Estimating HIV incidence from age-specific prevalence data: comparison with concurrent cohort estimates in a study of male factory workers, Harare, Zimbabwe.

Objective: To compare HIV incidence estimates from cross-sectional age-specific prevalence data with concurrent cohort estimates and to examine the sensitivity of the estimates to changes in age-categorization and survivorship assumptions.
Methods: Two previously described methods of estimating HIV incidence from cross-sectional prevalence data - the cumulative incidence and survival (CIS) and constant prevalence (CP) methods - are applied using data from a study of male factory workers in Harare, Zimbabwe. The methods are applied under two alternative groupings of the HIV prevalence data and under alternative survivorship assumptions: (a) Weibull distribution providing the best fit to the HIV prevalence data using the CIS method; (b) Weibull distribution matching data from an HIV natural history cohort study in Uganda; and (c) survivorship pattern as in (b) with survival periods reducing with increasing age at infection. Age-specific, age-standardized and cumulative HIV incidence estimates are calculated. The results are compared with concurrent longitudinal estimates from 3 years of follow-up of the Harare cohort (1993-1995).
Results: Age-standardized HIV incidence was estimated at 2.02 per 100 man years (95% CI, 1.57-2.47) in the cohort study. There was evidence of recent variability in HIV incidence in these data. Estimates from the cross-sectional methods ranged from 1.98 to 2.74 per 100 man years and were sensitive to changes in age-categorization of the HIV prevalence data and changes in survivorship assumptions. The cross-sectional estimates were higher at central ages and lower at older ages than the cohort estimates. The age-specific estimates from the CIS method were less sensitive to changes in age grouping than those from the CP method.
Conclusions: HIV incidence remains high in Harare. Incidence estimates broadly consistent with cohort estimates can be obtained from single-round cross-sectional HIV prevalence data in established epidemics - even when the underlying assumption of stable endemic prevalence is not fully met. Estimates based on cross-sectional surveys should therefore be explored when reliable longitudinal estimates cannot be obtained. More data on post-HIV infection survivorship distributions in sub-Saharan Africa would facilitate the improvement of estimates of incidence based on cross-sectional surveys.