ArticlePLoS computational biology2021
Covasim: An agent-based model of COVID-19 dynamics and interventions.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 271 papers, 6 of them syntheses that pooled it.
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Who cites it
271 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- A systematic review of spatial epidemiological modeling approaches applied during the COVID-19 pandemic.BMC public health · 2026Pooled it
- Relevance of social contact definitions for use in infectious disease transmission modeling: a systematic review and recommendations.BMC infectious diseases · 2026Pooled it
- Data-driven strategies for model-informed decision-making during the COVID-19 pandemic: a systematic review.BMJ open · 2026Pooled it
- Agent-based modelling of Mycobacterium tuberculosis transmission: a systematic review.BMC infectious diseases · 2024Pooled it
- Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review.Systematic reviews · 2024Pooled it
- Comparative effectiveness of contact tracing interventions in the context of the COVID-19 pandemic: a systematic review.European journal of epidemiology · 2023Pooled it
- Integrating mathematical modelling and artificial intelligence to combat emerging viral syndemics: A systematic review.New microbes and new infections · 2026Review
- Impact of Digital Contact Tracing and Other Nonpharmaceutical Interventions on Pandemic Control: Microlevel, Behavior-Driven Agent-Based Model Analysis.Journal of medical Internet research · 2026Article
- MEmilio: a high performance Modular EpideMIcs simuLatIOn software for multi-scale and comparative simulations of infectious disease dynamics.Scientific reports · 2026Article
- Multi-source agent-based modeling to optimize influenza mitigation strategies in Hong Kong.Nature communications · 2026Article
- Mapping spatial colleague connectivity patterns from individual-level registry data to inform regional pandemic interventions.PLoS computational biology · 2026Article
- Evaluation of respiratory disease hospitalisation forecasts using synthetic outbreak data.Communications medicine · 2026Article
- Differentially private federated learning for localized control of infectious disease dynamics.Scientific reports · 2026Article
- A comparison of contact patterns derived from the population structure in agent-based models and empirical contact survey data.PLoS computational biology · 2026Article
- Integrating viral kinetics and population spread in a one health framework to explain variant-specific epidemic dynamics.One health (Amsterdam, Netherlands) · 2026Article
- The spread of non-native species.Biological reviews of the Cambridge Philosophical Society · 2026Review
- Mechanistic Understanding of Pandemic Dynamics: A Multiscale Algorithmic Framework.Life (Basel, Switzerland) · 2026Article
- Human mobility and outbreak origins in epidemic spread: Insights from agent-based modeling.PLoS computational biology · 2026Article
- Modeling individual self-protective behavior during epidemics.PLoS computational biology · 2026Article
- Understanding how mobility and spatial disparities shape COVID-19 transmission under rotational and localized lockdowns.Scientific reports · 2026Article
211 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
26 authors.
Funding
No grant is acknowledged in the PubMed record.
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.