actually i think you overestimate the risk mad
acording to this artical a 20% increase (across the board) in queensland equals 20 new cases. that means the adverage infection rate for queensland is 100 cases, not very high at all
http://www.smh.com.au/articles/2003/05/28/1053801448420.html
Do you realize, Asguard, that you've just sealed my case? If the overall rate of infection for HIV is 100 per 4 million (the population of Queensland) compared with a male homosexual rate as high as 20 per 100, the effect of including male homosexual donors is staggering!
Let's run thru the numbers again. If the figure you gave me was correct for the population as a whole, the expected number of HIV positive donors among 10,000 would be 0.0000071. Now compare that with the 2,000 HIV positive results among 10,000 urban male homosexuals.
In my earlier example, I assumed a 1% false negative rate for the HIV screening (EIA) used by the Red Cross on blood donors. I just pulled that number out of my ass. Just now I tried to find out what the real number is, but couldn't find any data on false negatives. Probably no one wants to know! I did find this study having to do with the false negatives for clostridium difficile using the same test (EIA) that the Red Cross uses to screen for HIV:
The total number of stool samples tested by all three methods was 143. Chart review was done on patients with discordant test results.RESULTS: [table: see text] The Prospec II gave 4 false positive (FP) and 3 false negative (FN) results, compared to Tox A/B with 1 FP and 19 FN results.
http://gateway.nlm.nih.gov/MeetingAbstracts/ma?f=102245185.html
That's horrible! According to this study, the EIA has a false negative rate of 2-13%!
Of course it may well be that these particular EIA's aren't as good as the one's used for the screening of blood donors. So, in the absence of better data, let's just stick with the 1% false negative rate.
So, as before, with the urban male homosexuals, we'd expect 2,000 HIV positive donors. If our test had 1% false negatives, this would mean 20 donors with HIV would slip thru.
Compare this to the 0.07 expected HIV positive donors per 10,000 in thte general population. If we missed 1% of these, we'd expect 0.0007 HIV positive donors to slip thru per 10,000. Way less than one.
Can you see how including a high risk group profoundly increases the chances of tainted blood slipping thru? This is why male homosexual donors are excluded.