HIV Prevalence Estimates
Kim Yi Dionne was kind enough to respond to my question regarding why she was skeptical about the UN’s latest data (reports that infections are down 17% in sub-Saharan Africa).
I wasn’t surprised that it was a concern over measurement, and especially over the ability to compare data over time. (Read Kim’s post here). The data is … questionable. But I guess my point is that all UN data is problematic, and the estimates are nothing more than that.
From my perspective, there is something else going on with the data – and it’s political. I already spoke a little about this, but what is of particular interest is the fact that we know that data is never perfect – so there is always some kind of bias present. So the interesting question (to me) is why didn’t the UN over or under report? Or why did they?
Of course, such questions are simply academic. At the end of the day, what matters is what the data allows us to do. Kim says “that I’m no longer convinced that population-based testing will provide us HIV prevalence estimates we can be confident about.” My question back would be “how confident do we have to be, and why?” The data is always skewed, and by its nature it will always misrepresent reality. So what do we do with that?
I think the answer lies somewhere in the recognition that the data is never perfect, and any representation of the data is necessarily normative. Case in point, take a look at a Mercator Projection of the world, and then look at the Peters Projection. They’re both “right,” depending on your criteria. Politics and normative positions literally (in this case at list) shape how we see the world.
So I guess my pitch is this: when we look at data, we need to be cognizant of what we want to do with the data. And better – we should be cognizant of what others want to do with the data. I can use the UN data to argue for an increase in aid for SSA AIDS programs, or for a decrease. For more attention, or less. I can use it to criticize the UN for its past failures, or to compliment it for admitting its mistake. I want to know what the politics and ideology of the person working with the data is ahead of time – objectivity through transparency? I don’t know. Maybe just Gonzo academia.
Decemburns
In a moment of severely low caffeine levels, I thought that it would be a good idea to capitalize on the success of recent facial-hair related charity months (cf. Movember) and start one that brings attention to HIV/AIDS in sub-Saharan Africa. So I have recruited a few of my friends to grow “Decemburns” for the Stephen Lewis Foundation.
Not only will this raise some money, but I’m hoping that it will generate some amazing family holiday photographs. All of this will be posted on the website, Decemburns.org when it launches later this week. More news and “before” photos to follow.
