This is (in part) explained in the box to the right. Then there is also the 'population statistics' differences.
Epidemiology is a strange field. Because of the difficulty of balancing specificity and sensitivity, "99.9% accurate" tests often end up meaning that even if you test positive, you have a small chance of actually being infected.
Statistics are scary, especially to policy makers. If you tell someone "homosexuals have up to a 5000% higher chance of getting AIDS from sex", that can have a pretty big effect on policy.
This is (in part) explained in the box to the right. Then there is also the 'population statistics' differences.
Epidemiology is a strange field. Because of the difficulty of balancing specificity and sensitivity, "99.9% accurate" tests often end up meaning that even if you test positive, you have a small chance of actually being infected.
Statistics are scary, especially to policy makers. If you tell someone "homosexuals have up to a 5000% higher chance of getting AIDS from sex", that can have a pretty big effect on policy.