Open Access

ARTICLE

Is Social Distancing, and Quarantine Effective in Restricting COVID-19 Outbreak? Statistical Evidences from Wuhan, China

by Salman A. Cheema¹, Tanveer Kifayat², Abdu R. Rahman², Umair Khan³, A. Zaib⁴, Ilyas Khan^5,*, Kottakkaran Sooppy Nisar⁶

1 School of Mathematical and Physical Sciences, University of Newcastle, Newcastle, Australia
2 Department of Statistics, Quaid-i-Azam University Islamabad, Islamabad, Pakistan
3 Department of Mathematics and Social Sciences, Sukkur IBA University, Sukkur, 65200, Pakistan
4 Department of Mathematical Sciences, Federal Urdu University of Arts, Science & Technology, Gulshan-e-Iqbal, Karachi, Pakistan
5 Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City, Vietnam
6 Department of Mathematics, College of Arts and Sciences, Wadi Aldawaser, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia

* Corresponding Author: Ilyas Khan. Email:

(This article belongs to the Special Issue: Mathematical aspects of the Coronavirus Disease 2019 (COVID-19): Analysis and Control)

Computers, Materials & Continua 2021, 66(2), 1977-1985. https://doi.org/10.32604/cmc.2020.012096

Received 14 June 2020; Accepted 07 July 2020; Issue published 26 November 2020

Abstract

The flow of novel coronavirus (COVID-19) has affected almost every aspect of human life around the globe. Being the emerging ground and early sufferer of the virus, Wuhan city-data remains a case of multifold significance. Further, it is of notable importance to explore the impact of unique and unprecedented public health response of Chinese authorities—the extreme lockdown of the city. In this research, we investigate the statistical nature of the viral transmission concerning social distancing, extreme quarantine, and robust lockdown interventions. We observed highly convincing and statistically significant evidences in favor of quarantine and social distancing approaches. These findings might help countries, now facing, or likely to face the wave of the virus. We analyzed Wuhan-based data of “number of deaths” and “confirmed cases,” extracted from China CDC weekly database, dated from February 13, 2020, to March 24, 2020. To estimate the underlying group structure, the assembled data is further sub-divided into three blocks, each consists of two weeks. Thus, the complete data set is studied in three phases, such as, phase 1 (Ph 1) = February 13, 2020, to February 26, 2020; phase 2 (Ph 2) = February 27, 2020 to March 11, 2020; and phase 3 (Ph 3) = March 12, 2020 to March 24, 2020. We observed the overall median proportion of deaths in those six weeks remained 0.0127. This estimate is highly influenced by Ph1, when the early flaws of weak health response were still prevalent. Over the time, we witnessed a median decline of 92.12% in the death proportions. Moreover, a non-parametric version of the variability analysis of death data, estimated that the average rank of reported proportions in Ph 3 remained 7, which was 20.5 in Ph 2, and stayed 34.5 in the first phase. Similar patterns were observed, when studying the confirmed cases data. We estimated the overall median of the proportion of confirmed cases in Wuhan as 0.0041, which again, is highly inclined towards Ph 1 and Ph 2. We also witnessed minimum average rank proportions for Ph 3, such as 7, which was noticeably lower than Ph 2, 21.71, and Ph 1, 32.29. Moreover, the varying degree of clustering indicates that the effectiveness of quarantine based policies is time-dependent. In general, the decline in coronavirus transmission in Wuhan significantly coincides with the lockdown.

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