Newly funded: Identifying which interactions spread disease

As shelter-in-place mandates lessen, societies may be able to reopen parts of their economies while still curbing overall disease spread by limiting interactions related to increased disease. A new project led by Meggan Craft, PhD, and Matt Michalska-Smith, PhD, seeks to identify which interactions are specifically related to disease spread. The researchers will simulate disease spread through a variety of social contact networks, and use machine learning to relate each network’s interpersonal interactions to the number and timing of new infections. The researchers will produce an interactive web application for the public and decision-makers to visualize trade-offs between reducing disease and opening parts of the economy. The outcomes of this research will inform and facilitate quick, efficient interventions to reduce the social and economic costs of COVID-19. This research will develop a general framework for relating disease to network structure, which can also be applied beyond the current pandemic, serving to further our understanding of potential future waves of COVID-19, as well as other directly-transmitted diseases in humans, livestock, and wildlife. This work is being funded by the National Science Foundation.