A mechanism-based parameterisation scheme to investigate the association between transmission rate of COVID-19 and meteorological factors on plains in China

Changqing Lin; Alexis K.H. Lau; Jimmy C.H. Fung; Cui Guo; Jimmy W.M. Chan; David W. Yeung; Yumiao Zhang; Yacong Bo; Md Shakhaoat Hossain; Yiqian Zeng; Xiang Qian Lao

doi:10.1016/j.scitotenv.2020.140348

A mechanism-based parameterisation scheme to investigate the association between transmission rate of COVID-19 and meteorological factors on plains in China

Changqing Lin
, Alexis K.H. Lau^*
, Jimmy C.H. Fung
, Cui Guo
, Jimmy W.M. Chan
, David W. Yeung
, Yumiao Zhang
, Yacong Bo
, Md Shakhaoat Hossain
, Yiqian Zeng
, Xiang Qian Lao^*

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

67 Citations (Scopus)

Abstract

The novel coronavirus disease 2019 (COVID-19), which first emerged in Hubei province, China, has become a pandemic. However, data regarding the effects of meteorological factors on its transmission are limited and inconsistent. A mechanism-based parameterisation scheme was developed to investigate the association between the scaled transmission rate (STR) of COVID-19 and the meteorological parameters in 20 provinces/municipalities located on the plains in China. We obtained information on the scale of population migrated from Wuhan, the world epicentre of the COVID-19 outbreak, into the study provinces/municipalities using mobile-phone positioning system and big data techniques. The highest STRs were found in densely populated metropolitan areas and in cold provinces located in north-eastern China. Population density had a non-linear relationship with disease spread (linearity index, 0.9). Among various meteorological factors, only temperature was significantly associated with the STR after controlling for the effect of population density. A negative and exponential relationship was identified between the transmission rate and the temperature (correlation coefficient, −0.56; 99% confidence level). The STR increased substantially as the temperature in north-eastern China decreased below 0 °C (the STR ranged from 3.5 to 12.3 when the temperature was between −9.41 °C and −13.87 °C), whilst the STR showed less temperature dependence in the study areas with temperate weather conditions (the STR was 1.21 ± 0.57 when the temperature was above 0 °C). Therefore, a higher population density was linearly whereas a lower temperature (

Original language	English
Article number	140348
Journal	Science of the Total Environment
Volume	737
Online published	18 Jun 2020
DOIs	https://doi.org/10.1016/j.scitotenv.2020.140348
Publication status	Published - 1 Oct 2020
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2020

Funding

This work was supported by NSFC / RGC (Grant No. N_HKUST638/19 ) and the Research Grants Council of Hong Kong Government (Project No. T24/504/17). We would like to thank Institute for the Environment (IENV) and Environmental Central Facility (ENVF) of Hong Kong University of Science and Technology (HKUST) for providing atmospheric and environmental data. We thank Johns Hopkins University Center for Systems Science and Engineering (CSSE) and Baidu Inc., for managing the COVID-19 and population migration data.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Research Keywords

COVID-19
Imported scale
Meteorology
Population density
Temperature

RGC Funding Information

RGC-funded

Policy Impact

Cited in Policy Documents

Access Output

10.1016/j.scitotenv.2020.140348

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

Lin, C., Lau, A. K. H., Fung, J. C. H., Guo, C., Chan, J. W. M., Yeung, D. W., Zhang, Y., Bo, Y., Hossain, M. S., Zeng, Y., & Lao, X. Q. (2020). A mechanism-based parameterisation scheme to investigate the association between transmission rate of COVID-19 and meteorological factors on plains in China. Science of the Total Environment, 737, Article 140348. https://doi.org/10.1016/j.scitotenv.2020.140348

@article{7d1ad20668aa4d2e938d8be8f24d9c93,

title = "A mechanism-based parameterisation scheme to investigate the association between transmission rate of COVID-19 and meteorological factors on plains in China",

abstract = "The novel coronavirus disease 2019 (COVID-19), which first emerged in Hubei province, China, has become a pandemic. However, data regarding the effects of meteorological factors on its transmission are limited and inconsistent. A mechanism-based parameterisation scheme was developed to investigate the association between the scaled transmission rate (STR) of COVID-19 and the meteorological parameters in 20 provinces/municipalities located on the plains in China. We obtained information on the scale of population migrated from Wuhan, the world epicentre of the COVID-19 outbreak, into the study provinces/municipalities using mobile-phone positioning system and big data techniques. The highest STRs were found in densely populated metropolitan areas and in cold provinces located in north-eastern China. Population density had a non-linear relationship with disease spread (linearity index, 0.9). Among various meteorological factors, only temperature was significantly associated with the STR after controlling for the effect of population density. A negative and exponential relationship was identified between the transmission rate and the temperature (correlation coefficient, −0.56; 99\% confidence level). The STR increased substantially as the temperature in north-eastern China decreased below 0 °C (the STR ranged from 3.5 to 12.3 when the temperature was between −9.41 °C and −13.87 °C), whilst the STR showed less temperature dependence in the study areas with temperate weather conditions (the STR was 1.21 ± 0.57 when the temperature was above 0 °C). Therefore, a higher population density was linearly whereas a lower temperature (",

keywords = "COVID-19, Imported scale, Meteorology, Population density, Temperature",

author = "Changqing Lin and Lau, \{Alexis K.H.\} and Fung, \{Jimmy C.H.\} and Cui Guo and Chan, \{Jimmy W.M.\} and Yeung, \{David W.\} and Yumiao Zhang and Yacong Bo and Hossain, \{Md Shakhaoat\} and Yiqian Zeng and Lao, \{Xiang Qian\}",

note = "Publisher Copyright: {\textcopyright} 2020",

year = "2020",

month = oct,

day = "1",

doi = "10.1016/j.scitotenv.2020.140348",

language = "English",

volume = "737",

journal = "Science of the Total Environment",

issn = "0048-9697",

publisher = "Elsevier B.V.",

}

Lin, C, Lau, AKH, Fung, JCH, Guo, C, Chan, JWM, Yeung, DW, Zhang, Y, Bo, Y, Hossain, MS, Zeng, Y & Lao, XQ 2020, 'A mechanism-based parameterisation scheme to investigate the association between transmission rate of COVID-19 and meteorological factors on plains in China', Science of the Total Environment, vol. 737, 140348. https://doi.org/10.1016/j.scitotenv.2020.140348

A mechanism-based parameterisation scheme to investigate the association between transmission rate of COVID-19 and meteorological factors on plains in China. / Lin, Changqing; Lau, Alexis K.H.; Fung, Jimmy C.H. et al.
In: Science of the Total Environment, Vol. 737, 140348, 01.10.2020.

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

TY - JOUR

T1 - A mechanism-based parameterisation scheme to investigate the association between transmission rate of COVID-19 and meteorological factors on plains in China

AU - Lin, Changqing

AU - Lau, Alexis K.H.

AU - Fung, Jimmy C.H.

AU - Guo, Cui

AU - Chan, Jimmy W.M.

AU - Yeung, David W.

AU - Zhang, Yumiao

AU - Bo, Yacong

AU - Hossain, Md Shakhaoat

AU - Zeng, Yiqian

AU - Lao, Xiang Qian

PY - 2020/10/1

Y1 - 2020/10/1

N2 - The novel coronavirus disease 2019 (COVID-19), which first emerged in Hubei province, China, has become a pandemic. However, data regarding the effects of meteorological factors on its transmission are limited and inconsistent. A mechanism-based parameterisation scheme was developed to investigate the association between the scaled transmission rate (STR) of COVID-19 and the meteorological parameters in 20 provinces/municipalities located on the plains in China. We obtained information on the scale of population migrated from Wuhan, the world epicentre of the COVID-19 outbreak, into the study provinces/municipalities using mobile-phone positioning system and big data techniques. The highest STRs were found in densely populated metropolitan areas and in cold provinces located in north-eastern China. Population density had a non-linear relationship with disease spread (linearity index, 0.9). Among various meteorological factors, only temperature was significantly associated with the STR after controlling for the effect of population density. A negative and exponential relationship was identified between the transmission rate and the temperature (correlation coefficient, −0.56; 99% confidence level). The STR increased substantially as the temperature in north-eastern China decreased below 0 °C (the STR ranged from 3.5 to 12.3 when the temperature was between −9.41 °C and −13.87 °C), whilst the STR showed less temperature dependence in the study areas with temperate weather conditions (the STR was 1.21 ± 0.57 when the temperature was above 0 °C). Therefore, a higher population density was linearly whereas a lower temperature (

AB - The novel coronavirus disease 2019 (COVID-19), which first emerged in Hubei province, China, has become a pandemic. However, data regarding the effects of meteorological factors on its transmission are limited and inconsistent. A mechanism-based parameterisation scheme was developed to investigate the association between the scaled transmission rate (STR) of COVID-19 and the meteorological parameters in 20 provinces/municipalities located on the plains in China. We obtained information on the scale of population migrated from Wuhan, the world epicentre of the COVID-19 outbreak, into the study provinces/municipalities using mobile-phone positioning system and big data techniques. The highest STRs were found in densely populated metropolitan areas and in cold provinces located in north-eastern China. Population density had a non-linear relationship with disease spread (linearity index, 0.9). Among various meteorological factors, only temperature was significantly associated with the STR after controlling for the effect of population density. A negative and exponential relationship was identified between the transmission rate and the temperature (correlation coefficient, −0.56; 99% confidence level). The STR increased substantially as the temperature in north-eastern China decreased below 0 °C (the STR ranged from 3.5 to 12.3 when the temperature was between −9.41 °C and −13.87 °C), whilst the STR showed less temperature dependence in the study areas with temperate weather conditions (the STR was 1.21 ± 0.57 when the temperature was above 0 °C). Therefore, a higher population density was linearly whereas a lower temperature (

KW - COVID-19

KW - Imported scale

KW - Meteorology

KW - Population density

KW - Temperature

UR - https://www.scopus.com/pages/publications/85086573973

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85086573973&origin=recordpage

UR - https://app-overton-io.ezproxy.cityu.edu.hk/articles.php?query=10.1016/j.scitotenv.2020.140348

U2 - 10.1016/j.scitotenv.2020.140348

DO - 10.1016/j.scitotenv.2020.140348

M3 - RGC 21 - Publication in refereed journal

C2 - 32569904

AN - SCOPUS:85086573973

SN - 0048-9697

VL - 737

JO - Science of the Total Environment

JF - Science of the Total Environment

M1 - 140348

ER -

A mechanism-based parameterisation scheme to investigate the association between transmission rate of COVID-19 and meteorological factors on plains in China

Abstract

Bibliographical note

Funding

UN SDGs

Research Keywords

RGC Funding Information

Policy Impact

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this