meetings with the stakeholder advisory board. This shows that engaging with stakeholders takes time and energy to do right! The challenge with the patient-centric outcome measures is in using them to make decisions. From an individual or an employer’s perspective, it may be useful to have results in terms of costs per workday missed avoided, for example, if these can then be compared to a maximum acceptable cost. As suggested by the authors, an interesting next step would be to seek feedback from managed care organisations. Whether such measures would be useful to inform decisions in publicly funded healthcare services is less clear.

Patient engagement is all the rage at present, but there’s not much guidance on how to do it in practice. This paper is a great example of how to go about it.

TECH-VER: a verification checklist to reduce errors in models and improve their credibility. PharmacoEconomics [PubMed] [RePEc] Published 8th November 2019

Looking for help in checking your decision model? Fear not, there’s a new tool on the block! The TECH-VER checklist lists a set of steps to assess the internal validity of your model.

I have to admit that I’m getting a bit weary of checklists, but this one is truly useful. It’s divided into five areas: model inputs, event/state calculations, results, uncertainty analysis, and overall validation and other supplementary checks. Each area includes an assessment of the completeness of the calculations in the electronic model, their consistency with the technical report, and then steps to check their correctness.

Correctness is assessed with a series of black-box, white-box, and replication-based tests. Black-box tests involve changing parameters in the model and checking if the results change as expected. For example, if the HRQOL weights=1 and decrements=0, the QALYs should be the same as the life years. White-box testing involves checking the calculations one by one. Replication-based tests involve redoing calculations independently.

The authors’ handy tip is to apply the checks in ascending order of effort and time: starting first with black-box tests, then conducting white-box tests only for priority calculations or if there are unexpected results. I recommend this paper to all cost-effectiveness modellers. TECH-VER will definitely feature in my toolbox!

Proposals on Kaplan-Meier plots in medical research and a survey of stakeholder views: KMunicate. BMJ Open [PubMed] Published 30th September 2019

What’s your view of the Kaplan-Meier plot? I find it quite difficult to explain to non-specialist audiences, particularly the uncertainty in the differences in survival time between treatment groups. It seems that I’m not the only one!

Tim Morris and colleagues agree that Kaplan-Meier can be difficult to interpret. To address this, they proposed improvements to better show the status of patients over time and the uncertainty around those estimates. They then assessed the proposed improvements with a survey of researchers. Similar to my own views, the majority of respondents preferred having a table with the number of patients who had the events and who were censored to show the status of patients over time, and confidence intervals to show the uncertainty.

The Kaplan-Meier plot with confidence intervals and the table would definitely help me to interpret and explain Kaplan-Meier plots. Also, the proposed improvements seem to be straightforward to implement. One way to make it easy for researchers to implement these plots in practice would be to publish the code to replicate the preferred plots.

There is a broader question, outside the scope of this project, about how to convey survival times and their uncertainty to untrained audiences, from health care professionals and managers to patients. Would audience-specific tools be the answer? Or should we try to up-skill the audience to understand a Kaplan-Meier plot?

Better communication is surely key if we want to engage stakeholders with research and if our research is to have an impact on policy. I, for one, would be grateful for more guidance on how to communicate research. This study is an excellent first step in making a specialist tool – the Kaplan-Meier plot – easier to understand.

Cost-effectiveness of strategies preventing late-onset infection in preterm infants. Archives of Disease in Childhood [PubMed] Published 13th December 2019

And lastly, a plug for my own paper! This article reports the cost-effectiveness analysis conducted for a ‘negative’ trial. The PREVAIL trial found that the experimental intervention – anti-microbial impregnated peripherally inserted central catheters (AM-PICCs) – had no effect compared to the standard PICCS, which are used in the NHS. AM-PICCs are more costly than standard PICCs. Clearly, AM-PICCs are not cost-effective. So, you may ask, why conduct a cost-effectiveness analysis and develop a new model?

Developing a model to evaluate the cost-effectiveness of AM-PICCs was one of the project’s objectives. We started the economic work pretty early on. By the time that the trial reported, the model was already built, tested with data from the literature, and all ready to receive the trial data. Wasted effort? Not at all!

Thanks to this cost-effectiveness analysis, we have concluded that avoiding neurodevelopmental impairment in children born preterm is very beneficial; hence warranting a large investment by the NHS. If we believe the observational evidence that infection causes neurodevelopmental impairment, interventions that reduce the risk of infection can be cost-effective.

The linkage to Hospital Episode Statistics, National Neonatal Research Database and Paediatric Intensive Care Audit Network allowed us to get a good picture of the hospital care and costs of the babies in the PREVAIL trial. This informed some of the cost inputs in the cost-effectiveness model.

If you’re planning a cost-effectiveness analysis of strategies to prevent infections and/or neurodevelopmental impairment in preterm babies, do feel free to get in touch!

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