Official websites use. Share sensitive information only on official, secure websites. Author for correspondence: Dr J. Email: jonread liverpool. A central tenet of close-contact or respiratory infection epidemiology is that infection patterns within human populations are related to underlying patterns of social interaction. Until recently, few researchers had attempted to quantify potentially infectious encounters made between people.
Now, however, several studies have quantified social mixing behaviour, using a variety of methods. Here, we review the methodologies employed, suggest other appropriate methods and technologies, and outline future research challenges for this rapidly advancing field of research.
Key words: Contact diary, infectious disease control, mathematical modelling, proximity, social mixing, social network, transmission. Understanding the spread of respiratory pathogens is a public health priority as many of the greatest threats to human health are spread by direct person-to-person contact.
A major challenge is identifying and quantifying the behavioural, social and environmental factors which permit the transmission of such pathogens and generate larger-scale patterns of spread. Accurate predictions of the likely impact of new or re-emerging pathogens and improved targeting of control interventions require a quantitative understanding of the factors and mechanisms that promote or inhibit the spread of pathogens through populations.
A principal assertion within the epidemiology of respiratory pathogens is that patterns of social mixing behaviour at the individual level contribute to the dynamics of infection seen at the population level. Despite controversy about the precise role different mechanisms may play in infection [ 1 , 2 ], proximity or social contact is thought to be a major factor in the transmission process for many important infections, including SARS, influenza and tuberculosis [ 3 , 4 ].
