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The Spread of the Covid-19 Pandemic in Time and Space

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  • Hafner, Christian

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

Abstract
As the COVID-19 pandemic has had a profound impact on public health and global economies in 2020; it is crucial to understand how it developed and spread in time and space. This paper contributes to the growing literature by considering the dynamics of country-wise growth rates of infection numbers. Low-order serial correlation of growth rates is predominantly negative with cycles of two to four days for most countries. The results of fitted spatial autoregressive models suggest that there is high degree of spillover between countries. Forecast variances of many countries, in particular those with a high absolute number of infections, can to a large extent be explained by structural innovations of other countries. A better understanding of the serial and spatial dynamics of the spread of the pandemic may contribute to an improved containment and risk management.

Suggested Citation

  • Hafner, Christian, 2020. "The Spread of the Covid-19 Pandemic in Time and Space," LIDAM Reprints ISBA 2020031, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  • Handle: RePEc:aiz:louvar:2020031
    DOI: https://doi.org/10.3390/ijerph17113827
    Note: In: International Journal of Environmental Research and Public Health - Vol. 17, no.11, p. 3827 (2020)
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    15. Yingfei Zhang & Zheng Feei Ma, 2020. "Impact of the COVID-19 Pandemic on Mental Health and Quality of Life among Local Residents in Liaoning Province, China: A Cross-Sectional Study," IJERPH, MDPI, vol. 17(7), pages 1-12, March.
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    5. Hou, Li & Jin, Baisuo & Wu, Yuehua, 2024. "Estimation and variable selection for high-dimensional spatial dynamic panel data models," Journal of Econometrics, Elsevier, vol. 238(2).
    6. Anna Gloria Billé & Massimiliano Caporin, 2022. "Impact of COVID-19 on financial returns: a spatial dynamic panel data model with random effects," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-21, December.
    7. Sergio A. Chillon & Mikel Millan & Iñigo Aramendia & Unai Fernandez-Gamiz & Ekaitz Zulueta & Xabier Mendaza-Sagastizabal, 2021. "Natural Ventilation Characterization in a Classroom under Different Scenarios," IJERPH, MDPI, vol. 18(10), pages 1-13, May.
    8. Li, Shaoran & Linton, Oliver, 2021. "When will the Covid-19 pandemic peak?," Journal of Econometrics, Elsevier, vol. 220(1), pages 130-157.
    9. Amanda M. Y. Chu & Thomas W. C. Chan & Mike K. P. So & Wing-Keung Wong, 2021. "Dynamic Network Analysis of COVID-19 with a Latent Pandemic Space Model," IJERPH, MDPI, vol. 18(6), pages 1-22, March.
    10. Zhangbo Yang & Jiahao Zhang & Shanxing Gao & Hui Wang, 2022. "Complex Contact Network of Patients at the Beginning of an Epidemic Outbreak: An Analysis Based on 1218 COVID-19 Cases in China," IJERPH, MDPI, vol. 19(2), pages 1-17, January.

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