Abstract:
To quantify the HIV epidemic, the classical population-based prevalence and incidence rates (P rates) are the two
most commonly used measures used for policy interventions. However, these P rates ignore the heterogeneity of
the size of geographic regionwhere the population resides. It is intuitive that with the sameP rates, the likelihood
for HIV can be much greater to spread in a population residing in a crowed small urban area than the same
number of population residing in a large rural area. With this limitation, Chen and Wang (2017) proposed the
geographic area-based rates (G rates) to complement the classical P rates. They analyzed the 2000–2012 US
data on new HIV infections and persons living with HIV and found, as compared with other methods, using G
rates enables researchers to more quickly detect increases in HIV rates. This capacity to reveal increasing rates
in a more efficient and timely manner is a crucial methodological contribution to HIV research. To enhance
this newly proposed concept of G rates, this article presents a discussion of 3 areas for further development of
this important concept: (1) analysis of global HIV epidemic data using the newly proposed G rates to capture
the changes globally; (2) development of the associated population density-based rates (D rates) to incorporate
the heterogeneities from both geographical area and total population-at-risk; and (3) development of methods
to calculate variances and confidence intervals for the P rates, G rates, and D rates to capture the variability of
these indices.
