Aids data: Most of it is lies,
damned lies and statistics
Up-to-date facts and figures are a prerequisite in any effective communication on most subjects, and HIV/Aids is no exception.
Seven hundred Kenyans dying every day, three in five minutes, prevalence rates, and rates of incidence are common terms to us. Such data is bandied around with such adroitness and vigour that sometimes it is as if we are fighting a series of mathematical algorithms rather than an actual virus.
Whilst there is value in using numbers to describe phenomena, it is essential that when we do so, we understand exactly what these figures represent.
It was former British Prime Minister Benjamin Disraeli who once said: "There are three types of lies: Lies, damned lies and statistics".
This could not be truer for some of the so-called "facts" hurled at us by reputable experts and international agencies in the build-up to World Aids Day.
In the Sunday Nation of November 30, Arthur Okwemba quoted the Executive Director of an Aids support group from Uganda claiming that there has been a fall in HIV prevalence in Uganda "from more than 30 per cent in 1995 to nearly 5 per cent today".
This translated in real terms, means that of the 23 million inhabitants of Uganda, almost seven million were HIV positive in 1995 and eight years later, the figure stands at slightly more than one million.
This means that there are six million less HIV positive Ugandans today than in 1995. If you factor in the Ugandans who acquired the virus after 1995, this leaves a simply enormous body of people who are no longer HIV positive. What has happened to the Ugandans who do not appear in the latest figures? Did they leave Uganda, die or were they cured of HIV?
If the prevalence figures are inverted, it does not say much for Uganda's widely commended HIV/Aids response if it is unable to prevent the deaths of 800,000 HIV positive people a year.
In Kenya, it has been stated that HIV/Aids had, by 1998, reduced life expectancy by 13 years to only 51. Taking HIV prevalence in Kenya of 12 per cent and applying a simple weighted average, it is easily proved that this assertion is a mathematical impossibility. In fact, for such a drop in life expectancy to be caused by HIV alone, HIV positive Kenyans would have to have a life expectancy of minus 44 years. That is, they would have been dead a whole two generations before they were born! We cannot be so foolish as to use baseless and incongruous statistics in our arguments.
Even the great UN, in its much quoted Aids Epidemic Update released recently, makes statements that, on closer inspection, are questionable.
It is simply not good enough to use tests on pregnant women taken in antenatal clinics as the main source for raw data used to estimate national prevalence in the way the UNAids study has.
People tested in antenatal clinics are, by the very fact they are women who have had unprotected sex, a high-risk group. The argument presented in the Epidemic Update in justifying the assumptions made by the UN in producing their estimates using this method is both weak and flawed.
What is needed is a wide reaching and aggressive campaign to derive comprehensive and accurate figures on the scourge that will allow us to plan our response based on knowledge and not conjecture.
MATTHEW BLACK,
Kenya Aids Watch Institute.
BT Yahoo! Broadband - Save £80 when you order online today. Hurry! Offer ends 21st December 2003. The way the internet was meant to be.
