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CDC (Cindy and David's Conversations) Game: Advising President to Survive Pandemic.
Ma, Zhanshan Sam; Yang, Liexun.
  • Ma ZS; Computational Biology and Medical Ecology Lab,State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences.
  • Yang L; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences Kunming, 650223 China.
iScience ; : 107079, 2023 Jun 09.
Article in English | MEDLINE | ID: covidwho-20239031
ABSTRACT
Ongoing debates on anti-COVID19 policies have been focused on coexistence-with vs. zero-out (virus) strategies, which can be simplified as "always open (AO)" vs. "always closed (AC)." We postulate that a middle ground, dubbed LOHC (low-risk-open and high-risk-closed), is likely favorable, precluding obviously irrational HOLC (high-risk-open and low-risk-closed). From a meta-strategy perspective, these four policies cover the full spectrum of anti-pandemic policies. By emulating the reality of anti-pandemic policies today, the study aims to identify possible cognitive gaps and traps by harnessing the power of evolutionary game-theoretic analysis and simulations, which suggest that (i) AO and AC seems to be "high-probability" events (0.412-0.533); (ii) counter-intuitively, the middle ground-LOHC-seems to be small-probability event (0.053), possibly mirroring its wide adoptions but broad failures. Besides devising specific policies, an equally important challenge seems to deal with often hardly avoidable policy transitions along the process from emergence, epidemic, through pandemic, to endemic state.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study / Reviews Language: English Journal: IScience Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study / Reviews Language: English Journal: IScience Year: 2023 Document Type: Article