Assessing the mechanism of citywide test-trace-isolate Zero-COVID policy and exit strategy of COVID-19 pandemic

Pei Yuan; Yi Tan; Liu Yang; Elena Aruffo; Nicholas H Ogden; Guojing Yang; Haixia Lu; Zhigui Lin; Weichuan Lin; Wenjun Ma; Meng Fan; Kaifa Wang; Jianhe Shen; Tianmu Chen; Huaiping Zhu

doi:10.1186/s40249-022-01030-7

Assessing the mechanism of citywide test-trace-isolate Zero-COVID policy and exit strategy of COVID-19 pandemic

Infect Dis Poverty. 2022 Oct 4;11(1):104. doi: 10.1186/s40249-022-01030-7.

Authors

Pei Yuan^#^{1

2}, Yi Tan^#^{1

2}, Liu Yang^#^{1

2

3}, Elena Aruffo^#^{1

2}, Nicholas H Ogden^{2

4}, Guojing Yang⁵, Haixia Lu⁶, Zhigui Lin⁷, Weichuan Lin⁸, Wenjun Ma^{9

10}, Meng Fan³, Kaifa Wang¹¹, Jianhe Shen⁸, Tianmu Chen¹², Huaiping Zhu^{13

14}

Affiliations

¹ Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada.
² Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada.
³ School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, China.
⁴ Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Canada.
⁵ Key Laboratory of Tropical Translational Medicine of Ministry of Education and School of Tropical Medicine and Laboratory Medicine, The First Affiliated Hospital of Hainan Medical University, Hainan Medical University, Haikou, Hainan, China. guojingyang@hotmail.com.
⁶ School of Arts and Science, Suqian University, Suqian, Jiangsu, China.
⁷ School of Mathematical Science, Yangzhou University, Yangzhou, Jiangsu, China.
⁸ School of Mathematics and Statistics, Fujian Normal University, Fuzhou, Fujian, China.
⁹ Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, Guangdong, China.
¹⁰ Disease Control and Prevention Institute, Jinan University, Guangzhou, Guangdong, China.
¹¹ School of Mathematics and Statistics, Southwest University, Chongqing, China.
¹² School of Public Health and State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Xiamen University, Xiamen, Fujian, China.
¹³ Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada. huaiping@yorku.ca.
¹⁴ Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada. huaiping@yorku.ca.

^# Contributed equally.

Abstract

Background: Countries that aimed for eliminating the cases of COVID-19 with test-trace-isolate policy are found to have lower infections, deaths, and better economic performance, compared with those that opted for other mitigation strategies. However, the continuous evolution of new strains has raised the question of whether COVID-19 eradication is still possible given the limited public health response capacity and fatigue of the epidemic. We aim to investigate the mechanism of the Zero-COVID policy on outbreak containment, and to explore the possibility of eradication of Omicron transmission using the citywide test-trace-isolate (CTTI) strategy.

Methods: We develop a compartmental model incorporating the CTTI Zero-COVID policy to understand how it contributes to the SARS-CoV-2 elimination. We employ our model to mimic the Delta outbreak in Fujian Province, China, from September 10 to October 9, 2021, and the Omicron outbreak in Jilin Province, China for the period from March 1 to April 1, 2022. Projections and sensitivity analyses were conducted using dynamical system and Latin Hypercube Sampling/ Partial Rank Correlation Coefficient (PRCC).

Results: Calibration results of the model estimate the Fujian Delta outbreak can end in 30 (95% confidence interval CI: 28-33) days, after 10 (95% CI: 9-11) rounds of citywide testing. The emerging Jilin Omicron outbreak may achieve zero COVID cases in 50 (95% CI: 41-57) days if supported with sufficient public health resources and population compliance, which shows the effectiveness of the CTTI Zero-COVID policy.

Conclusions: The CTTI policy shows the capacity for the eradication of the Delta outbreaks and also the Omicron outbreaks. Nonetheless, the implementation of radical CTTI is challenging, which requires routine monitoring for early detection, adequate testing capacity, efficient contact tracing, and high isolation compliance, which constrain its benefits in regions with limited resources. Moreover, these challenges become even more acute in the face of more contagious variants with a high proportion of asymptomatic cases. Hence, in regions where CTTI is not possible, personal protection, public health control measures, and vaccination are indispensable for mitigating and exiting the COVID-19 pandemic.

Keywords: COVID-19; Citywide testing; Exit strategy; Test-trace-isolate; Transmission model; Zero-COVID policy.

MeSH terms

COVID-19* / epidemiology
COVID-19* / prevention & control
Contact Tracing / methods
Humans
Pandemics / prevention & control
Policy
SARS-CoV-2