Thesis Thursday: Koh Jun Ong

On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Koh Jun Ong who has a PhD from the University of Groningen. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Title
Economic aspects of public health programmes for infectious disease control: studies on human immunodeficiency virus & human papillomavirus
Supervisors
Maarten Postma, Mark Jit
Repository link
http://hdl.handle.net/11370/0edbcfae-2a0c-4103-9722-fb8086d75cff

Which public health programmes did you consider in your research?

Three public health programmes were considered in the thesis: 1) HIV Pre-Exposure Prophylaxis (PrEP), 2) Human Papillomavirus (HPV) vaccination, and 3) HIV screening to reduce undiagnosed infections in the population.

The first two of the three involved primary infectious disease prevention among men who have sex with men (MSM), and both of these programmes were to be delivered via sexual health clinics in England (commonly known as genitourinary medicine, GUM, clinics).

The third public health infectious disease control programme involved secondary prevention of onward HIV transmission in the general population by encouraging routine HIV screening to reduce undiagnosed HIV, with a view of earlier diagnosis leading to antiretroviral treatment initiation, which will stop HIV transmission with viral suppression.

Was it necessary to develop complex mathematical models?

It depends on the policy research question. A dynamic model was used for the HPV vaccination research question, which captures the ecological externality that vaccination provides by reducing transmission to non-vaccinees. A dynamic model was used because this programme would likely reach a high proportion of MSM who attend GUM clinics in England, and therefore the subsequent knock-on impact of disease transmission in the population was likely to be substantial.

The policy research question was different for PrEP and a static model was more suitable since the objective was to advise NHS England on whether and how such a programme, with relatively small numbers of patients over an initial time-limited period, may represent value for money in England. We first considered a public health control programme, with promising new efficacy data from the 500-person PrEP pilot study (the UK-based PROUD trial) and additional information from per protocol participants in the earlier iPrEx study. The initial consideration was to maintain the preventative effect of a drug that needs to be taken on a daily basis (compared with near one-off HPV vaccination – three doses in total delivered within a year’s time). Regular monitoring of STI and patient’s renal function meant there were clinical service capacity issue to consider, which was likely to limit access initially. Thus, a static model that did not take into account transmission was used.

However, dynamic modelling would be useful to inform policy decisions as PrEP usage expands. Firstly, because it would then be important to capture the indirect effect on infection transmission. Secondly, because when the force of infection begins to fall as incidence declines, dynamic modelling will inform future delivery of a programme that maintains its value. These represent important areas for future research.

Finally, the model designed for the research question on HIV screening was quite straightforward as its aim is primarily to advise local commissioners on financial implications of offering routine screening in their local area, which is dependent on local clinical resources and local disease prevalence.

Did you draw any important conclusions from your literature reviews?

Two literature reviews were conducted: 1) a review on economic parameters i.e. cost and utility estimates for HPV-related outcomes, and 2) a review on published MSM HPV vaccination economic evaluations.

In relation to the first review, most economic models of HPV-related interventions selected economic parameters in a pretty ad hoc way, without reviewing the entirety of the literature. We found substantial variations in cost and utility estimates for all diseases considered in our systematic review, wherever there were more than one publication. These variations in value estimates could result from the differences in cancer site, disease stages, study population, treatment pathway/settings, treatment country and utility elicitation methods used. It would be important for future models to be transparent about parameter sources and assumptions, and to recognise that as patient disease management changes over time, there will be corresponding effects on both cost and utility, necessitating future updates to the estimates. These must be considered when applied to future economic evaluations, to ensure that assumptions are up-to-date and closely reflect the case mix of patients being evaluated.

In relation to the second review, despite limited models, different modelling approaches and assumptions, a general theme from these studies reveal modelling outcomes to be most sensitive to assumptions around vaccine efficacy and price. Future studies could consider synchronising parameter assumptions to test outputs generated by different models.

What can your research tell us about the ‘cost-effective but unaffordable’ paradox?

A key finding and concluding remark of this thesis was that “findings around cost-effectiveness should not be considered independently of budget impact and affordability considerations, as the two are interlinked”. Ultimately, cost-effectiveness is linked to the budget and, in an ideal world, a cost-effectiveness threshold should correspond to the opportunity cost of replacing least cost-effective care at the margin of the whole healthcare budget spend. This willingness to pay threshold should be linked to the amount of budgetary resources an intervention displaces. After all, the concept of opportunity cost in a fixed budget setting means that decisions to invest in something translates to funding being displaced elsewhere.

Since most health economies do not have unlimited resources, even if investment in a new intervention gives high returns and therefore is worthwhile from a value for money perspective, without the necessary resources it cannot always be afforded despite its high return on investment. Having a limited budget means that funding an expensive new intervention may mean moving funding away from existing services, which may be more cost-effective than the new intervention. Hence, the services from which funds are moved from will lose out, and this may leave society worse-off.

A simple analogy may be that buying a property that guarantees return over a defined period is worthwhile, but if I cannot afford it in the first place, is this still an option?

This was clearly demonstrated in the PrEP example, where despite potential to be cost-effective, the high cost of the intervention at list price carried with it a very high budget impact. The size of the population needed to be given PrEP to achieve substantial public health benefits is large, which meant that a public health programme could pose an affordability challenge to the national health care system.

Based on your findings, how might HIV and HPV prevention strategies be made more cost-effective?

Two strategies could influence cost effectiveness: optimizing the population covered and using an appropriate comparator price.

The most obvious way to improve cost-effectiveness is to optimise the population covered. For example, we know that HIV risk, as measured by HIV incidence, is higher among GUM-attending MSM. Therefore, delivering a PrEP programme to this population (at least in the initial phase until the intervention becomes more affordable) will likely result in a higher number of new HIV infections prevented. Similarly, HIV screening offered to areas with high local prevalence would likely give a higher number of new diagnoses.

The other important factor to consider around cost-effectiveness is the comparator price on which the technology appraisal is based. In the chapter on estimating HIV care cost in England, we demonstrated that with imminent availability of generic antiretrovirals, the lifetime care cost for a person living with HIV will reduce substantially. This reduced cost, representing cost of care with existing intervention, should be used as comparator for newer HIV interventions, as they would represent what society will be paying in the absence of the new interventions, allowing corresponding reduced price expectations for new interventions to ensure cost-effectiveness is maintained.

How did you find the experience of completing your thesis by publication?

It was brilliant! I must acknowledge all the contributions from my supervisors and co-authors in making this possible and for the very positive experience of this process. A major advantage of doing a PhD by publication is that the work conducted was regularly peer-reviewed, hence providing an extra check of the robustness of the analyses. And also the fact that these works are out for public consumption almost immediately, making the science available for other researchers to consider and to move the science to the next stage.

Thesis Thursday: Caroline Chuard

On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Caroline Chuard who has a PhD from the University of Zurich. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Title
Three essays on the health effects of family policies
Supervisors
Hannes Schwandt, Josef Zweimüller
Repository link
https://www.zora.uzh.ch/id/eprint/172853/

Is there a strong health economics evidence base on family policies?

The literature on parental leave and family health is relatively young. This literature emphasises that the returns depend on several key features. First, the timing of measurement matters. Therefore, the effects differ according to whether they are measured in the short- versus long-run. Second, the initial level of parental leave and the extent to which parental leave is increased are both key influencing factors. As such, an introduction is more beneficial than an increase at an already generous level of parental leave. Third, the results depend on the targeted group.

But keep in mind that the effects of family policies on health outcomes are just one part of a large literature that studies the effect on other outcomes such as maternal labour market outcomes, fertility, and child cognitive and non-cognitive development (e.g. Ruhm (2000), Lalive and Zweimüller (2009), Baker and Milligan (2008), Dustmann and Schönberg (2012), Lalive et al. (2014), Carneiro et al. (2015), Dahl et al. (2016), Danzer and Lavy (2018), Butikofer et al. (2018) and many more which have recently been reviewed by Olivetti and Petrongolo (2017) and Rossin-Slater (2018)).

What policy changes were you able to evaluate in your research?

I exploit two types of family policy changes in two countries. On the one hand, I use three changes in parental leave duration in Austria and, on the other hand, I use cantonal variation in family allowances across Switzerland.

More specifically, Austria increased parental leave by 1 year to 2 years in July 1990. This was partially reversed again in July 1996, by exclusively reserving 6 months to fathers so that maternal leave was essentially reduced to 1.5 years. Finally, in July 2000, there was another large extension in paid parental leave by 1 year to 2.5 years. Enforcement of all these changes was very strict, changing from one day to another depending on giving birth in June or July. This sharp discontinuity allows me to employ a regression discontinuity design.

In the case of Switzerland, I analyse the impact of birth allowances (so-called baby bonuses) on fertility, newborn health and birth scheduling. I exploit a unique quasi-experimental setting of Switzerland’s family allowances system. In this system, cantons are free to choose whether they want to implement birth allowances and how much they want to pay. During the last 50 years, 11 cantons have introduced a baby bonus, all increase the amount paid thereafter, and two cantons even abolished the baby bonus after all. This gives rise to a lot of cantonal variation. Thus, I use a difference-in-differences setting where I can analyse both the introduction and the intensity of the treatment.

What were the key strengths of the data sets that you used?

For all my studies I rely on administrative data. Thus, I can use the universe of observations delivered with high quality, as both Austria and Switzerland have very reliable administrative data.

In the Austrian case, I can even combine several different data sets. Namely, I use the Austrian Social Security Database (ASSD), which covers the complete working history of every worker in Austria. The ASSD covers every birth of employed mothers and their actual duration of parental leave. I can link the ASSD to the Austrian Birth Register (ABR) recording newborn health outcomes and additional individual-level characteristics of the mother. Finally, for a part of Austria, I additionally merge the data to health outcomes recorded in the health insurance data. This data set records every outpatient doctor visit, prescribed medication, and hospital stays including diagnosis code.

All of this, together, gives a huge variety of different variables on an individual basis allowing me to study a broad set of outcomes (such as health outcomes next to the directly targeted labour market outcomes). Furthermore, the detailed level of information allows me to study the impact of labour market behaviour on two margins—the extensive margin of mothers who choose to work or not and the intensive margin of how much mothers choose to work. The richness of the data also makes it possible to analyse heterogeneous effects across mothers and by work environment.

Did the policies achieve what they were designed to achieve?

This is a little hard to tell from looking at my results only. For example, in Austria the initial increase of parental leave duration by 1 year was introduced so that fathers could take up to 6 months of the full duration. This policy reform was a result of parliamentary procedural requests which wanted to introduce paternal leave. Due to the flat benefit structure almost no fathers were taking up parental leave, which essentially resulted in an increase of maternal leave from 1 to 2 years and, ultimately, led to the second policy change by exclusively reserving 6 months out of the total 2 years for fathers.

However, what I want to mention here, note that I explicitly evaluated side effects. All three chapters of my dissertation highlight the importance of studying alternative and indirect outcome measures in addition to the direct measures targeted by policymakers.

For example, in the Swiss study, we only find little fertility effects, the directly targeted outcome measure of birth allowances, but a sizable and significant reduction in the stillbirth rate as well as a positive impact on birth weight. A policymaker, who would now only study fertility, would argue that birth allowances were expensive to implement with little to no result, which, however, does not capture the full story.

Is there heterogeneity in how family policy reforms affect families?

The answer depends on the person affected and the studied outcome. For example, the Austrian parental leave duration reform affects maternal work behaviour during pregnancy regardless of the mother’s socioeconomic background and the industry. This change in prenatal maternal work status doesn’t affect newborn health at all.

However, when I study the same reforms with respect to maternal health, there is substantial heterogeneity. The initial increase in leave length is especially good for low-wage and unmarried mothers. Reducing leave duration harms mothers with unhealthy babies, proxied by a preterm birth or low birth weight baby. Substantially increasing leave duration is, though, especially bad for maternal health of those mothers who already suffered from mental diseases pre-birth. Also, for the paper on the Swiss baby bonus, we find a more beneficial impact in the decline of stillbirths for low socioeconomic status mothers.

Based on your research, how would you design parental leave policies?

With my research, I tried to give a more complete picture on the impact of family policies by taking into account health outcomes which have vastly been neglected so far. Nevertheless, for a policy recommendation it is crucial to take the findings from the previous literature into account.

Firstly, introducing parental leave has generally been shown to be very beneficial for the cognitive development of children (Carneiro et al., 2015). Secondly, these returns are, however, quickly declining (Butikofer et al., 2018). In combination with my findings of no impact of working during pregnancy on child health and a negative impact of too long parental leave policies for maternal health (Chuard, 2018), I would clearly put the focus on mandatory leave in the first months of a newborn’s life. While this might seem obvious for many European countries, this is still not the case in the US. And even Europe might face the risk on the other end of the parental leave duration scale. Many European countries tend to expand leave rather generously both pre- and post-natal, which seems from my research not necessary (always keep in mind, these policies are extremely expensive) and could potentially even be harmful in the long-run.

Thesis Thursday: Luke Wilson

On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Luke Wilson who has a PhD from Lancaster University. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Title
Essays on the economics of alcohol and risky behaviours
Supervisors
Colin P. Green, Bruce Hollingsworth, Céu Caixeiro Mateus
Repository link
https://doi.org/10.17635/lancaster/thesis/636

What inspired your research and how did ‘attractiveness’ enter the picture?

Without trying to sound like I have a problem, I find the subject of alcohol fascinating. The history of it, how it is perceived in society, how our behaviours around it have changed over time, not to mention it tastes pretty damn good!

Our attitude to alcohol is fascinating and diverse. Over 6.5 million people have visited Munich in the last month alone to attend the world’s largest beer festival Oktoberfest, drinking more than 7.3 million litres of beer. However, 2020 will be the 100-year anniversary of the introduction of prohibition in the United States. Throughout history, alcohol consumption has been portrayed as both a positive and negative commodity in society.

For my thesis, I wanted to understand individuals’ current attitudes to drinking alcohol; whether they are affected by legal restrictions such as being constrained by the minimum legal drinking age of 18 in the UK, whether their attitudes have changed over their life course, and how alcohol fits among a wider variety of risky behaviours such as smoking and illicit drug use.

As for how did ‘attractiveness’ enter the picture, I was searching for datasets that allow for longitudinal analysis, as well as contain information on risky behaviours, and I stumbled upon the data that asked the interviewers to rate the attractiveness of the respondent. My first thought was what a barbaric question to ask, but I quickly realised that the question is used a lot in determining the ‘beauty premia’ in the labour market. However, nobody has examined how these ‘beauty premia’ might come into effect while still at school.

Are people perceived to be more attractive at an advantage or a disadvantage in this context?

The current literature provides a compelling view that there are sizeable labour market returns to attractiveness in the United States (Fletcher, 2009; Stinebrickener et al., 2019). What is not well understood, and where our research fits in, is how physical attractiveness influences earlier, consequential, decisions. The previous literature seeks to provide, in essence, the effect of attractiveness on labour market outcomes conditional on individual characteristics, both demographic and ‘pre-market’. However, attractiveness is also likely to change both the opportunities and costs of a variety of behaviours during adolescence.

Exploiting the interviewer variations in ratings of attractiveness, we found that attractiveness of adolescents has marked effects on a range of risky behaviours. For instance, more attractive teens are less likely to smoke than teens of average or than lower attractiveness teens. However, attractiveness is associated with higher teen alcohol consumption. Attractive females, in particular, are substantially more likely to have consumed alcohol in the past twelve months, than those of or below average attractiveness.

How did you model the role of the minimum legal drinking age in the UK?

I was highly unoriginal and estimated the effect of the minimum legal drinking age in the UK using a regression discontinuity design approach, like that of Carpenter and Dobkin (2009). I jest but it is one of the most effective ways to estimate a causal effect of a particular law/policy that is triggered by age, especially for the UK which has not changed its legal drinking age.

Where our research deviates is that we focus on the law itself and analyse how an individual’s consumption of alcohol in a particular school year may differ at the cut-off (aged 18). For example, do those born in September purchase alcohol for themselves and their younger friends or do we all adhere to the laws that govern us and wait patiently…

Are younger people drinking less, nowadays?

The short answer is yes! Evidence from multiple British surveys shows a consistent pattern over 10-15 years of reduced participation in drinking, reduced consumption levels among drinkers, reduced prevalence of drunkenness, and less positive attitudes towards alcohol in young adults aged 16 to 24.

Friends of mine at the University of Sheffield (Oldham et al., 2018) have sought to unravel the decline in youth drinking further and find evidence that younger drinkers are consuming alcohol less often and in smaller quantities. They find that, among those who were drinkers, the percentage of 16-24 year-olds who drank in the last week fell from 76% to 60% between 2002 and 2016, while for 11-15 year-olds it fell from 35% to 19%. Additionally, alongside declines in youth drinking, the proportion of young adults who had ever tried smoking fell from 43% in 1998 to 17% in 2016.

While we are witnessing this decline, the jury is still out as to why it is happening. Explanations so far include that increases in internet use (social media) and online gaming are changing the way young people spend their leisure time. Additionally, economic factors may play a role, such as the increase in the cost of alcohol, as well as the increase in tuition fees and housing costs meaning that young adults have less disposable income.

What were some of the key methodological challenges you faced in your research?

The largest methodological problem I faced throughout my PhD was finding suitable data to examine the effect of the minimum legal drinking age in the setting of the UK. One of the key underlying components in a regression discontinuity design is the running variable. The running variable I use is age in months of the respondents, which is calculated using the date in which the survey interview took place as well as the month and year of birth of the respondent. Unfortunately, due to issues with data being disclosive, it is very difficult to obtain data that have these variables as well as suitable questions regarding alcohol consumption. Luckily, the General Household Survey (Special Licence version) had the variables I needed to conduct the analysis, albeit only between 1998 and 2007.

How might your research inform policymakers seeking to discourage risky behaviours?

Definitely a difficult question to answer, especially given that one of my chapters uses interviewer variations in ratings of attractiveness of the respondents, so I have stayed well clear from drawing individual policy recommendations from that chapter. That said, these results are important for a number of interrelated reasons. Previous labour market research demonstrates marked effects of attractiveness. My results suggest that important pre-market effects of attractiveness on individual behaviour are likely to be consequential for both labour market performance and important pre-market investments. In this sense, the findings suggest that physical attractiveness provides another avenue for understanding non-cognitive traits that are important in child and adolescent development and carry lifetime consequences.

The chapter on the minimum legal drinking age provides intriguing results regarding the effectiveness of policies that impose limits on ‘consumption’ through age-restrictive policies; whether they are enough on their own or merely delay consumption. This is especially relevant given that there is currently a discussion about increasing the minimum legal tobacco purchasing age to 21 and increasing the age in which you can buy a national lottery ticket from age 16 to 18 in the UK.