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

PLoS Comput Biol. 2021 Jul 26;17(7):e1009149. doi: 10.1371/journal.pcbi.1009149. eCollection 2021 Jul.

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.

MeSH terms

  • Basic Reproduction Number
  • COVID-19 Testing
  • COVID-19 Vaccines
  • COVID-19* / etiology
  • COVID-19* / prevention & control
  • COVID-19* / transmission
  • Computational Biology
  • Computer Simulation
  • Contact Tracing
  • Disease Progression
  • Hand Disinfection
  • Host Microbial Interactions
  • Humans
  • Masks
  • Mathematical Concepts
  • Models, Biological*
  • Pandemics
  • Physical Distancing
  • Quarantine
  • SARS-CoV-2*
  • Software
  • Systems Analysis*

Substances

  • COVID-19 Vaccines

Grant support

The author(s) received no specific funding for this work.