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

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  • Christian M. Hafner

    (Louvain Institute of Data Analysis and Modelling in Economics and Statistics, Institute of Statistics, Biostatistics and Actuarial Sciences, Université Catholique de Louvain, Voie du Roman Pays, 20, 1348 Louvain-la-Neuve, 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

  • Christian M. Hafner, 2020. "The Spread of the Covid-19 Pandemic in Time and Space," IJERPH, MDPI, vol. 17(11), pages 1-13, May.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:11:p:3827-:d:364077
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    2. Ewen Gallic & Michel Lubrano & Pierre Michel, 2021. "Optimal lockdowns: Analysing the efficiency of sanitary policies in Europe during the first wave," AMSE Working Papers 2111, Aix-Marseille School of Economics, France.
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    4. Monika Małgorzata Wojcieszak-Zbierska & Anna Jęczmyk & Jan Zawadka & Jarosław Uglis, 2020. "Agritourism in the Era of the Coronavirus (COVID-19): A Rapid Assessment from Poland," Agriculture, MDPI, vol. 10(9), pages 1-19, September.
    5. 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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    7. 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.
    8. Samuel Domínguez-Amarillo & Jesica Fernández-Agüera & Sonia Cesteros-García & Roberto Alonso González-Lezcano, 2020. "Bad Air Can Also Kill: Residential Indoor Air Quality and Pollutant Exposure Risk during the COVID-19 Crisis," IJERPH, MDPI, vol. 17(19), pages 1-33, September.
    9. 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.

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