Estimating HIV incidence and detection rates from surveillance data.
BACKGROUND
Markov models that incorporate HIV test information can increase precision in estimates of new infections and permit the estimation of detection rates. The purpose of this study was to assess the functioning of a Markov model for estimating new HIV infections and HIV detection rates in Louisiana using surveillance data.


METHODS
We expanded a discrete-time Markov model by accounting for the change in AIDS case definition made by the Centers for Disease Control and Prevention in 1993. The model was applied to quarterly HIV/AIDS surveillance data reported in Louisiana from 1981 to 1996 for various exposure and demographic subgroups. When modeling subgroups defined by exposure categories, we adjusted for the high proportion of missing exposure information among recent cases. We ascertained sensitivity to changes in various model assumptions.


RESULTS
The model was able to produce results consistent with other sources of information in the state. Estimates of new infections indicated a transition of the HIV epidemic in Louisiana from (1) predominantly white men and men who have sex with men to (2) women, blacks, and high-risk heterosexuals. The model estimated that 61% of all HIV/AIDS cases were detected and reported by 1996, yet half of all HIV/non-AIDS cases were yet to be detected. Sensitivity analyses demonstrated that the model was robust to several uncertainties.


CONCLUSIONS
In general, the methodology provided a useful and flexible alternative for estimating infection and detection trends using data from a U.S. surveillance program. Its use for estimating current infection will need further exploration to address assumptions related to newer treatments.
Posner
Stephanie J
SJ
HIV/AIDS Program, Louisiana Office of Public Health, Department of Health and Hospitals, New Orleans, Louisiana, USA. posner@tulane.edu
Myers
Leann
L
Hassig
Susan E
SE
Rice
Janet C
JC
Kissinger
Patricia
P
Farley
Thomas A
TA
D005260:Female; D015658:HIV Infections / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D008145:Louisiana / Q000453:epidemiology; D008297:Male; D008390:Markov Chains; D011159:Population Surveillance / Q000379:methods*