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Influence of Meteorological Factors on the COVID-19 Transmission with Season and Geographic Location

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  • Xiao-Dong Yang

    (Department of Geography and Spatial Information Techniques/Center for Land and Marine Spatial Utilization and Governance Research, Ningbo University, Ningbo 315211, China
    Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research at Ningbo University, Ningbo 315211, China)

  • Hong-Li Li

    (Department of Geography and Spatial Information Techniques/Center for Land and Marine Spatial Utilization and Governance Research, Ningbo University, Ningbo 315211, China
    Institute of East China Sea, Ningbo University, Ningbo 315211, China)

  • Yue-E Cao

    (School of Environmental and Geographical Science, Shanghai Normal University, Shanghai 200234, China)

Abstract

The purpose of this study is to investigate whether the relationship between meteorological factors (i.e., daily maximum temperature, minimum temperature, average temperature, temperature range, relative humidity, average wind speed and total precipitation) and COVID-19 transmission is affected by season and geographical location during the period of community-based pandemic prevention and control. COVID-19 infected case records and meteorological data in four cities (Wuhan, Beijing, Urumqi and Dalian) in China were collected. Then, the best-fitting model of COVID-19 infected cases was selected from four statistic models (Gaussian, logistic, lognormal distribution and allometric models), and the relationship between meteorological factors and COVID-19 infected cases was analyzed using multiple stepwise regression and Pearson correlation. The results showed that the lognormal distribution model was well adapted to describing the change of COVID-19 infected cases compared with other models (R 2 > 0.78; p -values < 0.001). Under the condition of implementing community-based pandemic prevention and control, relationship between COVID-19 infected cases and meteorological factors differed among the four cities. Temperature and relative humidity were mainly the driving factors on COVID-19 transmission, but their relations obviously varied with season and geographical location. In summer, the increase in relative humidity and the decrease in maximum temperature facilitate COVID-19 transmission in arid inland cities, while at this point the decrease in relative humidity is good for the spread of COVID-19 in coastal cities. For the humid cities, the reduction of relative humidity and the lowest temperature in the winter promote COVID-19 transmission.

Suggested Citation

  • Xiao-Dong Yang & Hong-Li Li & Yue-E Cao, 2021. "Influence of Meteorological Factors on the COVID-19 Transmission with Season and Geographic Location," IJERPH, MDPI, vol. 18(2), pages 1-13, January.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:2:p:484-:d:477411
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    References listed on IDEAS

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    1. Radina P Soebiyanto & Farida Adimi & Richard K Kiang, 2010. "Modeling and Predicting Seasonal Influenza Transmission in Warm Regions Using Climatological Parameters," PLOS ONE, Public Library of Science, vol. 5(3), pages 1-10, March.
    2. Behnood, Ali & Mohammadi Golafshani, Emadaldin & Hosseini, Seyedeh Mohaddeseh, 2020. "Determinants of the infection rate of the COVID-19 in the U.S. using ANFIS and virus optimization algorithm (VOA)," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
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    2. Bogdan Bochenek & Mateusz Jankowski & Marta Gruszczynska & Grzegorz Nykiel & Maciej Gruszczynski & Adam Jaczewski & Michal Ziemianski & Robert Pyrc & Mariusz Figurski & Jarosław Pinkas, 2021. "Impact of Meteorological Conditions on the Dynamics of the COVID-19 Pandemic in Poland," IJERPH, MDPI, vol. 18(8), pages 1-13, April.
    3. Woraphon Yamaka & Siritaya Lomwanawong & Darin Magel & Paravee Maneejuk, 2022. "Analysis of the Lockdown Effects on the Economy, Environment, and COVID-19 Spread: Lesson Learnt from a Global Pandemic in 2020," IJERPH, MDPI, vol. 19(19), pages 1-21, October.

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