The recent availability of survey data on social contact patterns has made possible important advances in the understanding of the social determinants of the spread of close-contact infections, and of the importance of long-lasting contacts for effective transmission to occur. Still, little is known about the relationship between two of the most critical identified factors (frequency of contacts and duration of exposure) and how this relationship applies to different types of infections. By integrating data from two independently collected social surveys (Polymod and time use), we propose a model that combines these two transmission determinants into a new epidemiologically relevant measure of contacts: the number of "suitable" contacts, which is the number of contacts that involve a sufficiently long exposure time to allow for transmission. The validity of this new epidemiological measure is tested against Italian serological data for varicella and parvovirus-B19, with uncertainty evaluated using the Bayesian melding technique. The model performs quite well, indicating that the interplay between time of exposure and contacts is critical for varicella transmission, while for B19 it is the duration of exposure that matters for transmission.

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Summary 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.

Potential bias in survey responses is higher if sensitive outcomes are measured. This study analyses attitudes towards female genital cutting (FGC) in Ethiopia. A list experiment is designed to elicit truthful answers about FGC support and compares these outcomes with the answers given to a direct question. Our results confirm that the average bias is substantial as answers to direct questions underestimate the FGC support by about 10 percentage points. Moreover, our results provide suggestive but not statistically significant evidence that this bias is more pronounced among uneducated women and women targeted by an NGO intervention (not randomly assigned).