Spatiotemporal Analysis of Weather Effects on COVID-19 Pandemic Transmissions in Select US Counties

Zhenkun Tian; Chuixiang Yi; Yingying Fu; Jacqueline Singer; Qin Zhang

doi:doi:10.11648/j.jher.20200604.11

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Spatiotemporal Analysis of Weather Effects on COVID-19 Pandemic Transmissions in Select US Counties

Zhenkun Tian, Chuixiang Yi, Yingying Fu, Jacqueline Singer, Qin Zhang

Published in Journal of Health and Environmental Research (Volume 6, Issue 4)

Received: 6 September 2020 Accepted: 29 September 2020 Published: 17 October 2020

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Abstract

The COVID-19 pandemic has become a global crisis with enormous uncertainty. This study aims to explore what role weather plays in pandemic transmission. We hypothesize that weather conditions (temperature, wind speed, and precipitation) significantly influence the transmissibility of the disease and the number of infected people. We tested this hypothesis by analyzing weather variable in moving-average-windows that varied from 1 to 30 days, and daily new confirmed cases observed from 23 counties in the United States, during the period of January 22 to August 19, 2020. We found consistent results that the moving average temperature over 10 days (T_avg10), the moving average wind speed and the moving average amount of precipitation over 28 days (W_avg28, P_avg28) were the meteorological parameters most closely linked to the outbreak and growth of new cases of COVID-19 in the US. The correlation statistics differed regionally: (1) temperature is negatively correlated to the outbreak of COVID-19 in the Northeastern US and positively in other areas; (2) wind speed is negatively correlated to the COVID-19 pandemic in the Southeastern US while positively in other areas; and (3) precipitation holds a positive correlation on the east coast of the US and a negative one on the west coast. Our results suggest that meteorological factors may play a significant role in COVID-19 pandemic transmission in the US and should be considered by policy makers and crisis administrators.

Published in	Journal of Health and Environmental Research (Volume 6, Issue 4)
DOI	10.11648/j.jher.20200604.11
Page(s)	104-113
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

COVID-19, Lag Effect, Temperature, Wind Speed, Precipitation, Pandemic

References

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APA Style

Zhenkun Tian, Chuixiang Yi, Yingying Fu, Jacqueline Singer, Qin Zhang. (2020). Spatiotemporal Analysis of Weather Effects on COVID-19 Pandemic Transmissions in Select US Counties. Journal of Health and Environmental Research, 6(4), 104-113. https://doi.org/10.11648/j.jher.20200604.11

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ACS Style

Zhenkun Tian; Chuixiang Yi; Yingying Fu; Jacqueline Singer; Qin Zhang. Spatiotemporal Analysis of Weather Effects on COVID-19 Pandemic Transmissions in Select US Counties. J. Health Environ. Res. 2020, 6(4), 104-113. doi: 10.11648/j.jher.20200604.11

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AMA Style

Zhenkun Tian, Chuixiang Yi, Yingying Fu, Jacqueline Singer, Qin Zhang. Spatiotemporal Analysis of Weather Effects on COVID-19 Pandemic Transmissions in Select US Counties. J Health Environ Res. 2020;6(4):104-113. doi: 10.11648/j.jher.20200604.11

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@article{10.11648/j.jher.20200604.11,
  author = {Zhenkun Tian and Chuixiang Yi and Yingying Fu and Jacqueline Singer and Qin Zhang},
  title = {Spatiotemporal Analysis of Weather Effects on COVID-19 Pandemic Transmissions in Select US Counties},
  journal = {Journal of Health and Environmental Research},
  volume = {6},
  number = {4},
  pages = {104-113},
  doi = {10.11648/j.jher.20200604.11},
  url = {https://doi.org/10.11648/j.jher.20200604.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jher.20200604.11},
  abstract = {The COVID-19 pandemic has become a global crisis with enormous uncertainty. This study aims to explore what role weather plays in pandemic transmission. We hypothesize that weather conditions (temperature, wind speed, and precipitation) significantly influence the transmissibility of the disease and the number of infected people. We tested this hypothesis by analyzing weather variable in moving-average-windows that varied from 1 to 30 days, and daily new confirmed cases observed from 23 counties in the United States, during the period of January 22 to August 19, 2020. We found consistent results that the moving average temperature over 10 days (Tavg10), the moving average wind speed and the moving average amount of precipitation over 28 days (Wavg28, Pavg28) were the meteorological parameters most closely linked to the outbreak and growth of new cases of COVID-19 in the US. The correlation statistics differed regionally: (1) temperature is negatively correlated to the outbreak of COVID-19 in the Northeastern US and positively in other areas; (2) wind speed is negatively correlated to the COVID-19 pandemic in the Southeastern US while positively in other areas; and (3) precipitation holds a positive correlation on the east coast of the US and a negative one on the west coast. Our results suggest that meteorological factors may play a significant role in COVID-19 pandemic transmission in the US and should be considered by policy makers and crisis administrators.},
 year = {2020}
}

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TY  - JOUR
T1  - Spatiotemporal Analysis of Weather Effects on COVID-19 Pandemic Transmissions in Select US Counties
AU  - Zhenkun Tian
AU  - Chuixiang Yi
AU  - Yingying Fu
AU  - Jacqueline Singer
AU  - Qin Zhang
Y1  - 2020/10/17
PY  - 2020
N1  - https://doi.org/10.11648/j.jher.20200604.11
DO  - 10.11648/j.jher.20200604.11
T2  - Journal of Health and Environmental Research
JF  - Journal of Health and Environmental Research
JO  - Journal of Health and Environmental Research
SP  - 104
EP  - 113
PB  - Science Publishing Group
SN  - 2472-3592
UR  - https://doi.org/10.11648/j.jher.20200604.11
AB  - The COVID-19 pandemic has become a global crisis with enormous uncertainty. This study aims to explore what role weather plays in pandemic transmission. We hypothesize that weather conditions (temperature, wind speed, and precipitation) significantly influence the transmissibility of the disease and the number of infected people. We tested this hypothesis by analyzing weather variable in moving-average-windows that varied from 1 to 30 days, and daily new confirmed cases observed from 23 counties in the United States, during the period of January 22 to August 19, 2020. We found consistent results that the moving average temperature over 10 days (Tavg10), the moving average wind speed and the moving average amount of precipitation over 28 days (Wavg28, Pavg28) were the meteorological parameters most closely linked to the outbreak and growth of new cases of COVID-19 in the US. The correlation statistics differed regionally: (1) temperature is negatively correlated to the outbreak of COVID-19 in the Northeastern US and positively in other areas; (2) wind speed is negatively correlated to the COVID-19 pandemic in the Southeastern US while positively in other areas; and (3) precipitation holds a positive correlation on the east coast of the US and a negative one on the west coast. Our results suggest that meteorological factors may play a significant role in COVID-19 pandemic transmission in the US and should be considered by policy makers and crisis administrators.
VL  - 6
IS  - 4
ER  -

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Author Information

Zhenkun Tian

Department of Mathematics and Computer, China University of Labor Relations, Beijing, China
Chuixiang Yi

School of Earth and Environmental Sciences, Queens College, City University of New York, New York, USA
Yingying Fu

School of Mathematics and Statistics, Beijing Technology and Business University, Beijing, China
Jacqueline Singer

School of Earth and Environmental Sciences, Queens College, City University of New York, New York, USA
Qin Zhang

Institution of Water and Environment Research, Dalian University of Technology, Dalian, China

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APA Style

Zhenkun Tian, Chuixiang Yi, Yingying Fu, Jacqueline Singer, Qin Zhang. (2020). Spatiotemporal Analysis of Weather Effects on COVID-19 Pandemic Transmissions in Select US Counties. Journal of Health and Environmental Research, 6(4), 104-113. https://doi.org/10.11648/j.jher.20200604.11

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ACS Style

Zhenkun Tian; Chuixiang Yi; Yingying Fu; Jacqueline Singer; Qin Zhang. Spatiotemporal Analysis of Weather Effects on COVID-19 Pandemic Transmissions in Select US Counties. J. Health Environ. Res. 2020, 6(4), 104-113. doi: 10.11648/j.jher.20200604.11

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AMA Style

Zhenkun Tian, Chuixiang Yi, Yingying Fu, Jacqueline Singer, Qin Zhang. Spatiotemporal Analysis of Weather Effects on COVID-19 Pandemic Transmissions in Select US Counties. J Health Environ Res. 2020;6(4):104-113. doi: 10.11648/j.jher.20200604.11

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@article{10.11648/j.jher.20200604.11,
  author = {Zhenkun Tian and Chuixiang Yi and Yingying Fu and Jacqueline Singer and Qin Zhang},
  title = {Spatiotemporal Analysis of Weather Effects on COVID-19 Pandemic Transmissions in Select US Counties},
  journal = {Journal of Health and Environmental Research},
  volume = {6},
  number = {4},
  pages = {104-113},
  doi = {10.11648/j.jher.20200604.11},
  url = {https://doi.org/10.11648/j.jher.20200604.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jher.20200604.11},
  abstract = {The COVID-19 pandemic has become a global crisis with enormous uncertainty. This study aims to explore what role weather plays in pandemic transmission. We hypothesize that weather conditions (temperature, wind speed, and precipitation) significantly influence the transmissibility of the disease and the number of infected people. We tested this hypothesis by analyzing weather variable in moving-average-windows that varied from 1 to 30 days, and daily new confirmed cases observed from 23 counties in the United States, during the period of January 22 to August 19, 2020. We found consistent results that the moving average temperature over 10 days (Tavg10), the moving average wind speed and the moving average amount of precipitation over 28 days (Wavg28, Pavg28) were the meteorological parameters most closely linked to the outbreak and growth of new cases of COVID-19 in the US. The correlation statistics differed regionally: (1) temperature is negatively correlated to the outbreak of COVID-19 in the Northeastern US and positively in other areas; (2) wind speed is negatively correlated to the COVID-19 pandemic in the Southeastern US while positively in other areas; and (3) precipitation holds a positive correlation on the east coast of the US and a negative one on the west coast. Our results suggest that meteorological factors may play a significant role in COVID-19 pandemic transmission in the US and should be considered by policy makers and crisis administrators.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - Spatiotemporal Analysis of Weather Effects on COVID-19 Pandemic Transmissions in Select US Counties
AU  - Zhenkun Tian
AU  - Chuixiang Yi
AU  - Yingying Fu
AU  - Jacqueline Singer
AU  - Qin Zhang
Y1  - 2020/10/17
PY  - 2020
N1  - https://doi.org/10.11648/j.jher.20200604.11
DO  - 10.11648/j.jher.20200604.11
T2  - Journal of Health and Environmental Research
JF  - Journal of Health and Environmental Research
JO  - Journal of Health and Environmental Research
SP  - 104
EP  - 113
PB  - Science Publishing Group
SN  - 2472-3592
UR  - https://doi.org/10.11648/j.jher.20200604.11
AB  - The COVID-19 pandemic has become a global crisis with enormous uncertainty. This study aims to explore what role weather plays in pandemic transmission. We hypothesize that weather conditions (temperature, wind speed, and precipitation) significantly influence the transmissibility of the disease and the number of infected people. We tested this hypothesis by analyzing weather variable in moving-average-windows that varied from 1 to 30 days, and daily new confirmed cases observed from 23 counties in the United States, during the period of January 22 to August 19, 2020. We found consistent results that the moving average temperature over 10 days (Tavg10), the moving average wind speed and the moving average amount of precipitation over 28 days (Wavg28, Pavg28) were the meteorological parameters most closely linked to the outbreak and growth of new cases of COVID-19 in the US. The correlation statistics differed regionally: (1) temperature is negatively correlated to the outbreak of COVID-19 in the Northeastern US and positively in other areas; (2) wind speed is negatively correlated to the COVID-19 pandemic in the Southeastern US while positively in other areas; and (3) precipitation holds a positive correlation on the east coast of the US and a negative one on the west coast. Our results suggest that meteorological factors may play a significant role in COVID-19 pandemic transmission in the US and should be considered by policy makers and crisis administrators.
VL  - 6
IS  - 4
ER  -

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