Modelling the COVID-19 pandemic in context: an international participatory approach
| dc.contributor.author | Aguas, Ricardo | |
| dc.contributor.author | White, Lisa | |
| dc.contributor.author | Hupert, Nathaniel | |
| dc.contributor.author | Shretta, Rima | |
| dc.contributor.author | Pan-Ngum, Wirichada | |
| dc.contributor.author | Celhay, Olivier | |
| dc.contributor.author | Moldokmatova, Ainura | |
| dc.contributor.author | Arifi, Fatima | |
| dc.contributor.author | Mirzazadeh, Ali | |
| dc.contributor.author | Sharifi, Hamid | |
| dc.contributor.author | Adib, Keyrellous | |
| dc.contributor.author | Sahak, Mohammad Nadir | |
| dc.contributor.author | Franco, Caroline [UNESP] | |
| dc.contributor.author | Coutinho, Renato | |
| dc.contributor.institution | Univ Oxford | |
| dc.contributor.institution | MAEMOD | |
| dc.contributor.institution | Cornell Inst Dis & Disaster Preparedness | |
| dc.contributor.institution | Florida Int Univ | |
| dc.contributor.institution | Univ Calif San Francisco | |
| dc.contributor.institution | Kerman Univ Med Sci | |
| dc.contributor.institution | WHO | |
| dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
| dc.contributor.institution | Universidade Federal do ABC (UFABC) | |
| dc.date.accessioned | 2021-06-25T12:30:25Z | |
| dc.date.available | 2021-06-25T12:30:25Z | |
| dc.date.issued | 2020-01-01 | |
| dc.description.abstract | 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. | en |
| dc.description.affiliation | Univ Oxford, Nuffield Dept Med, Ctr Trop Med & Global Hlth, Oxford, England | |
| dc.description.affiliation | MAEMOD, Mahidol Oxford Trop Med Res Unit, Bangkok, Thailand | |
| dc.description.affiliation | Univ Oxford, Ctr Trop Med & Global Hlth, Ctr Trop Med, Oxford, England | |
| dc.description.affiliation | Cornell Inst Dis & Disaster Preparedness, Weill Cornell Med, New York, NY USA | |
| dc.description.affiliation | Univ Oxford, Nuffield Dept Med, Oxford, England | |
| dc.description.affiliation | Florida Int Univ, Dept Epidemiol, Miami, FL 33199 USA | |
| dc.description.affiliation | Univ Calif San Francisco, Sch Med, San Francisco, CA USA | |
| dc.description.affiliation | Kerman Univ Med Sci, Inst Futures Studies Hlth, WHO Collaborating Ctr HIV Surveillance, Kerman, Iran | |
| dc.description.affiliation | WHO, Reg Off Eastern Mediterranean, Kabul, Afghanistan | |
| dc.description.affiliation | Sao Paulo State Univ UNESP, Inst Theoret Phys, Waves & Nonlinear Patterns Res Grp, Sao Paulo, SP, Brazil | |
| dc.description.affiliation | Fed Univ ABC, Ctr Math Computat & Cognit, Ctr Math Comp & Cognit, Santo Andre, SP, Brazil | |
| dc.description.affiliationUnesp | Sao Paulo State Univ UNESP, Inst Theoret Phys, Waves & Nonlinear Patterns Res Grp, Sao Paulo, SP, Brazil | |
| dc.description.sponsorship | Bill and Melinda Gates Foundation | |
| dc.description.sponsorship | Li Ka Shing Foundation | |
| dc.description.sponsorship | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
| dc.description.sponsorship | Oxford University COVID-19 Research Response Fund | |
| dc.description.sponsorshipId | Bill and Melinda Gates Foundation: OPP1193472 | |
| dc.description.sponsorshipId | FAPESP: 2017/26770-8 | |
| dc.description.sponsorshipId | Oxford University COVID-19 Research Response Fund: 0009280 | |
| dc.format.extent | 9 | |
| dc.identifier | http://dx.doi.org/10.1136/bmjgh-2020-003126 | |
| dc.identifier.citation | Bmj Global Health. London: Bmj Publishing Group, v. 5, n. 12, 9 p., 2020. | |
| dc.identifier.doi | 10.1136/bmjgh-2020-003126 | |
| dc.identifier.issn | 2059-7908 | |
| dc.identifier.uri | http://hdl.handle.net/11449/209824 | |
| dc.identifier.wos | WOS:000602736100001 | |
| dc.language.iso | eng | |
| dc.publisher | Bmj Publishing Group | |
| dc.relation.ispartof | Bmj Global Health | |
| dc.source | Web of Science | |
| dc.subject | health policy | |
| dc.subject | respiratory infections | |
| dc.subject | control strategies | |
| dc.subject | SARS | |
| dc.title | Modelling the COVID-19 pandemic in context: an international participatory approach | en |
| dc.type | Artigo | |
| dcterms.rightsHolder | Bmj Publishing Group | |
| dspace.entity.type | Publication | |
| unesp.author.orcid | 0000-0002-3006-3737[7] | |
| unesp.campus | Universidade Estadual Paulista (UNESP), Instituto de Física Teórica (IFT), São Paulo | pt |

