Alliance for Pandemic Preparedness

May 7, 2020

Geospatially Referenced Demographic Agent-Based Modeling of SARS-CoV-2-Infection (COVID-19) Dynamics and Mitigation Effects in a Real-World Community

Category:

Topic:

  • Adler et al. address limitations of compartmental deterministic models, including their limited ability make predictions for specific locations, points in time, or demographic groups, and to capture chance (“stochastic”) events, which is needed to estimate the probability of a second wave of transmission. 
  • The GERDA-1 model is a stochastic, geospatially-referenced and demography-specific agent-based model that can predict infection dynamics for specific subpopulations under a variety of scenarios (e.g., among health care workers with versus without adequate PPE access). 

Adler et al. (May 6, 2020). Geospatially Referenced Demographic Agent-Based Modeling of SARS-CoV-2-Infection (COVID-19) Dynamics and Mitigation Effects in a Real-World Community. Medrxiv. https://doi.org/10.1101/2020.05.03.20089235