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Volume 26, Number 11—November 2020
Online Report

Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19

Matthew Biggerstaff, Benjamin J. Cowling, Zulma M. Cucunubá, Linh Dinh, Neil M. Ferguson, Huizhi Gao, Verity Hill, Natsuko Imai, Michael A. Johansson, Sarah Kada, Oliver Morgan, Ana Pastore y Piontti, Jonathan A. Polonsky, Pragati Venkata Prasad, Talia M. Quandelacy, Andrew Rambaut, Jordan W. Tappero, Katelijn A. VandemaeleComments to Author , Alessandro Vespignani, K. Lane Warmbrod, Jessica Y. Wong, and for the WHO COVID-19 Modelling Parameters Group
Author affiliations: Centers for Disease Control and Prevention, Atlanta, Georgia, USA (M. Biggerstaff, M.A. Johansson, S. Kada, P.V. Prasad, T.M. Quandelacy); University of Hong Kong, Hong Kong, China (B.J. Cowling, H. Gao, J.Y. Wong); Imperial College London, London, UK (Z.M. Cucunubá, N.M. Ferguson, N. Imai); World Health Organization, Geneva, Switzerland (L. Dinh, O. Morgan, J.A. Polonsky, J.W. Tappero, K.A. Vandemaele, K.L. Warmbrod); University of Edinburgh, Edinburgh, Scotland, UK (V. Hill, A. Rambaut); Northeastern University, Boston, Massachusetts, USA (A. Pastore y Piontti, A. Vespignani); ISI Foundation, Turin, Italy (A. Vespignani)

Main Article

Table 2

Summary of estimates of mean evolutionary rate and most recent common ancestor of COVID-19*

Mean evolutionary rate (95% CI) MRCA (95% CI) No. genomes analyzed Clock model† Growth model Source
NA
2019 Nov 29
(Nov 8–Dec 16)
23
Strict
Constant
Rambaut, unpub. data, http://virological.org/t/phylogenetic-analysis-of-23-ncov-2019-genomes-2020-01-23/335
1.23 × 10−3 (0.56 × 10−3 to 1.98 × 10−3)
2019 Nov 21 (Oct 23–Dec 13)
51
Strict
Exponential
Duchene et al., unpub. data, http://virological.org/t/temporal-signal-and-the-evolutionary-rate-of-2019-n-cov-using-47-genomes-collected-by-feb-01-2020/379
1.29 × 10−3 (0.535 × 10−4 to 2.15 × 10−3)
2019 Nov 14 (Sep 28–Dec 13)
51
UNCL
Exponential
Duchene et al., unpub. data, http://virological.org/t/temporal-signal-and-the-evolutionary-rate-of-2019-n-cov-using-47-genomes-collected-by-feb-01-2020/379
0.9 × 10−3 (0.5 × 10−3 to 1.4 × 10−3)
2019 Dec 3 (Oct 30–Dec 17)
51
Strict
Exponential
Bedford, unpub. data, http://virological.org/t/phylodynamic-estimation-of-incidence-and-prevalence-of-novel-coronavirus-ncov-infections-through-time/391
0.92 × 10−3 (0.33 × 10−3 to 1.46×10−3)
2019 Nov 29 (Oct 28–Dec 20)
75
Strict
Exponential
Rambaut, unpub. data, http://virological.org/t/phylodynamic-analysis-176-genomes-6-mar-2020/356. Accessed March 4, 2020
1.04 × 10−3 (0.71 × 10−3 to 1. 4 ×10−3)
2019 Dec 3 (Nov 16–Dec 17)
116
Strict
Exponential
Hill and Rambaut, unpub. data, http://virological.org/t/phylodynamic-analysis-of-sars-cov-2-update-2020-03-06/420
7.41×10−4 (4.91 × 10−4 to 1.02 × 10−3) 2019 Nov 27 (Nov 7–Dec 11) 128 Strict Birth–death model Sciré et al., unpub. data, http://virological.org/t/update-2-evolutionary-epidemiological-analysis-of-128-genomes/423

*MRCA, most recent common ancestor; NA, not applicable; UNCL, uncorrelated.
†The clock model is a technique that uses the mutation rate to estimate the time of emergence (48).

Main Article

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1All authors contributed equally to this article.

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