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Preliminary Spatiotemporal Analysis of Mortality in Northern Italy During COVID-19 First Wave

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Geomatics for Green and Digital Transition (ASITA 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1651))

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Abstract

We present a large-scale spatiotemporal analysis of excess mortality (EM) in the first COVID-19 epidemic wave in Lombardy and Veneto. Spatial statistics show that EM is spatially heterogenous in both regions. Global spatiotemporal correlation identifies EM trends that differ across regions during the epi-curve peak, but are uniform in early and late stages. Local spatiotemporal correlation identifies EM hotspots, coldspots, and transition zones. Identifying process dynamics and local features, spatiotemporal correlation can support epidemic surveillance.

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Notes

  1. 1.

    The definition of SARS-COV-2 changed from epidemic to pandemic on March 11, 2020, i.e., during the time analyzed by this study [2]; therefore, both terms are used in the paper.

  2. 2.

    According to ISTAT data, referred to 1 January 2020.

  3. 3.

    The municipal borders are visible in Fig. 5.

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Authors and Affiliations

  1. University of Calgary, Calgary, AB, T2N 1N4, Canada

    Stefania Bertazzon, Isabelle Couloigner & Alison Hanes

Authors
  1. Stefania Bertazzon
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  2. Isabelle Couloigner
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  3. Alison Hanes
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Correspondence to Stefania Bertazzon .

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Editors and Affiliations

  1. University of Torino, Grugliasco, Italy

    Enrico Borgogno-Mondino

  2. University of Pisa, Pisa, Italy

    Paola Zamperlin

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Bertazzon, S., Couloigner, I., Hanes, A. (2022). Preliminary Spatiotemporal Analysis of Mortality in Northern Italy During COVID-19 First Wave. In: Borgogno-Mondino, E., Zamperlin, P. (eds) Geomatics for Green and Digital Transition. ASITA 2022. Communications in Computer and Information Science, vol 1651. Springer, Cham. https://doi.org/10.1007/978-3-031-17439-1_28

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  • DOI: https://doi.org/10.1007/978-3-031-17439-1_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-17438-4

  • Online ISBN: 978-3-031-17439-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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