Multinational Observational Cohort of HIV and other Infections (MOCHI). This observational study is to gain information regarding the number of new HIV infections among people who engage in behaviors that make them vulnerable to acquiring HIV across multiple international sites.
Documented history of newly diagnosed syphilis, gonorrhea, chlamydia, Mycoplasma genitalium, herpes simplex virus, or acute hepatitis C virus infection in the 24 weeks prior to screening
Self-reported vaginal, oral, or anal intercourse in exchange for money as a regular source of income in the 24 weeks prior to screening
Self-reported condomless vaginal or anal intercourse with at least three different partners living with HIV or of unknown status in the 24 weeks prior to screening
Self- reported injection drug use (IDU) in the 24 weeks prior to screening
None
The enrolled study population in step 1 will consist of up to 3000 men and women between 14 and 55 years of age who are vulnerable to HIV and other sexually transmitted infections. The incidence of HIV will be evaluated across all study sites as a primary objective; the incidence of STIs and retention in the cohort will be evaluated as key secondary objectives. During the accrual period, additional volunteers may be screened to replace participants lost to follow-up or withdrawn from the study, but no additional participants will be screened once the accrual period has expired.
Other
Prospective
Novel interventions to achieve HIV remission
BehavioralTo establish a group of well-characterized people living with HIV who initiated ART during acute or early HIV transmission that can serve as a source population for future studies, including those designed to test novel interventions to achieve HIV remission.
Establish HIV Incidence at All Sites
For the analysis of the incidence rate, only individuals who are not living with HIV at the baseline exam will be included in the incidence rate analysis. People without HIV will contribute person-time beginning with the time they enter the study until the study concludes or they are either censored or an HIV transmission event occurs. The event time for each subject is set to the minimum of the HIV transmission event time or the censoring time caused by one of the following: a drop-out event, a death event, or study end event. If one of these censoring events occurs, the censoring time is set to the last time there is recorded data for the subject. If an individual tests positive for HIV during the study, the HIV transmission event time is set to the visit during which the HIV transmission occurred. Those individuals who are lost to follow-up after enrollment will be censored at the last visit.
Establish Incidence and Prevalence of STIs Including Chlamydia, Gonorrhea, Syphilis, and Mycoplasma genitalium
For incident cases, the date of the positive test will be used as the date of infection. Specifically, for syphilis, a positive test can be determined by one of the following algorithms: 1. In the traditional algorithm, a non-treponemal test (e.g., rapid plasma reagin \[RPR\] or Venereal Disease Research Laboratory test \[VDRL\]) is used as the initial screen and reactive samples are confirmed with a treponemal test (e.g., fluorescent treponemal antibody absorption \[FTA-ABS\], T. pallidum particle agglutination \[TPPA\] test, Treponema pallidum particle agglutination assay \[TPHA\], or Syphilis IgG) or other tests that detect targets specific to T. pallidum. 2. The reverse algorithm uses a treponemal test for screening with reactive samples followed up with a non-treponemal test.
Willingness to Participate and Other Calculations
Willingness to participate in an HIV vaccine trial and study retention rates and their respective 95% CIs will be estimated assuming a binomial distribution. Factors associated with willingness to participate in vaccine trial will be evaluated using logistic regression models. Self-reported risk behavior over time will be assessed by frequency tables and bar graphs. Changes in risk behavior over time will be evaluated using a Generalized Estimating Equation (GEE) model with clustering occurring within individuals (ex: multiple observations per person). Knowledge, attitudes, and practices regarding behaviors and preventive measures will be evaluated using descriptive statistics.
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