Agent models for disease propagation

Detalhes bibliográficos
Autor(a) principal: Araújo, Juliano Genari de
Data de Publicação: 2024
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Biblioteca Digital de Teses e Dissertações da USP
Texto Completo: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-29072024-155156/
Resumo: As we experienced a major pandemic the necessity of smart interventions became very clear, but the decision for the best interventions to implement are usually based on educated guesses as each disease behaves differently and the macro behavior of the population can be very difficult to predict. Inappropriate interventions usually fail to consider heterogeneities in communities and can put the most susceptible part of the population at risk. To help in the evaluation of interventions, we developed highly modular and configurable software for stochastic agent model simulations: COMORBUSS, a software where the population is constructed in an organic way. Every person in the community is represented in the simulation and has an established routine, some actions are fixed (such as the time when that person goes and comes back from work), and some are randomly taken following probabilities to achieve a mean behavior. COMORBUSS can also be expanded in functionally with modules using some simple interface methods implemented in the main classes. With COMORBUSS and an airborne spread model for inside classrooms we tested different strategies for the return of schools after the first wave of the Covid-19 pandemic for the city of Maragogi-AL, in those simulations we arrived at the conclusion that for the safe opening of schools during a pandemic appropriate NPIs and behavioral protocols must be adopted, the vaccination of school teacher and other school staff is of paramount importance, as those workers are not only more susceptible than students, but they are also the main vectors of transmission. Uncontrolled school opening can be very dangerous as infection rates inside schools can explode leading to a significant increase in cases in the community.
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spelling Agent models for disease propagationModelos de agentes para propagação de doençasAgent modelsDisease simulationDynamic populationsModelo de agentesModelos estocásticosopulações dinâmicasSimulação de doençasStochastic modelsAs we experienced a major pandemic the necessity of smart interventions became very clear, but the decision for the best interventions to implement are usually based on educated guesses as each disease behaves differently and the macro behavior of the population can be very difficult to predict. Inappropriate interventions usually fail to consider heterogeneities in communities and can put the most susceptible part of the population at risk. To help in the evaluation of interventions, we developed highly modular and configurable software for stochastic agent model simulations: COMORBUSS, a software where the population is constructed in an organic way. Every person in the community is represented in the simulation and has an established routine, some actions are fixed (such as the time when that person goes and comes back from work), and some are randomly taken following probabilities to achieve a mean behavior. COMORBUSS can also be expanded in functionally with modules using some simple interface methods implemented in the main classes. With COMORBUSS and an airborne spread model for inside classrooms we tested different strategies for the return of schools after the first wave of the Covid-19 pandemic for the city of Maragogi-AL, in those simulations we arrived at the conclusion that for the safe opening of schools during a pandemic appropriate NPIs and behavioral protocols must be adopted, the vaccination of school teacher and other school staff is of paramount importance, as those workers are not only more susceptible than students, but they are also the main vectors of transmission. Uncontrolled school opening can be very dangerous as infection rates inside schools can explode leading to a significant increase in cases in the community.Não disponívelBiblioteca Digitais de Teses e Dissertações da USPSilva, Tiago Pereira daAraújo, Juliano Genari de2024-05-28info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/55/55134/tde-29072024-155156/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2024-07-29T18:59:02Zoai:teses.usp.br:tde-29072024-155156Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212024-07-29T18:59:02Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Agent models for disease propagation
Modelos de agentes para propagação de doenças
title Agent models for disease propagation
spellingShingle Agent models for disease propagation
Araújo, Juliano Genari de
Agent models
Disease simulation
Dynamic populations
Modelo de agentes
Modelos estocásticos
opulações dinâmicas
Simulação de doenças
Stochastic models
title_short Agent models for disease propagation
title_full Agent models for disease propagation
title_fullStr Agent models for disease propagation
title_full_unstemmed Agent models for disease propagation
title_sort Agent models for disease propagation
author Araújo, Juliano Genari de
author_facet Araújo, Juliano Genari de
author_role author
dc.contributor.none.fl_str_mv Silva, Tiago Pereira da
dc.contributor.author.fl_str_mv Araújo, Juliano Genari de
dc.subject.por.fl_str_mv Agent models
Disease simulation
Dynamic populations
Modelo de agentes
Modelos estocásticos
opulações dinâmicas
Simulação de doenças
Stochastic models
topic Agent models
Disease simulation
Dynamic populations
Modelo de agentes
Modelos estocásticos
opulações dinâmicas
Simulação de doenças
Stochastic models
description As we experienced a major pandemic the necessity of smart interventions became very clear, but the decision for the best interventions to implement are usually based on educated guesses as each disease behaves differently and the macro behavior of the population can be very difficult to predict. Inappropriate interventions usually fail to consider heterogeneities in communities and can put the most susceptible part of the population at risk. To help in the evaluation of interventions, we developed highly modular and configurable software for stochastic agent model simulations: COMORBUSS, a software where the population is constructed in an organic way. Every person in the community is represented in the simulation and has an established routine, some actions are fixed (such as the time when that person goes and comes back from work), and some are randomly taken following probabilities to achieve a mean behavior. COMORBUSS can also be expanded in functionally with modules using some simple interface methods implemented in the main classes. With COMORBUSS and an airborne spread model for inside classrooms we tested different strategies for the return of schools after the first wave of the Covid-19 pandemic for the city of Maragogi-AL, in those simulations we arrived at the conclusion that for the safe opening of schools during a pandemic appropriate NPIs and behavioral protocols must be adopted, the vaccination of school teacher and other school staff is of paramount importance, as those workers are not only more susceptible than students, but they are also the main vectors of transmission. Uncontrolled school opening can be very dangerous as infection rates inside schools can explode leading to a significant increase in cases in the community.
publishDate 2024
dc.date.none.fl_str_mv 2024-05-28
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.teses.usp.br/teses/disponiveis/55/55134/tde-29072024-155156/
url https://www.teses.usp.br/teses/disponiveis/55/55134/tde-29072024-155156/
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv
dc.rights.driver.fl_str_mv Liberar o conteúdo para acesso público.
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Liberar o conteúdo para acesso público.
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.coverage.none.fl_str_mv
dc.publisher.none.fl_str_mv Biblioteca Digitais de Teses e Dissertações da USP
publisher.none.fl_str_mv Biblioteca Digitais de Teses e Dissertações da USP
dc.source.none.fl_str_mv
reponame:Biblioteca Digital de Teses e Dissertações da USP
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Biblioteca Digital de Teses e Dissertações da USP
collection Biblioteca Digital de Teses e Dissertações da USP
repository.name.fl_str_mv Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)
repository.mail.fl_str_mv virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br
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