Population-based surveys are often considered the ‘gold standard’ to estimate the
prevalence of human immunodeficiency virus (HIV) but typically suffer from serious missing
data problems.This causes considerable uncertainty about HIV prevalence.Following the partial
identification approach, we produce worst-case bounds for HIV prevalence. We then exploit the
availability of panel data and the absorbing nature of HIV infection to narrow the width of these
bounds. Applied to panel data from rural Malawi, our approach considerably reduces the width
of the worst-case bounds. It also allows us to check the credibility of the additional assumptions
that are imposed by methods that point-identify HIV prevalence.