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Braz. j. infect. dis ; 8(6): 399-406, Dec. 2004. ilus, tab, graf
Article in English | LILACS | ID: lil-401713

ABSTRACT

Several strategies aim at characterizing the AIDS epidemic in different parts of the world. Among these, the identification of recent HIV-1 infections using the recently described serologic testing algorithm for recent human immunodeficiency virus (HIV) seroconversion (STARHS) strategy was employed in four testing sites of the City of São Paulo Public Health Department (CSPPHD). Those identified as recently infected were invited to participate in a prospective clinical and laboratory evaluation study. We describe the establishment of the patient identification network and the success in enrolling the participants, as well as their clinical and laboratory characteristics. From May to December 2002, 6,443 persons were tested for HIV in the four participating sites, of whom 384 (5.96 percent) tested HIV-1 positive; 43 (11.2 percent) of them were identified as recently infected. Twenty-two were successfully enrolled in the follow-up study, but three of them did not meet clinical and/or laboratory criteria for recent HIV-1 infection. After these exclusions, the laboratory findings revealed a median CD4+ T lymphocyte count of 585 cells/muL (inter-quartile range 25-75 percent [IQR], 372-754), a CD8+ T lymphocyte count of 886 cells/muL (IQR, 553-1098), a viral load of 11,000 HIV-RNA copies/mL (IQR, 3,650-78,150), log10 of 4.04 (IQR 3.56-4.88). The identification of recent HIV infections is an extremely valuable way to evaluate the spread of the virus in a given population, especially when cohort studies, considered the gold standard method to evaluate incidence, are not available. This work demonstrated that establishing a network to identify such patients is a feasible task, even considering the difficulties in a large, resource-limited country or city.


Subject(s)
Humans , Male , Female , Adult , Aged , Algorithms , HIV Infections/diagnosis , HIV-1 , Information Services , Serologic Tests/methods , Follow-Up Studies , Prospective Studies , RNA, Viral/analysis , Time Factors
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