Ades and Medley provided the first flexible method for estimating age- and time-specific HIV incidence using HIV prevalence data collected among pregnant women and adjusting for the effect of differential selection between infected and uninfected women. This paper extends the approach proposed by these authors. We used a parametric model that allows the relative inclusion rate to depend on both age, calendar time, and duration of HIV infection. We developed a two dimensional penalized log-likelihood approach for estimating time- and age-specific incidence using a binomial likelihood function and a quadratic roughness penalty which allows smoothing over both age and time. Identifiability of the model parameters and effect of sample size are studied through simulations. The method is illustrated using prenatal HIV testing data recorded from 1995 to 2002 in Abidjan, C?d'Ivoire, to estimate the HIV annual incidence rate among women aged 12-40 year old, from the beginning of the epidemic to 2002. We show that estimated incidence rates are highly dependent on hypotheses made to model the relative inclusion rate. Despite this dependency, the application of the method leads to new and accurate findings on HIV incidence qualitative features in Abidjan. We highlight the relevance of such a method in monitoring the dynamics of HIV epidemic in Africa which is essential for planning vaccine trials and future treatment needs, and for assessment of prevention policy.