GlobalMix

Mathematical models of infectious diseases are increasingly influential in informing health policy and investment strategies globally. Accurate data on social mixing patterns are critical for the development of valid mathematical models that simulate disease transmission dynamics. Specifically, social contact rates and mixing patterns are a fundamental parameter in the calculation of the force of infection (i.e. the rate of susceptible individuals becoming infected) in disease transmission models and are informed by social mixing studies. However, there has been no standardized multi-site social mixing study conducted in low and middle-income countries that can be used to broadly inform policy in these regions. We will collect and analyze contact data, in both rural and urban settings, in Guatemala, Pakistan, India and Mozambique in order to better parameterize infectious disease models, and thus evaluate infectious disease interventions.