Non-linear link between temperature difference and COVID-19: Excluding the effect of population density

  • Yongmei Ding Department of Mathematics and Statistics, College of Science, Wuhan University of Science and Technology, Wuhan, Hubei Province, China
  • Liyuan Gao Department of Mathematics and Statistics, College of Science, Wuhan University of Science and Technology, Wuhan, Hubei Province, China
  • Ning-Yi Shao Faculty of Health Sciences, University of Macau, Macau SAR, China
Keywords: Coronavirus, temperature difference, nonlinearity, population density

Abstract

Introduction: The spatiotemporal patterns of Corona Virus Disease 2019 (COVID-19) is detected in the United States, which shows temperature difference (TD) with cumulative hysteresis effect significantly changes the daily new confirmed cases after eliminating the interference of population density.

Methodology: The nonlinear feature of updated cases is captured through Generalized Additive Mixed Model (GAMM) with threshold points; Exposure-response curve suggests that daily confirmed cases is changed at the different stages of TD according to the threshold points of piecewise function, which traces out the rule of updated cases under different meteorological condition.

Results: Our results show that the confirmed cases decreased by 0.390% (95% CI: -0.478 ~ -0.302) for increasing each one degree of TD if TD is less than 11.5°C; It will increase by 0.302% (95% CI: 0.215 ~ 0.388) for every 1°C increase in the TD (lag0-4) at the interval [11.5, 16]; Meanwhile the number of newly confirmed COVID-19 cases will increase by 0.321% (95% CI: 0.142 ~ 0.499) for every 1°C increase in the TD (lag0-4) when the TD (lag0-4) is over 16°C, and the most fluctuation occurred on Sunday. The results of the sensitivity analysis confirmed our model robust.

Conclusions: In US, this interval effect of TD reminds us that it is urgent to control the spread and infection of COVID-19 when TD becomes greater in autumn and the ongoing winter.

Published
2021-03-07
How to Cite
1.
Ding Y, Gao L, Shao N-Y (2021) Non-linear link between temperature difference and COVID-19: Excluding the effect of population density. J Infect Dev Ctries 15:230-236. doi: 10.3855/jidc.13926
Section
Coronavirus Pandemic