A method for reconstructing the HIV infection curve from data on both HIV and AIDS diagnoses is enhanced by using age as a covariate and by using the diagnosis data to estimate parameters that were previously assumed known. Maximum likelihood estimation is used for parameters of the induction distribution. Each of the set of parameters that specify the baseline rate of infection over time and the set of parameters giving the relative susceptibility over age are estimated by maximizing the likelihood subject to a smoothness requirement. We find that estimating the extra parameters is feasible, producing estimates with good precision. Including age as a covariate gives 90 per cent confidence intervals for the HIV incidence curve that are about 20 per cent narrower than those obtained when age data are not used.