that we're seeking.
The next kind of bias is my personal favorite,
that's detection bias, because detection bias
results a lot in surveillance studies. This
is when the act of looking for an effect erroneously
gives you the impression that an effect actually
exists or that it is larger than it actually
is. So imagine you have a phenomenon and you're
looking for that phenomenon, are you going
to find it, yes you are, by the very act of
looking for it, you're going to find it. That
doesn't mean it suddenly arose, it might have
been there all along, so your presence there
has an effect on how you view the data collection
process. So here is an example, let's say
doctors are more likely to examine obese patients
for diabetes than they do thin patients, we
know this to be true because we know that
obesity is a risk factor for diabetes, therefore
they're more likely to find diabetes amongst
obese patients than they are in thinner patients.
This gives rise to something called a syndemic.
A syndemic is when we have an epidemic that's
based on synergy between two different diseases,
in this case diabetes and obesity. It might
be true, it might not. But it's entirely conceivable
that it will give you a skewed impression
of the prevalence of a certain kind of condition
in a certain kind of person. My personal favorite
is this graph that I show all my students.
So this shows us the new AIDS cases per year
from 1990 till about 2000 in three different
regions in the world; Latin America, the Caribbean
and North America. In North America the new
AIDS cases declined in the early to mid-1990s,
we think due to new therapies being introduced
and in the Caribbean in the same time period
the number of AIDS cases increased dramatically.
And I always asked my students, why was that?
Why do you think it went up so dramatically
in the Caribbean? And I hear all sorts of
theories, things like, "Oh! because there are
more travelers were coming in from different
AIDS endemic areas." or the rate of sex work
increased or a variety of different kinds
of theories. In truth, what was happening
in the Caribbean is we started looking for
more AIDS cases, so we found more AIDS cases,
it was always high, but we only noticed it
in the late 1990s, so that graph has the appearance
of an increase, but there wasn't an increase,
that's classic detection bias.
So what have you learned? You have learned
what the typical kinds of information bias