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Covasim: An agent-based model of COVID-19 dynamics and interventions
- Source :
- Kerr, C C, Stuart, R M, Mistry, D, Abeysuriya, R G, Rosenfeld, K, Hart, G R, Núñez, R C, Cohen, J A, Selvaraj, P, Hagedorn, B, George, L, Jastrzȩbski, M, Izzo, A S, Fowler, G, Palmer, A, Delport, D, Scott, N, Kelly, S L, Bennette, C S, Wagner, B G, Chang, S T, Oron, A P, Wenger, E A, Panovska-Griffiths, J, Famulare, M & Klein, D J 2021, ' Covasim : An agent-based model of COVID-19 dynamics and interventions ', PLOS Computational Biology, vol. 17, no. 7, e1009149 . https://doi.org/10.1371/journal.pcbi.1009149, PLoS Computational Biology, PLoS Computational Biology, Vol 17, Iss 7, p e1009149 (2021)
- Publication Year :
- 2021
- Publisher :
- Public Library of Science (PLoS), 2021.
-
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.<br />Author summary Mathematical models have played an important role in helping countries around the world decide how to best tackle the COVID-19 pandemic. In this paper, we describe a COVID-19 model, called Covasim (COVID-19 Agent-based Simulator), that we developed to help answer these questions. Covasim can be tailored to the local context by using detailed data on the population (such as the population age distribution and number of contacts between people) and the epidemic (such as diagnosed cases and reported deaths). While Covasim can be used to explore theoretical research questions or to make projections, its main purpose is to evaluate the effect of different interventions on the epidemic. These interventions include physical interventions (mobility restrictions and masks), diagnostic interventions (testing, contact tracing, and quarantine), and pharmaceutical interventions (vaccination). Covasim is open-source, written in Python, and comes with extensive documentation, tutorials, and a webapp to ensure it can be used as easily and broadly as possible. In partnership with local stakeholders, Covasim has been used to answer policy and research questions in more than a dozen countries, including India, the United States, Vietnam, and Australia.
- Subjects :
- 0301 basic medicine
Viral Diseases
Systems Analysis
Epidemiology
Computer science
Basic Reproduction Number
Psychological intervention
Social Sciences
Systems Science
Medical Conditions
COVID-19 Testing
0302 clinical medicine
Resource (project management)
Sociology
Agent-Based Modeling
Pandemic
Medicine and Health Sciences
030212 general & internal medicine
Biology (General)
Virus Testing
Agent-based model
Quarantines
Schools
Ecology
Simulation and Modeling
Masks
Viral Load
Infectious Diseases
Computational Theory and Mathematics
Risk analysis (engineering)
Modeling and Simulation
Physical Sciences
Quarantine
Disease Progression
Research Article
Hand Disinfection
Computer and Information Sciences
COVID-19 Vaccines
Isolation (health care)
QH301-705.5
Distancing
Physical Distancing
Research and Analysis Methods
Microbiology
Models, Biological
Education
03 medical and health sciences
Cellular and Molecular Neuroscience
Age Distribution
Population Metrics
Diagnostic Medicine
Virology
Genetics
Humans
Computer Simulation
Pandemics
Molecular Biology
Ecology, Evolution, Behavior and Systematics
Flexibility (engineering)
Population Biology
Host Microbial Interactions
SARS-CoV-2
business.industry
Biology and Life Sciences
COVID-19
Computational Biology
Covid 19
Usability
Mathematical Concepts
Intervention (law)
030104 developmental biology
Contact Tracing
business
Mathematics
Viral Transmission and Infection
Software
Contact tracing
Subjects
Details
- ISSN :
- 15537358
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- PLOS Computational Biology
- Accession number :
- edsair.doi.dedup.....89d14e9238f7a8d1ff11854f56fdc345