8. The accuracy of HIV testing technology is quite astonishing. If a person is truly HIV positive, blood testing methods have a $99 \%$ chance of detecting it. If a person does not carry HIV, the accuracy of the test is even higher, reaching $99.99 \%$, which means there is only a $0.01 \%$ chance of a false positive. It is known that the proportion of HIV carriers in the general population is $0.01 \%$. Now assume a random person on the street is tested, and the test result is HIV positive. The probability that this person is truly carrying HIV is approximately $\qquad$ (result to two significant figures).
8.0.50.

Let event $A=\{$ a person carries HIV $\}$,
$B=\{$ a person is diagnosed as carrying HIV through a blood test $\}$.
Then $P(B \mid A)=99\%, P(B \mid \bar{A})=0.01\%$,
$P(A)=0.01\%$.
As shown in Figure 3, let the total area be 1, and the areas of the four regions be $a, b, c, d$.
$$
\begin{array}{r}
\text { Then } \frac{a}{a+b}=0.99, \frac{c}{c+d}=10^{-4}, \\
a+b=10^{-4}, a+b+c+d=1 .
\end{array}
$$

Solving, we get $a=0.99 \times 10^{-4}$,
$$
\begin{array}{l}
c=0.9999 \times 10^{-4}, \\
P(A \mid B)=\frac{a}{a+c} \approx 0.50 .
\end{array}
$$

Therefore, the probability that this person truly carries HIV is approximately 0.50.