Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope

Lei Zhang, Yusha Tao, Jing Wang, Jason J. Ong, Weiming Tang, Maosheng Zou, Lu Bai, Miao Ding, Mingwang Shen, Guihua Zhuang, Christopher K. Fairley

Research output: Contribution to journalArticleResearchpeer-review

2 Citations (Scopus)

Abstract

Objectives: The mostly-resolved first wave of the COVID-19 epidemic in China provided a unique opportunity to investigate how the initial characteristics of the COVID-19 outbreak predict its subsequent magnitude. Methods: We collected publicly available COVID-19 epidemiological data from 436 Chinese cities from 16th January–15th March 2020. Based on 45 cities that reported >100 confirmed cases, we examined the correlation between early-stage epidemic characteristics and subsequent epidemic magnitude. Results: We identified a transition point from a slow- to a fast-growing phase for COVID-19 at 5.5 (95% CI, 4.6–6.4) days after the first report, and 30 confirmed cases marked a critical threshold for this transition. The average time for the number of confirmed cases to increase from 30 to 100 (time from 30-to-100) was 6.6 (5.3–7.9) days, and the average case-fatality rate in the first 100 confirmed cases (CFR-100) was 0.8% (0.2–1.4%). The subsequent epidemic size per million population was significantly associated with both of these indicators. We predicted a ranking of epidemic size in the cities based on these two indicators and found it highly correlated with the actual classification of epidemic size. Conclusions: Early epidemic characteristics are important indicators for the size of the entire epidemic.

Original languageEnglish
Pages (from-to)219-224
Number of pages6
JournalInternational Journal of Infectious Diseases
Volume97
DOIs
Publication statusPublished - Aug 2020

Keywords

  • COVID-19
  • Early characteristics
  • Epidemic size
  • SARS-COV-2

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