The Impact of Multi-level Interventions on the Second-wave SARS-CoV-2 Transmission in China

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2022 Sep 16

PMID 36112630

Authors

Yuanchen He

Yinzi Chen

Lin Yang

Ying Zhou

Run Ye

Xiling Wang

Affiliations

Soon will be listed here.

Abstract

Background: A re-emergence of COVID-19 occurred in the northeast of China in early 2021. Different levels of non-pharmaceutical interventions, from mass testing to city-level lockdown, were implemented to contain the transmission of SARS-CoV-2. Our study is aimed to evaluate the impact of multi-level control measures on the second-wave SARS-CoV-2 transmission in the most affected cities in China.

Methods: Five cities with over 100 reported COVID-19 cases within one month from Dec 2020 to Feb 2021 were included in our analysis. We fitted the exponential growth model to estimate basic reproduction number (R0), and used a Bayesian approach to assess the dynamics of the time-varying reproduction number (Rt). We fitted linear regression lines on Rt estimates for comparing the decline rates of Rt across cities, and the slopes were tested by analysis of covariance. The effect of non-pharmaceutical interventions (NPIs) was quantified by relative Rt reduction and statistically compared by analysis of variance.

Results: A total of 2,609 COVID-19 cases were analyzed in this study. We estimated that R0 all exceeded 1, with the highest value of 3.63 (1.36, 8.53) in Haerbin and the lowest value of 2.45 (1.44, 3.98) in Shijiazhuang. Downward trends of Rt were found in all cities, and the starting time of Rt < 1 was around the 12th day of the first local COVID-19 cases. Statistical tests on regression slopes of Rt and effect of NPIs both showed no significant difference across five cities (P = 0.126 and 0.157).

Conclusion: Timely implemented NPIs could control the transmission of SARS-CoV-2 with low-intensity measures for places where population immunity has not been established.

Citing Articles

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References

Keeling M, Hollingsworth T, Read J . Efficacy of contact tracing for the containment of the 2019 novel coronavirus (COVID-19). J Epidemiol Community Health. 2020; 74(10):861-866. PMC: 7307459. DOI: 10.1136/jech-2020-214051. View

Galvani A, May R . Epidemiology: dimensions of superspreading. Nature. 2005; 438(7066):293-5. PMC: 7095140. DOI: 10.1038/438293a. View

Ge Y, Chen Z, Handel A, Martinez L, Xiao Q, Li C . The impact of social distancing, contact tracing, and case isolation interventions to suppress the COVID-19 epidemic: A modeling study. Epidemics. 2021; 36:100483. PMC: 8275486. DOI: 10.1016/j.epidem.2021.100483. View

Wang L, Wang J, Zhao H, Shi Y, Wang K, Wu P . Modelling and assessing the effects of medical resources on transmission of novel coronavirus (COVID-19) in Wuhan, China. Math Biosci Eng. 2020; 17(4):2936-2949. DOI: 10.3934/mbe.2020165. View

Leung K, Wu J, Leung G . Real-time tracking and prediction of COVID-19 infection using digital proxies of population mobility and mixing. Nat Commun. 2021; 12(1):1501. PMC: 7940469. DOI: 10.1038/s41467-021-21776-2. View

Wu J, Leung K, Leung G . Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. Lancet. 2020; 395(10225):689-697. PMC: 7159271. DOI: 10.1016/S0140-6736(20)30260-9. View

Thompson R, Stockwin J, van Gaalen R, Polonsky J, Kamvar Z, Demarsh P . Improved inference of time-varying reproduction numbers during infectious disease outbreaks. Epidemics. 2019; 29:100356. PMC: 7105007. DOI: 10.1016/j.epidem.2019.100356. View

Chung P, Chan T . Impact of physical distancing policy on reducing transmission of SARS-CoV-2 globally: Perspective from government's response and residents' compliance. PLoS One. 2021; 16(8):e0255873. PMC: 8354459. DOI: 10.1371/journal.pone.0255873. View

Kucharski A, Russell T, Diamond C, Liu Y, Edmunds J, Funk S . Early dynamics of transmission and control of COVID-19: a mathematical modelling study. Lancet Infect Dis. 2020; 20(5):553-558. PMC: 7158569. DOI: 10.1016/S1473-3099(20)30144-4. View

10.

Griffin S . Covid-19: Test and trace programmes are important but no silver bullet, say scientists. BMJ. 2020; 369:m2151. DOI: 10.1136/bmj.m2151. View

11.

Xu S, Li Y . Beware of the second wave of COVID-19. Lancet. 2020; 395(10233):1321-1322. PMC: 7194658. DOI: 10.1016/S0140-6736(20)30845-X. View

12.

Haug N, Geyrhofer L, Londei A, Dervic E, Desvars-Larrive A, Loreto V . Ranking the effectiveness of worldwide COVID-19 government interventions. Nat Hum Behav. 2020; 4(12):1303-1312. DOI: 10.1038/s41562-020-01009-0. View

13.

Pan A, Liu L, Wang C, Guo H, Hao X, Wang Q . Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China. JAMA. 2020; 323(19):1915-1923. PMC: 7149375. DOI: 10.1001/jama.2020.6130. View

14.

Cori A, Ferguson N, Fraser C, Cauchemez S . A new framework and software to estimate time-varying reproduction numbers during epidemics. Am J Epidemiol. 2013; 178(9):1505-12. PMC: 3816335. DOI: 10.1093/aje/kwt133. View

15.

Wallinga J, Lipsitch M . How generation intervals shape the relationship between growth rates and reproductive numbers. Proc Biol Sci. 2007; 274(1609):599-604. PMC: 1766383. DOI: 10.1098/rspb.2006.3754. View

16.

Lemey P, Ruktanonchai N, Hong S, Colizza V, Poletto C, Van den Broeck F . Untangling introductions and persistence in COVID-19 resurgence in Europe. Nature. 2021; 595(7869):713-717. PMC: 8324533. DOI: 10.1038/s41586-021-03754-2. View

17.

Gountas I, Quattrocchi A, Mamais I, Tsioutis C, Christaki E, Fokianos K . Effect of public health interventions during the first epidemic wave of COVID-19 in Cyprus: a modelling study. BMC Public Health. 2021; 21(1):1898. PMC: 8526096. DOI: 10.1186/s12889-021-11945-9. View

18.

Tuite A, Fisman D . Reporting, Epidemic Growth, and Reproduction Numbers for the 2019 Novel Coronavirus (2019-nCoV) Epidemic. Ann Intern Med. 2020; 172(8):567-568. PMC: 7077751. DOI: 10.7326/M20-0358. View

19.

Aleta A, Martin-Corral D, Pastore Y Piontti A, Ajelli M, Litvinova M, Chinazzi M . Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19. Nat Hum Behav. 2020; 4(9):964-971. PMC: 7641501. DOI: 10.1038/s41562-020-0931-9. View

20.

Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y . Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. N Engl J Med. 2020; 382(13):1199-1207. PMC: 7121484. DOI: 10.1056/NEJMoa2001316. View