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The unequal effects of the health-economy trade-off during the COVID-19 pandemic.
Pangallo, Marco; Aleta, Alberto; Del Rio-Chanona, R Maria; Pichler, Anton; Martín-Corral, David; Chinazzi, Matteo; Lafond, François; Ajelli, Marco; Moro, Esteban; Moreno, Yamir; Vespignani, Alessandro; Farmer, J Doyne.
Afiliación
  • Pangallo M; CENTAI Institute, Turin, Italy. marco.pangallo@centai.eu.
  • Aleta A; Institute for Biocomputation and Physics of Complex Systems and Department of Theoretical Physics, University of Zaragoza, Zaragoza, Spain.
  • Del Rio-Chanona RM; Complexity Science Hub, Vienna, Austria.
  • Pichler A; Complexity Science Hub, Vienna, Austria.
  • Martín-Corral D; Department of Mathematics and GISC, Universidad Carlos III de Madrid, Leganes, Spain.
  • Chinazzi M; MOBS Lab, Northeastern University, Boston, MA, USA.
  • Lafond F; The Roux Institute, Northeastern University, Portland, ME, USA.
  • Ajelli M; Institute for New Economic Thinking at the Oxford Martin School, and Smith School of Enterprise and the Environment, University of Oxford, Oxford, UK.
  • Moro E; Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA.
  • Moreno Y; Department of Mathematics and GISC, Universidad Carlos III de Madrid, Leganes, Spain.
  • Vespignani A; Connection Science, Institute for Data Science and Society, MIT, Cambridge, MA, USA.
  • Farmer JD; CENTAI Institute, Turin, Italy.
Nat Hum Behav ; 8(2): 264-275, 2024 Feb.
Article en En | MEDLINE | ID: mdl-37973827
Despite the global impact of the coronavirus disease 2019 pandemic, the question of whether mandated interventions have similar economic and public health effects as spontaneous behavioural change remains unresolved. Addressing this question, and understanding differential effects across socioeconomic groups, requires building quantitative and fine-grained mechanistic models. Here we introduce a data-driven, granular, agent-based model that simulates epidemic and economic outcomes across industries, occupations and income levels. We validate the model by reproducing key outcomes of the first wave of coronavirus disease 2019 in the New York metropolitan area. The key mechanism coupling the epidemic and economic modules is the reduction in consumption due to fear of infection. In counterfactual experiments, we show that a similar trade-off between epidemic and economic outcomes exists both when individuals change their behaviour due to fear of infection and when non-pharmaceutical interventions are imposed. Low-income workers, who perform in-person occupations in customer-facing industries, face the strongest trade-off.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Nat Hum Behav Año: 2024 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
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XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Nat Hum Behav Año: 2024 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Reino Unido