Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: an agent-based modeling approach

Abstract

Intervention strategies for minimizing indoor SARS-CoV-2 transmission are often based on anecdotal evidence because there is little evidence-based research to support them. We developed a spatially-explicit agent-based model for simulating indoor respiratory pathogen transmission, and used it to compare effects of four interventions on reducing individual-level SARS-CoV-2 transmission risk by simulating a well-known case study. We found that imposing movement restrictions and efficacious mask usage appear to have the greatest effects on reducing infection risk, but multiple concurrent interventions are required to minimize the proportion of susceptible individuals infected. Social distancing had little effect on reducing transmission if individuals move during the gathering. Furthermore, our results suggest that there is potential for ventilation airflow to expose susceptible people to aerosolized pathogens even if they are relatively far from infectious individuals. Maximizing rates of aerosol removal is the key to successful transmission-risk reduction when using ventilation systems as intervention tools.

Article summary line: Imposing mask usage requirements, group size restrictions, duration limits, and social distancing policies can have additive, and in some cases multiplicative protective effects on SARS-CoV-2 infection risk during indoor events.

Figure 1.

Model droplet dynamics. A) Infectious individuals expel droplets of different sizes. B) Relatively large droplets fall out of the air quickly post expectoration. C) Smaller droplets remain aerosolized for longer time periods and move throughout the simulated room via diffusion and forced airflow effects. D) Distribution of droplet sizes during expectoration events. Distributions of size classes during coughing and speaking events are based on findings of (47), and represent mean observed droplet-size measurements they recorded 60 mm away from individuals’ mouths immediately following these activities.

Figure 2.

In the absence of interventions to reduce transmission risk, the proportion of susceptible people infected in simulations can reflect the case study value (i.e., 0.88) and is more likely to do so when forced airflow is included.

Figure 3.

Predicted proportion of susceptible populations infected with SARS-CoV-2 for varied parameter sets suggest that concurrent deployment of multiple interventions is required to achieve near-zero transmission rates.