Selected article for: "basic reproduction number and disease system"

Author: Zhang, Zhaowang; Kong, Lingming; Lin, Hualiang; Zhu, Guanghu
Title: Modeling coupling dynamics between the transmission, intervention of COVID-19 and economic development
  • Cord-id: u89jhk06
  • Document date: 2021_8_8
  • ID: u89jhk06
    Snippet: Current explosive outbreak of the novel coronavirus (COVID-19) pandemic is posing serious threats to public health and economics around the world. To clarify the coupling mechanism between this disease and economic development, a new dynamical system is established by ordinary differential equations (ODEs). It is theoretically proved that the basic reproduction number is a nonlinear combination of parameters regarding disease transmission, intervention and economy effect, which totally determine
    Document: Current explosive outbreak of the novel coronavirus (COVID-19) pandemic is posing serious threats to public health and economics around the world. To clarify the coupling mechanism between this disease and economic development, a new dynamical system is established by ordinary differential equations (ODEs). It is theoretically proved that the basic reproduction number is a nonlinear combination of parameters regarding disease transmission, intervention and economy effect, which totally determines the stability of the disease-free and endemic equilibria. Further analyses indicate the existence of interaction and mutual restraint among transmissibility, quarantine and economics, in which (1) COVID-19 would cause a long-term impact on halting economic progress; (2) strong coupling of COVID-19 and economics would easily trigger disease outbreak, cause more human infections and alleviate the intervention effects of quarantine; and (3) there exists optimal strategy of time-varying quarantine for disease control and economic development. It is highlighted that adaptive isolation (rather than constant isolation) of at-risk population (rather than random individuals) is highly effective in reducing morbidity at the cost of least economic loss.

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