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Threshold conditions for curbing COVID‑19 with a dynamic zero‑case policy derived from 101 outbreaks in China

Threshold conditions for curbing COVID‑19 with a dynamic zero‑case policy derived from 101 outbreaks in China

Tang, Sanyi, Wang, Xia, Tang, Biao, He, Sha, Huang, Chenxi, Shao, Yiming, Xiao, Yanni and Cheke, Robert ORCID logoORCID: https://orcid.org/0000-0002-7437-1934 (2023) Threshold conditions for curbing COVID‑19 with a dynamic zero‑case policy derived from 101 outbreaks in China. BMC Public Health, 23:1084. pp. 1-12. ISSN 1471-2458 (doi:10.1186/s12889-023-16009-8)

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Abstract

By 31 May 2022, original/Alpha, Delta and Omicron strains induced 101 outbreaks of COVID-19 in mainland China. Most outbreaks were cleared by combining non-pharmaceutical interventions (NPIs) with vaccines, but continuous virus variations challenged the dynamic zero-case policy (DZCP), posing questions of what are the prerequisites and threshold levels for success? And what are the independent effects of vaccination in each outbreak? Using a modified classic infectious disease dynamic model and an iterative relationship for new infections per day, the effectiveness
of vaccines and NPIs was deduced, from which the independent effectiveness of vaccines was derived. There was a negative correlation between vaccination coverage rates and virus transmission. For the Delta strain, a 61.8% increase in the vaccination rate (VR) reduced the control reproduction number (CRN) by about 27%. For the Omicron strain, a 20.43% increase in VR, including booster shots, reduced the CRN by 42.16%. The implementation speed of NPIs against the original/Alpha strain was faster than the virus’s transmission speed, and vaccines significantly accelerated the DZCP against the Delta strain. The CRN ( Rc1 ) during the exponential growth phase and the peak time and intensity of NPIs were key factors affecting a comprehensive theoretical threshold condition for DZCP success, illustrated by contour diagrams for the CRN under different conditions. The DZCP maintained the Rc1 of 101 outbreaks below the
safe threshold level, but the strength of NPIs was close to saturation especially for Omicron, and there was little room for improvement. Only by curbing the rise in the early stage and shortening the exponential growth period could clearing be achieved quickly. Strengthening China’s vaccine immune barrier can improve China’s ability to prevent and control epidemics and provide greater scope for the selection and adjustment of NPIs. Otherwise, there will be rapid rises in infection rates and an extremely high peak and huge pressure on the healthcare system, and a potential increase in excess mortality.

Item Type: Article
Uncontrolled Keywords: COVID-19; non-pharmaceutical interventions; mathematical model; epidemic waves; mitigation; China
Subjects: H Social Sciences > H Social Sciences (General)
Q Science > QR Microbiology > QR355 Virology
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Faculty / School / Research Centre / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Natural Resources Institute
Faculty of Engineering & Science > Natural Resources Institute > Agriculture, Health & Environment Department
Faculty of Engineering & Science > Natural Resources Institute > Centre for Sustainable Agriculture 4 One Health
Faculty of Engineering & Science > Natural Resources Institute > Centre for Sustainable Agriculture 4 One Health > Behavioural Ecology
Last Modified: 27 Nov 2024 14:29
URI: http://gala.gre.ac.uk/id/eprint/42981

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