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Comment
. 2020 Aug 27;56(2):2001253.
doi: 10.1183/13993003.01253-2020. Print 2020 Aug.

A re-analysis in exploring the association between temperature and COVID-19 transmissibility: an ecological study with 154 Chinese cities

Jinjun Ran  1   2 , Shi Zhao  3   4   2 , Lefei Han  5 , Gengze Liao  3 , Kai Wang  6 , Maggie H Wang  3   4 , Daihai He  7
Affiliations
Comment

A re-analysis in exploring the association between temperature and COVID-19 transmissibility: an ecological study with 154 Chinese cities

Jinjun Ran et al. Eur Respir J. .

Abstract

In this national ecological study across 154 Chinese cities, the ambient temperature was found to have a nonlinear negative association with COVID-19 transmissibility https://bit.ly/3esw8rc

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Conflict of interest statement

Conflict of interest: J. Ran has nothing to disclose. Conflict of interest: S. Zhao has nothing to disclose. Conflict of interest: L. Han has nothing to disclose. Conflict of interest: G. Liao has nothing to disclose. Conflict of interest: K. Wang has nothing to disclose. Conflict of interest: M.H. Wang is a shareholder of Beth Bioinformatics Co., Ltd. Conflict of interest: D. He reports grants from Alibaba (China) Co. Ltd collaborative research grant, outside the submitted work.

Figures

FIGURE 1
FIGURE 1
Association between temperature and coronavirus disease 2019 transmissibility (R0) across 154 Chinese cities. a) Multiple linear regression (p=0.178; AIC=53.82). b) Linear regression with a discontinuous point at 7°C (p=0.049 when temperature is over 7°C; AIC=51.78). The inserted panel shows the likelihood profile of the discontinuous point and its maximum likelihood estimate (MLE). The red triangle is the MLE at 7°C, and the grey triangles are the input samples. c) Spline regression with a knot at 7°C (AIC=53.41). AIC: Akaike information criterion.
See this image and copyright information in PMC

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References

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