Trends in HIV seroprevalence among persons attending sexually transmitted disease clinics in the United States, 1988-1992

Article Abstract:

The prevalence of HIV infection among heterosexuals and injecting drug users in minority populations appears to remain largely unchanged, while the prevalence of HIV infection among gay and bisexual men has decreased. A total of 552,665 specimens from patients at 80 U.S. sexually transmitted disease clinics was tested from 1988 to 1992. The HIV seroprevalence among gay and bisexual men dropped from 36% to 28%. Seroprevalence has remained about 2% to 3% among heterosexual men and women over the five-year period. High seroprevalence was found among young gay and bisexual men, especially minority men. Among heterosexuals, seroprevalence appears to be decreasing among whites. Prevention programs should be aimed at high-risk minority populations.

Health aspects, Minorities, Homosexuality, Male, Male homosexuality, Heterosexuals

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Serial HIV seroprevalence surveys: interpretation, design, and role in HIV/AIDS prediction

Article Abstract:

A model to interpret HIV seroprevalence data is presented that may help in analyzing and predicting the AIDS epidemic. In the case of HIV, both infected and uninfected people in the serosurvey must be analyzed or incidence may be overestimated. HIV seroprevalence may be assessed in terms of age and time incidence. For example, seroprevalence falls in a group of 40-year-olds in the 15th year of the AIDS epidemic, while seroprevalence rises in a group of 20-year-olds in the same year. Models using incidence and differential inclusion are needed to interpret trends in seroprevalence.

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Interpreting HIV seroprevalence data from pregnant women

Article Abstract:

Researchers are working on a mathematical model that will allow them to predict the prevalence of HIV infection in women by analyzing the prevalence in pregnant women. Pregnant women are often used in surveys of HIV infection because they receive regular check-ups. However, the prevalence of HIV infection in women may not be the same as in pregnant women because each group has different risk factors and social behaviors. The model can take these differences into account.

Testing, Pregnant women, Prevalence studies (Epidemiology)

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