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Optimal strategies for coordinating infection control and socio-economic activities.
Li, Tangjuan; Xiao, Yanni.
  • Li T; School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, PR China.
  • Xiao Y; School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, PR China.
Math Comput Simul ; 207: 533-555, 2023 May.
Article in English | MEDLINE | ID: covidwho-2181397
ABSTRACT
It becomes challenging to identify feasible control strategies for simultaneously relaxing the countermeasures and containing the Covid-19 pandemic, given China's huge population size, high susceptibility, persist vaccination waning, and relatively weak strength of health systems. We propose a novel mathematical model with waning of immunity and solve the optimal control problem, in order to provide an insight on how much detecting and social distancing are required to coordinate socio-economic activities and epidemic control. We obtain the optimal intensity of countermeasures, i.e., the dynamic nucleic acid screening and social distancing, under which the health system is functioning normally and people can engage in a certain level of socio-economic activities. We find that it is the isolation capacity or the restriction of the case fatality rate (CFR) rather than the hospital capacity that mainly determines the optimal strategies. And the solved optimal controls under quarterly CFR restrictions exhibit oscillations. It is worth noticing that, if without considering booster or very low booster rate, the optimal strategy is a "on-off" mode, alternating between lock down and opening with certain social distancing, which reflects the importance and necessity of China's static management on a certain area during Covid-19 outbreak. The findings suggest some feasible paths to smoothly transit from the Covid-19 pandemic to an endemic phase.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Topics: Vaccines Language: English Journal: Math Comput Simul Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Topics: Vaccines Language: English Journal: Math Comput Simul Year: 2023 Document Type: Article