# Covasim: An agent-based model of COVID-19 dynamics and interventions

“Covasim: An agent-based model of COVID-19 dynamics and interventions” (2021), by Cliff C. Kerr et al. Mathematics research paper. Original abstract below, unchanged. A free PDF is available.

- Authors: Cliff C. Kerr, Robyn M. Stuart, Dina Mistry, Romesh Abeysuriya, Katherine Rosenfeld, Gregory R. Hart, Rafael C. Núñez, Jamie A. Cohen, Prashanth Selvaraj, Brittany Hagedorn et al.
- Published: July 26, 2021
- Field: Mathematics
- DOI: https://doi.org/10.1371/journal.pcbi.1009149
- Free PDF: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1009149&type=printable

## Abstract

The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.

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