tetano
Editor, Senior Moderator
Nat Hum Behav
. 2023 Nov 16.
doi: 10.1038/s41562-023-01747-x. Online ahead of print. The unequal effects of the health-economy trade-off during the COVID-19 pandemic
Marco Pangallo[SUP] 1 [/SUP], Alberto Aleta[SUP] 2 [/SUP], R Maria Del Rio-Chanona[SUP] 3 [/SUP], Anton Pichler[SUP] 3 [/SUP], David Martín-Corral[SUP] 4 [/SUP], Matteo Chinazzi[SUP] 5 6 [/SUP], François Lafond[SUP] 7 [/SUP], Marco Ajelli[SUP] 8 [/SUP], Esteban Moro[SUP] 4 9 [/SUP], Yamir Moreno[SUP] 10 2 3 [/SUP], Alessandro Vespignani[SUP] 5 [/SUP], J Doyne Farmer[SUP] 7 11 [/SUP]
Affiliations
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.
. 2023 Nov 16.
doi: 10.1038/s41562-023-01747-x. Online ahead of print. The unequal effects of the health-economy trade-off during the COVID-19 pandemic
Marco Pangallo[SUP] 1 [/SUP], Alberto Aleta[SUP] 2 [/SUP], R Maria Del Rio-Chanona[SUP] 3 [/SUP], Anton Pichler[SUP] 3 [/SUP], David Martín-Corral[SUP] 4 [/SUP], Matteo Chinazzi[SUP] 5 6 [/SUP], François Lafond[SUP] 7 [/SUP], Marco Ajelli[SUP] 8 [/SUP], Esteban Moro[SUP] 4 9 [/SUP], Yamir Moreno[SUP] 10 2 3 [/SUP], Alessandro Vespignani[SUP] 5 [/SUP], J Doyne Farmer[SUP] 7 11 [/SUP]
Affiliations
- PMID: 37973827
- DOI: 10.1038/s41562-023-01747-x
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.