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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.

Original publication

DOI

10.1371/journal.pcbi.1009149

Type

Journal article

Journal

PLoS computational biology

Publication Date

07/2021

Volume

17

Addresses

Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America.

Keywords

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