Association between ambient temperature and COVID-19 infection in 122 cities from China

Jingui Xie, Yongjian Zhu

Research output: Contribution to journalArticlepeer-review

575 Scopus citations

Abstract

Background: Coronavirus disease 2019 (COVID-19) has become a severe public health problem globally. Both epidemiological and laboratory studies have shown that ambient temperature could affect the transmission and survival of coronaviruses. This study aimed to determine whether the temperature is an essential factor in the infection caused by this novel coronavirus. Methods: Daily confirmed cases and meteorological factors in 122 cities were collected between January 23, 2020, to February 29, 2020. A generalized additive model (GAM) was applied to explore the nonlinear relationship between mean temperature and COVID-19 confirmed cases. We also used a piecewise linear regression to determine the relationship in detail. Results: The exposure-response curves suggested that the relationship between mean temperature and COVID-19 confirmed cases was approximately linear in the range of <3 °C and became flat above 3 °C. When mean temperature (lag0–14) was below 3 °C, each 1 °C rise was associated with a 4.861% (95% CI: 3.209–6.513) increase in the daily number of COVID-19 confirmed cases. These findings were robust in our sensitivity analyses. Conclusions: Our results indicate that mean temperature has a positive linear relationship with the number of COVID-19 cases with a threshold of 3 °C. There is no evidence supporting that case counts of COVID-19 could decline when the weather becomes warmer, which provides useful implications for policymakers and the public.

Original languageEnglish
Article number138201
JournalScience of the Total Environment
Volume724
DOIs
StatePublished - 1 Jul 2020
Externally publishedYes

Keywords

  • COVID-19
  • China
  • Generalized additive model
  • Novel coronavirus pneumonia
  • Temperature

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