Project R-15172

Statistical methods for analyzing infectious diseases using social contact data (Research)

Infectious diseases are caused by pathogens such as viruses, bacteria, fungi, or parasites that invade a host, multiply, and can spread to others. The transmission of respiratory infections in human populations is primarily driven by social interactions, which determine how pathogens move between individuals. Understanding these social contact patterns is crucial for characterizing the interactions that facilitate the spread of viral respiratory infections. This information not only reveals key mixing patterns but also serves as the foundation for developing more realistic contact-based mathematical models that enhance our ability to predict and understand disease transmission. Given their importance, studies have collected contact information across different settings, including various countries and locations during pre- and pandemic settings. During the study period, we aim to enhance the utility of social contact data by conducting evaluations to assess the quality of existing surveys and exploring how to better incorporate this data into models to reflect more realistic contact behaviors. These efforts will allow us to better understand the impact of contact patterns on outbreak dynamics and improve the validity of disease transmission models, ultimately aiding in the design of more effective public health interventions and outbreak prevention strategies.

01 July 2024 - 15 August 2025