by Alan Whiteside, CIGI Chair in Global Health Policy, Balsillie School for International Affairs and Wilfrid Laurier University, Waterloo, Canada
We are bombarded with data and making sense of it is increasingly challenging. The same internet that brings the International Health Policies Newsletter barrages us with information: advertisements; offers to send money; raise libido and so on. With a few clicks of the mouse we can Google or find Wikipedia information, (although there is no guarantee of its quality). In this editorial I want to deconstruct three figures I have seen and used recently. These relate to money, HIV data, and life expectancy
Let me begin with money and the figure of $87 billion. Ahead of the replenishment meeting in December 2013, the Global Fund estimated US $87 billion was required to reach all vulnerable populations in eligible low and middle income countries over the period 2014 to 2016. This would provide essential services and bring HIV and AIDS, TB and Malaria under control. The estimated sources were: US$24 billion from international funding; an existing US $23 billion from domestic funding and a further US$14 billion to be found. The Fund hoped to raise US$15 billion but received roughly $12 billion. Clearly 24+23+14+12=73 and there is no certainty that additional domestic resources will be provided.
So is this a game of bluff? The reality is that we are reasonably certain of only $50 billion ($12 billion Global Fund, $24 billion international donors; and $14 billion domestic). What does this mean for the response? There is a disconnect between absolutely having to have this money to reverse the epidemics, as the advocates so eloquently argued, and facing the reality of having just 66 percent of the 87 percent needed.
The second set of figures is HIV prevalence data. On the 1st April 2014 the Human Sciences Research Council in South Africa released the results of the 2012 South African National HIV Prevalence, Incidence and Behaviour Survey. This is mostly bad news. By mid-2012, there were an unbelievable 6.4 million people living with HIV in South Africa. Prevalence peaks at 36 percent among women aged 30-34 and at 28.8 percent among men in the 35 -39 cohort. The only ‘good’ news is that 2 million (31.2%) ‘were exposed to ART’, there was evidence to suggest they were on treatment.
These figures are shocking. Even more disturbing is the way we seem to have taken them into our stride. There should be research on the economic, social and political consequences of having this many people infected. Most are or will be dependent on state provided drugs. Why are we not looking at the social and psychological impact of this? Should we be rewriting the social contract between state and citizens?
The last set of data I want to highlight are from the United Nations 2013 World Mortality Report. The Department of Economic and Social Affairs of the United Nations Secretariat regard themselves as ‘a vital interface between global policies in the economic, social and environmental spheres and national action’. They compile, generate and analyse a wide range of economic, social and environmental data and information to review common problems and take stock of policy options. These reports are dense and require careful study.
Table three in the report gives the ten countries with the highest and lowest life expectancies at birth for the periods 1950 – 1955, 1990 – 1995, and 2010 – 2015. For people with basic economic and political literacy the data are generally not surprising. In 1950 – 1955 the highest life expectancy was Norway at 72.2 years; Japan took poll position in the second period (79.4 years) and remained there in 2010 -2015 at 83.5 years. For the most part the low life expectancies are also predictable surprising, in 1950 – 1955 Yemen at 25.3 leads the list followed by Mali. By the second period all ten countries are African. Worst was Rwanda, post genocide, where life expectancy was just 23.1 years. The real shock comes when looking at the data for 2010 to 2015. The country with the lowest expected life expectancy in the world is Sierra Leone (45.3 years). Next were Botswana (47.4), Swaziland (49.2) and Lesotho (49.5), then come nations such as the Democratic Republic of the Congo and the Central African Republic. Botswana, Lesotho and Swaziland are all middle income countries that, by most other measures, are doing well. How can these data be unremarked!
Issues for data were at the core of the 2010 report by the Commission on the Measurement of Economic Performance and Social Progress. This work was commissioned by French President Nicolas Sarkozy. It is a short but dense book, and the graphs, in particular, require considerable study. The Commission was written largely by and for social scientists, but was intended to reach out more broadly. There are only three chapters. The first looks at classical GDP issues; the second quality of life and the third, and probably most important, is on sustainable development and the environment. I have always personally been deeply concerned about GDP particularly since it is used to place countries into income categories, which establishes what sort of support they are eligible for, and how they are viewed.
My take home message from the last few weeks of data overload is that figures are useful but we need to interrogate them and use carefully. However it is increasingly clear that in the health field we need a commission or at least an interest group to make sense of the information we are presented with. The life expectancy data from countries I know, that shaped my view of the world, and that I love has left me feeling depressed, but the real issue is that they have gone unremarked.