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Spatio-Temporal Resource Mapping for Intensive Care Units at Regional Level for COVID-19 Emergency in Italy

Author

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  • Pietro Hiram Guzzi

    (Department of Surgical and Medical Sciences, University of Catanzaro, 88100 Catanzaro, Italy
    These authors contributed equally to this work.)

  • Giuseppe Tradigo

    (Department of Surgical and Medical Sciences, University of Catanzaro, 88100 Catanzaro, Italy
    These authors contributed equally to this work.)

  • Pierangelo Veltri

    (Department of Surgical and Medical Sciences, University of Catanzaro, 88100 Catanzaro, Italy
    These authors contributed equally to this work.)

Abstract

COVID-19 is a worldwide emergency since it has rapidly spread from China to almost all the countries worldwide. Italy has been one of the most affected countries after China. North Italian regions, such as Lombardia and Veneto, had an abnormally large number of cases. COVID-19 patients management requires availability of sufficiently large number of Intensive Care Units (ICUs) beds. Resources shortening is a critical issue when the number of COVID-19 severe cases are higher than the available resources. This is also the case at a regional scale. We analysed Italian data at regional level with the aim to: (i) support health and government decision-makers in gathering rapid and efficient decisions on increasing health structures capacities (in terms of ICU slots) and (ii) define a geographic model to plan emergency and future COVID-19 patients management using reallocating them among health structures. Finally, we retain that the here proposed model can be also used in other countries.

Suggested Citation

  • Pietro Hiram Guzzi & Giuseppe Tradigo & Pierangelo Veltri, 2020. "Spatio-Temporal Resource Mapping for Intensive Care Units at Regional Level for COVID-19 Emergency in Italy," IJERPH, MDPI, vol. 17(10), pages 1-9, May.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:10:p:3344-:d:356868
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    References listed on IDEAS

    as
    1. Yaesoubi, Reza & Cohen, Ted, 2011. "Generalized Markov models of infectious disease spread: A novel framework for developing dynamic health policies," European Journal of Operational Research, Elsevier, vol. 215(3), pages 679-687, December.
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    Cited by:

    1. Costase Ndayishimiye & Christoph Sowada & Patrycja Dyjach & Agnieszka Stasiak & John Middleton & Henrique Lopes & Katarzyna Dubas-Jakóbczyk, 2022. "Associations between the COVID-19 Pandemic and Hospital Infrastructure Adaptation and Planning—A Scoping Review," IJERPH, MDPI, vol. 19(13), pages 1-22, July.

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