Your browser doesn't support javascript.
loading
Modelling disease mitigation at mass gatherings: A case study of COVID-19 at the 2022 FIFA World Cup.
Grunnill, Martin; Arino, Julien; McCarthy, Zachary; Bragazzi, Nicola Luigi; Coudeville, Laurent; Thommes, Edward W; Amiche, Amine; Ghasemi, Abbas; Bourouiba, Lydia; Tofighi, Mohammadali; Asgary, Ali; Baky-Haskuee, Mortaza; Wu, Jianhong.
Afiliação
  • Grunnill M; Laboratory of Industrial and Applied Mathematics (LIAM), York University, Toronto, Ontario, Canada.
  • Arino J; Department of Mathematics, University of Manitoba, Winnipeg, Manitoba, Canada.
  • McCarthy Z; Laboratory of Industrial and Applied Mathematics (LIAM), York University, Toronto, Ontario, Canada.
  • Bragazzi NL; Laboratory of Industrial and Applied Mathematics (LIAM), York University, Toronto, Ontario, Canada.
  • Coudeville L; Modeling, Epidemiology and Data Science (MEDS), Sanofi, Lyon, France.
  • Thommes EW; Modeling, Epidemiology and Data Science (MEDS), Sanofi, Lyon, France.
  • Amiche A; Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada.
  • Ghasemi A; Sanofi, Dubai, United Arab Emirates.
  • Bourouiba L; The Fluid Dynamics of Disease Transmission Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
  • Tofighi M; Mechanical and Industrial Engineering Department, Toronto Metropolitan University, Toronto, Ontario, Canada.
  • Asgary A; The Fluid Dynamics of Disease Transmission Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
  • Baky-Haskuee M; Dahdaleh Institute for Global Health Research, York University, Toronto, Canada.
  • Wu J; Disaster & Emergency Management, York University, Toronto, Canada.
PLoS Comput Biol ; 20(1): e1011018, 2024 Jan.
Article em En | MEDLINE | ID: mdl-38236838
ABSTRACT
The 2022 FIFA World Cup was the first major multi-continental sporting Mass Gathering Event (MGE) of the post COVID-19 era to allow foreign spectators. Such large-scale MGEs can potentially lead to outbreaks of infectious disease and contribute to the global dissemination of such pathogens. Here we adapt previous work and create a generalisable model framework for assessing the use of disease control strategies at such events, in terms of reducing infections and hospitalisations. This framework utilises a combination of meta-populations based on clusters of people and their vaccination status, Ordinary Differential Equation integration between fixed time events, and Latin Hypercube sampling. We use the FIFA 2022 World Cup as a case study for this framework (modelling each match as independent 7 day MGEs). Pre-travel screenings of visitors were found to have little effect in reducing COVID-19 infections and hospitalisations. With pre-match screenings of spectators and match staff being more effective. Rapid Antigen (RA) screenings 0.5 days before match day performed similarly to RT-PCR screenings 1.5 days before match day. Combinations of pre-travel and pre-match testing led to improvements. However, a policy of ensuring that all visitors had a COVID-19 vaccination (second or booster dose) within a few months before departure proved to be much more efficacious. The State of Qatar abandoned all COVID-19 related travel testing and vaccination requirements over the period of the World Cup. Our work suggests that the State of Qatar may have been correct in abandoning the pre-travel testing of visitors. However, there was a spike in COVID-19 cases and hospitalisations within Qatar over the World Cup. Given our findings and the spike in cases, we suggest a policy requiring visitors to have had a recent COVID-19 vaccination should have been in place to reduce cases and hospitalisations.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Futebol / Esportes / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Futebol / Esportes / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article