Modelling the COVID-19 pandemic in context: an international participatory approach

Detalhes bibliográficos
Autor(a) principal: Aguas, Ricardo
Data de Publicação: 2020
Outros Autores: White, Lisa, Hupert, Nathaniel, Shretta, Rima, Pan-Ngum, Wirichada, Celhay, Olivier, Moldokmatova, Ainura, Arifi, Fatima, Mirzazadeh, Ali, Sharifi, Hamid, Adib, Keyrellous, Sahak, Mohammad Nadir, Franco, Caroline [UNESP], Coutinho, Renato
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1136/bmjgh-2020-003126
http://hdl.handle.net/11449/209824
Resumo: The SARS-CoV-2 pandemic has had an unprecedented impact on multiple levels of society. Not only has the pandemic completely overwhelmed some health systems but it has also changed how scientific evidence is shared and increased the pace at which such evidence is published and consumed, by scientists, policymakers and the wider public. More significantly, the pandemic has created tremendous challenges for decision-makers, who have had to implement highly disruptive containment measures with very little empirical scientific evidence to support their decision-making process. Given this lack of data, predictive mathematical models have played an increasingly prominent role. In high-income countries, there is a long-standing history of established research groups advising policymakers, whereas a general lack of translational capacity has meant that mathematical models frequently remain inaccessible to policymakers in low-income and middle-income countries. Here, we describe a participatory approach to modelling that aims to circumvent this gap. Our approach involved the creation of an international group of infectious disease modellers and other public health experts, which culminated in the establishment of the COVID-19 Modelling (CoMo) Consortium. Here, we describe how the consortium was formed, the way it functions, the mathematical model used and, crucially, the high degree of engagement fostered between CoMo Consortium members and their respective local policymakers and ministries of health.
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spelling Modelling the COVID-19 pandemic in context: an international participatory approachhealth policyrespiratory infectionscontrol strategiesSARSThe SARS-CoV-2 pandemic has had an unprecedented impact on multiple levels of society. Not only has the pandemic completely overwhelmed some health systems but it has also changed how scientific evidence is shared and increased the pace at which such evidence is published and consumed, by scientists, policymakers and the wider public. More significantly, the pandemic has created tremendous challenges for decision-makers, who have had to implement highly disruptive containment measures with very little empirical scientific evidence to support their decision-making process. Given this lack of data, predictive mathematical models have played an increasingly prominent role. In high-income countries, there is a long-standing history of established research groups advising policymakers, whereas a general lack of translational capacity has meant that mathematical models frequently remain inaccessible to policymakers in low-income and middle-income countries. Here, we describe a participatory approach to modelling that aims to circumvent this gap. Our approach involved the creation of an international group of infectious disease modellers and other public health experts, which culminated in the establishment of the COVID-19 Modelling (CoMo) Consortium. Here, we describe how the consortium was formed, the way it functions, the mathematical model used and, crucially, the high degree of engagement fostered between CoMo Consortium members and their respective local policymakers and ministries of health.Bill and Melinda Gates FoundationLi Ka Shing FoundationFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Oxford University COVID-19 Research Response FundUniv Oxford, Nuffield Dept Med, Ctr Trop Med & Global Hlth, Oxford, EnglandMAEMOD, Mahidol Oxford Trop Med Res Unit, Bangkok, ThailandUniv Oxford, Ctr Trop Med & Global Hlth, Ctr Trop Med, Oxford, EnglandCornell Inst Dis & Disaster Preparedness, Weill Cornell Med, New York, NY USAUniv Oxford, Nuffield Dept Med, Oxford, EnglandFlorida Int Univ, Dept Epidemiol, Miami, FL 33199 USAUniv Calif San Francisco, Sch Med, San Francisco, CA USAKerman Univ Med Sci, Inst Futures Studies Hlth, WHO Collaborating Ctr HIV Surveillance, Kerman, IranWHO, Reg Off Eastern Mediterranean, Kabul, AfghanistanSao Paulo State Univ UNESP, Inst Theoret Phys, Waves & Nonlinear Patterns Res Grp, Sao Paulo, SP, BrazilFed Univ ABC, Ctr Math Computat & Cognit, Ctr Math Comp & Cognit, Santo Andre, SP, BrazilSao Paulo State Univ UNESP, Inst Theoret Phys, Waves & Nonlinear Patterns Res Grp, Sao Paulo, SP, BrazilBill and Melinda Gates Foundation: OPP1193472FAPESP: 2017/26770-8Oxford University COVID-19 Research Response Fund: 0009280Bmj Publishing GroupUniv OxfordMAEMODCornell Inst Dis & Disaster PreparednessFlorida Int UnivUniv Calif San FranciscoKerman Univ Med SciWHOUniversidade Estadual Paulista (Unesp)Universidade Federal do ABC (UFABC)Aguas, RicardoWhite, LisaHupert, NathanielShretta, RimaPan-Ngum, WirichadaCelhay, OlivierMoldokmatova, AinuraArifi, FatimaMirzazadeh, AliSharifi, HamidAdib, KeyrellousSahak, Mohammad NadirFranco, Caroline [UNESP]Coutinho, Renato2021-06-25T12:30:25Z2021-06-25T12:30:25Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article9http://dx.doi.org/10.1136/bmjgh-2020-003126Bmj Global Health. London: Bmj Publishing Group, v. 5, n. 12, 9 p., 2020.2059-7908http://hdl.handle.net/11449/20982410.1136/bmjgh-2020-003126WOS:000602736100001Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengBmj Global Healthinfo:eu-repo/semantics/openAccess2021-10-23T19:50:02Zoai:repositorio.unesp.br:11449/209824Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:36:41.960120Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Modelling the COVID-19 pandemic in context: an international participatory approach
title Modelling the COVID-19 pandemic in context: an international participatory approach
spellingShingle Modelling the COVID-19 pandemic in context: an international participatory approach
Aguas, Ricardo
health policy
respiratory infections
control strategies
SARS
title_short Modelling the COVID-19 pandemic in context: an international participatory approach
title_full Modelling the COVID-19 pandemic in context: an international participatory approach
title_fullStr Modelling the COVID-19 pandemic in context: an international participatory approach
title_full_unstemmed Modelling the COVID-19 pandemic in context: an international participatory approach
title_sort Modelling the COVID-19 pandemic in context: an international participatory approach
author Aguas, Ricardo
author_facet Aguas, Ricardo
White, Lisa
Hupert, Nathaniel
Shretta, Rima
Pan-Ngum, Wirichada
Celhay, Olivier
Moldokmatova, Ainura
Arifi, Fatima
Mirzazadeh, Ali
Sharifi, Hamid
Adib, Keyrellous
Sahak, Mohammad Nadir
Franco, Caroline [UNESP]
Coutinho, Renato
author_role author
author2 White, Lisa
Hupert, Nathaniel
Shretta, Rima
Pan-Ngum, Wirichada
Celhay, Olivier
Moldokmatova, Ainura
Arifi, Fatima
Mirzazadeh, Ali
Sharifi, Hamid
Adib, Keyrellous
Sahak, Mohammad Nadir
Franco, Caroline [UNESP]
Coutinho, Renato
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Univ Oxford
MAEMOD
Cornell Inst Dis & Disaster Preparedness
Florida Int Univ
Univ Calif San Francisco
Kerman Univ Med Sci
WHO
Universidade Estadual Paulista (Unesp)
Universidade Federal do ABC (UFABC)
dc.contributor.author.fl_str_mv Aguas, Ricardo
White, Lisa
Hupert, Nathaniel
Shretta, Rima
Pan-Ngum, Wirichada
Celhay, Olivier
Moldokmatova, Ainura
Arifi, Fatima
Mirzazadeh, Ali
Sharifi, Hamid
Adib, Keyrellous
Sahak, Mohammad Nadir
Franco, Caroline [UNESP]
Coutinho, Renato
dc.subject.por.fl_str_mv health policy
respiratory infections
control strategies
SARS
topic health policy
respiratory infections
control strategies
SARS
description The SARS-CoV-2 pandemic has had an unprecedented impact on multiple levels of society. Not only has the pandemic completely overwhelmed some health systems but it has also changed how scientific evidence is shared and increased the pace at which such evidence is published and consumed, by scientists, policymakers and the wider public. More significantly, the pandemic has created tremendous challenges for decision-makers, who have had to implement highly disruptive containment measures with very little empirical scientific evidence to support their decision-making process. Given this lack of data, predictive mathematical models have played an increasingly prominent role. In high-income countries, there is a long-standing history of established research groups advising policymakers, whereas a general lack of translational capacity has meant that mathematical models frequently remain inaccessible to policymakers in low-income and middle-income countries. Here, we describe a participatory approach to modelling that aims to circumvent this gap. Our approach involved the creation of an international group of infectious disease modellers and other public health experts, which culminated in the establishment of the COVID-19 Modelling (CoMo) Consortium. Here, we describe how the consortium was formed, the way it functions, the mathematical model used and, crucially, the high degree of engagement fostered between CoMo Consortium members and their respective local policymakers and ministries of health.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
2021-06-25T12:30:25Z
2021-06-25T12:30:25Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1136/bmjgh-2020-003126
Bmj Global Health. London: Bmj Publishing Group, v. 5, n. 12, 9 p., 2020.
2059-7908
http://hdl.handle.net/11449/209824
10.1136/bmjgh-2020-003126
WOS:000602736100001
url http://dx.doi.org/10.1136/bmjgh-2020-003126
http://hdl.handle.net/11449/209824
identifier_str_mv Bmj Global Health. London: Bmj Publishing Group, v. 5, n. 12, 9 p., 2020.
2059-7908
10.1136/bmjgh-2020-003126
WOS:000602736100001
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Bmj Global Health
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 9
dc.publisher.none.fl_str_mv Bmj Publishing Group
publisher.none.fl_str_mv Bmj Publishing Group
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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