Development of an age-adjusted, activity-based contact probability model for infectious diseases

Abstract

The COVID-19 pandemic highlighted the importance of gathering restrictions in slowing the spread of communicable disease. Many restrictions on activities were applied without identifying how effective the restrictions might be in curtailing disease spread. We present a model that estimates the probability of contacting an infected individual as a function of prevalence and self-reported or hypothesized activities. The model incorporates an age adjustment factor to account for differences between the age demographics of infected versus activity participants. The age adjustment factor was important to include when the difference in prevalence between age groups was sufficiently large, and prevalence and activity group sizes were moderate. We applied our contact probability model to two scenarios to demonstrate how the model may inform the development of public health measures. Our model presents a method for estimating contact probability that could be adopted by jurisdictions considering facility closures or group size limits, or for individuals evaluating their own behaviours in future outbreaks or pandemics.