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.
Model-based geostatistics for prevalence mapping in low-resource settings. Journal of the American Statistical Association Published 18th October 2016
Geostatistics refers to the set of statistical methods used to analyse discrete spatial data to unobserved underlying causal processes. The methods were first conceived in the 1950s for the South African mining industry to be able to make inferences about gold deposits from small sets of samples. Nowadays, these methods have wide applications, including in epidemiology as they are shown here. Peter Diggle and Emanuele Giorgi build on earlier work to give a broad overview of geostatistics for disease prevalence mapping and discuss specific applications in low resources settings where issues such as sparse data or the need to rely on different data sources of different quality arise. While this may not seem to be in the realm of health economics, the analysis of spatial data is often used for modelling things like hospital access or as a step in burden of disease calculations. In high income country settings, such as the United Kingdom, we often have access to high resolution data across all areas, but this could easily be combined with other data sources linked to specific locations in a way that this paper and others discuss. In a previous post, we discussed modelling and analysis of slums, methods such as these will no doubt prove invaluable as more data becomes available in the future. Better data along with valid and robust statistical methods can only improve policy analysis and policy design. This paper provides a good insight into this area of statistics for any statistically-minded health economist.
Assessment of economic vulnerability to infectious disease crises. The Lancet [PubMed] Published 12th November 2016
The risk register of the UK Cabinet Office provides a summary of the likelihood and potential impact of a wide range of possible civil emergencies. Pandemic influenza is rated as the highest risk both in terms of likelihood and potential impact. Indeed, an influenza pandemic of the scale of the 1918-9 Spanish Influenza would cause economic losses of around $3 trillion. Similarly, the ebola pandemic that struck a number of West African nations was estimated to have caused a cumulative loss worth about 10% of GDP for the affected nations. And yet infectious disease pandemics rarely feature in economic risk assessments. It may be due to the methodological difficulty of doing so, or poor judgement about the impact of low-probability, high-impact events. In any case, this article proposes a framework for assessing the potential consequences of a pandemic. The steps it outlines are pretty much as you would expect: identify pandemic risk, identify health system capacity, estimate economic vulnerability on a sectoral basis, and make an overall assessment. This may seem a fairly routine task when compared to the assessment of other economic risks, but as the authors show, it is often not done. They show that terrorism is widely considered as a major economic risk, and mentions of terrorism in reports change little from before to after a terrorist incidence. But, pandemics are often not discussed until after one has occurred. The Lancet can sometimes go awry when it ventures into economics. However, it can sometimes publish thoughtful and interesting arguments that economists should consider. Infectious disease crises are a neglected dimension of global security.
Distinguishing hypothetical willingness from behavioral intentions to initiate HIV pre-exposure prophylaxis (PrEP): Findings from a large cohort of gay and bisexual men in the U.S. Social Science & Medicine Published 18th November 2016
A short while ago we posted a piece about pre-exposure prophylaxis (PrEP). The media had kicked up a fuss when a court ruled that the provision of PrEP, which can significantly reduce the risk of contracting HIV, fell within the remit of the NHS. We argued that this was unwarranted since PrEP would likely go through the same scrutiny as any other potential treatment, and its cost-effectiveness would need to be established. Economic evaluations of interventions for infectious diseases can be tricky since the analyst should take into account transmission dynamics, which can amplify intervention effects in a population. A further concern, and one which this paper considers, is whether the patients targeted for the intervention would actually be willing to take it. A sub-sample of 880 PrEP-naïve men, from a longitudinal study of gay and bisexual men in the United States, were surveyed on their attitudes to PrEP. The men were asked about their perceptions of the efficacy of PrEP (about 90% reduction in risk) and whether they were unwilling, willing, or intending to take it. The results are broken down into various groups, including for those who had engaged in condomless sex with a partner who was HIV positive or of unknown status – a potentially high risk group to whom PrEP may be offered. Of this higher risk group, 27% responded that they were unwilling to take it, which may seem surprising given the high efficacy and low side effect profile. One explanation could be the lack of knowledge about PrEP: only one third of men in the sample knew its efficacy. Results like these are crucial to appropriately design and evaluate interventions in this area and it is suggestive of the need for greater provision of information to higher risk individuals.
[…] model. There is a wealth of literature on these models: we recently featured one on a journal round up. But, moving from these models to usable code is not always obvious, so this post outlines an […]