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Comparison of HIV‐1 and HIV‐2 infectivity from a prospective cohort study in Senegal
Author(s) -
Gilbert Peter B.,
McKeague Ian W.,
Eisen Geoffrey,
Mullins Christopher,
GuéyeNDiaye Aissatou,
Mboup Souleymane,
Kanki Phyllis J.
Publication year - 2003
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1342
Subject(s) - infectivity , multicenter aids cohort study , medicine , human immunodeficiency virus (hiv) , population , demography , cohort , prospective cohort study , hazard ratio , transmission (telecommunications) , virology , proportional hazards model , cohort study , immunology , sida , viral disease , virus , environmental health , confidence interval , sociology , electrical engineering , engineering
From a prospective cohort study of 1948 initially human immunodeficiency virus (HIV) uninfected female commercial sex workers followed between 1985 and 1999 in Dakar, Senegal, the authors compared the male to female per infectious sexual exposure transmission probability of HIV types one (HIV‐1) and two (HIV‐2). New non‐parametric competing risks failure time methods were used, which minimized modelling assumptions and controlled for risk factors for HIV infection. The HIV‐1 versus HIV‐2 infectivity ratio over time was estimated by the ratio of smoothed non‐parametric kernel estimates of the HIV‐1 and HIV‐2 infection hazard functions in sex workers, adjusted by an estimate of the relative HIV‐1 versus HIV‐2 prevalence in the partner population. HIV‐1 was found to be significantly more infectious than HIV‐2 throughout the follow‐up period (P < 0.001). The HIV‐1/HIV‐2 infectivity ratio was inferred to be approximately constant over time, with estimated common value 3.55. The finding of greater HIV‐1 infectivity persisted in sensitivity analyses and in covariate‐adjusted analyses, with adjusted infectivity ratio estimates ranging between 3.40 and 3.86. Understanding the mechanisms by which HIV‐1 infects more efficiently than HIV‐2 may be useful in the development of HIV‐1 vaccines. Additionally, the methodology developed here may be useful for analysing other data sets. Copyright © 2003 John Wiley & Sons, Ltd.