COVID-ABS : an agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions.

Simple item page
dc.contributor.authorSilva, Petrônio Cândido de Lima e
dc.contributor.authorBatista, Paulo Vitor do Carmo
dc.contributor.authorLima, Hélder Seixas
dc.contributor.authorAlves, Marcos Antonio
dc.contributor.authorGuimarães, Frederico Gadelha
dc.contributor.authorSilva, Rodrigo César Pedrosa
dc.date.accessioned2022-11-10T20:44:30Z
dc.date.available2022-11-10T20:44:30Z
dc.date.issued2020pt_BR
dc.description.abstractThe 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% of adhesion to social isolation. In the impossibility of implementing scenarios with lockdown, which present the lowest number of deaths and highest impact on the economy, scenarios combining the use of face masks and partial isolation can be the more realistic for implementation in terms of social cooperation. The COVID-ABS model was implemented in Python programming language, with source code publicly available. The model can be easily extended to other societies by changing the input parameters, as well as allowing the creation of a multitude of other scenarios. Therefore, it is a useful tool to assist politicians and health authorities to plan their actions against the COVID-19 epidemic.pt_BR
dc.identifier.citationSILVA, P. C. de L. e et al. COVID-ABS: an agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions. Chaos Solitons & Fractals, v. 139, artigo 110088, 2020. Disponível em: <https://www.sciencedirect.com/science/article/pii/S0960077920304859?via%3Dihub>. Acesso em: 06 jul. 2022.pt_BR
dc.identifier.doihttps://doi.org/10.1016/j.chaos.2020.110088pt_BR
dc.identifier.issn0960-0779
dc.identifier.urihttp://www.repositorio.ufop.br/jspui/handle/123456789/15795
dc.identifier.uri2https://www.sciencedirect.com/science/article/pii/S0960077920304859?via%3Dihubpt_BR
dc.language.isoen_USpt_BR
dc.rightsrestritopt_BR
dc.subjectAgent-based simulationpt_BR
dc.subjectEpidemic modelspt_BR
dc.titleCOVID-ABS : an agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions.pt_BR
dc.typeArtigo publicado em periodicopt_BR
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
ARTIGO_COVIDABSAgent.pdf
Size:
3.37 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
DECOM - Artigos publicados em periódicos