One of the basic characteristics of infectious disease is that the transmission of infection from one individual to another requires a form of contact between those two individuals, and as a consequence the pattern of contacts in a population determines how diseases can spread through this population. And this contact pattern is often determined by the demographical characteristics of the individuals involved in the contact, such as their ages and gender. Here we show how social contact data can be used to estimate the pattern of infectious disease contact rates. Social contact data is different from the data discussed in previous chapters, and the typical challenge in analyzing this data is that we have to account for reciprocity (symmetry of the contact rates) and sparsity of data (there are many more contact rates than observations). Existing methods for doing this are reviewed. The methods are illustrated by using observed with contacts as measured in a random sample of the population of the Netherlands, structured by age and sex; the proxy measure of infectious contact is “talking to,” believed to be relevant for direct contact diseases such as influenza.