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COVID-ABS

swMATH ID: 41716
Software Authors: Silva, Petrônio C. L.; Batista, Paulo V. C.; Lima, Hélder S.; Alves, Marcos A.; Guimarães, Frederico G.; Silva, Rodrigo C. P.
Description: COVID-ABS: an agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions. The COVID-19 pandemic due to the SARS-CoV-2 coronavirus has directly impacted the public health and economy worldwide. To overcome this problem, countries have adopted different policies and non-pharmaceutical interventions for controlling the spread of the virus. This paper proposes the COVID-ABS, a new SEIR (Susceptible-Exposed-Infected-Recovered) agent-based model that aims to simulate the pandemic dynamics using a society of agents emulating people, business and government. Seven different scenarios of social distancing interventions were analyzed, with varying epidemiological and economic effects: (1) do nothing, (2) lockdown, (3) conditional lockdown, (4) vertical isolation, (5) partial isolation, (6) use of face masks, and (7) use of face masks together with 50
Homepage: https://www.sciencedirect.com/science/article/pii/S0960077920304859
Source Code:  https://github.com/petroniocandido/COVID19_AgentBasedSimulation
Keywords: COVID-19; agent-based simulation; epidemic models; SEIR
Related Software: Covasim; fpp2; usmap; GNAR; rapidminer; ggplot2; CRAN; AlexNet; ImageNet; Scikit; SciPy; GitHub
Cited in: 8 Publications

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