Lai Hao, Tao Yusha, Shen Mingwang, Li Rui, Zou Maosheng, Zhang Leilei, Zhang Lei
China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China.
SESH (Social Entrepreneurship to Spur Health) Global, University of North Carolina at Chapel Hill Project-China, Guangzhou 510095, China.
Pathogens. 2022 May 13;11(5):576. doi: 10.3390/pathogens11050576.
It is still uncertain how the epidemic characteristics of COVID-19 in its early phase and subsequent waves contributed to the pre-delta epidemic size in the United States. We identified the early and subsequent characteristics of the COVID-19 epidemic and the correlation between these characteristics and the pre-delta epidemic size. Most (96.1% (49/51)) of the states entered a fast-growing phase before the accumulative number of cases reached (30). The days required for the number of confirmed cases to increase from 30 to 100 was 5.6 (5.1−6.1) days. As of 31 March 2021, all 51 states experienced at least 2 waves of COVID-19 outbreaks, 23.5% (12/51) experienced 3 waves, and 15.7% (8/51) experienced 4 waves, the epidemic size of COVID-19 was 19,275−3,669,048 cases across the states. The pre-delta epidemic size was significantly correlated with the duration from 30 to 100 cases (p = 0.003, r = −0.405), the growth rate of the fast-growing phase (p = 0.012, r = 0.351), and the peak cases in the subsequent waves (K1 (p < 0.001, r = 0.794), K2 (p < 0.001, r = 0.595), K3 (p < 0.001, r = 0.977), and K4 (p = 0.002, r = 0.905)). We observed that both early and subsequent epidemic characteristics contribute to the pre-delta epidemic size of COVID-19. This identification is important to the prediction of the emerging viral infectious diseases in the primary stage.
新冠病毒病（COVID-19）早期阶段及后续各波疫情的流行特征如何促成美国德尔塔变异株出现之前的疫情规模，目前仍不确定。我们确定了COVID-19疫情的早期及后续特征，以及这些特征与德尔塔变异株出现之前的疫情规模之间的相关性。大多数（96.1%（49/51））州在累计病例数达到30例之前就进入了快速增长阶段。确诊病例数从30例增加到100例所需天数为5.6（5.1−6.1）天。截至2021年3月31日，所有51个州均至少经历了2波COVID-19疫情暴发，23.5%（12/51）经历了3波，15.7%（8/51）经历了4波，各州COVID-19疫情规模为19275−3669048例。德尔塔变异株出现之前的疫情规模与30至100例病例的持续时间显著相关（p = 0.003，r = -0.405）、快速增长阶段的增长率显著相关（p = 0.012，r = 0.351），以及后续各波的病例峰值显著相关（K1（p < 0.001，r = 0.794）、K2（p < 0.001，r = 0.595）、K3（p < 0.001，r = 0.977）和K4（p = 0.002，r = 0.905））。我们观察到，早期及后续疫情特征均对COVID-19德尔塔变异株出现之前的疫情规模有影响。这一发现对于预测新发病毒传染病的初级阶段很重要。
