Quantitative analysis of non-pharmaceutical interventions during Shanghai COVID-19 outbreak

Yunlong Zhu

doi:10.1117/12.3000291

7 September 2023 Quantitative analysis of non-pharmaceutical interventions during Shanghai COVID-19 outbreak

Yunlong Zhu

Proceedings Volume 12789, International Conference on Modern Medicine and Global Health (ICMMGH 2023); 127892L (2023) https://doi.org/10.1117/12.3000291
Event: International Conference on Modern Medicine and Global Health (ICMMGH 2023), 2023, Oxford, United Kingdom

Abstract

The Shanghai COVID-19 outbreak from March to May 2022 was the largest local epidemic in China after the Wuhan outbreak in 2020. Studying the non-pharmaceutical interventions (NPIs) taken by the Shanghai government will provide valuable experience for other large cities to control the epidemic. In this paper, a new SQUPR model is constructed to quantitatively measure the effectiveness of NPIs in different phases of Shanghai outbreak. Two important parameters, screening index and moving index are proposed to reflect the government’s ability to identify and isolate patients and the severity of travel restrictions. By defining the error function, we transformed the parameter estimation problem into a nonlinear optimization problem, and obtained the values of the parameters by using the Particle Swarm Optimization algorithm. We calculated the effective reproduction number and found that it shares the same trend with the moving index. The simulation results of some hypothetical situations show that taking effective interventions as early as possible can effectively avoid the outbreak of the epidemic.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yunlong Zhu "Quantitative analysis of non-pharmaceutical interventions during Shanghai COVID-19 outbreak", Proc. SPIE 12789, International Conference on Modern Medicine and Global Health (ICMMGH 2023), 127892L (7 September 2023); https://doi.org/10.1117/12.3000291

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KEYWORDS

COVID 19

Data modeling

Particle swarm optimization

Reflection

Nucleic acids

Computer simulations

Particles

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