A deep learning approach for Spatio-Temporal forecasting of new cases and new hospital admissions of COVID-19 spread in Reggio Emilia, Northern Italy.

Journal: Journal of biomedical informatics
Published Date: Jul 11, 2022

Abstract

BACKGROUND: Since February 2020, the COVID-19 epidemic has rapidly spread throughout Italy. Some studies showed an association of environmental factors, such as PM, PM NO, temperature, relative humidity, wind speed, solar radiation and mobility with the spread of the epidemic. In this work, we aimed to predict via Deep Learning the real-time transmission of SARS-CoV-2 in the province of Reggio Emilia, Northern Italy, in a grid with a small resolution (12 km × 12 km), including satellite information.

Authors

  • Veronica Sciannameo
    University of Padova, Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, Italy.
  • Alessia Goffi
    TerrAria s.r.l, Via Melchiorre Gioia, 132, 20125 Milan, Italy.
  • Giuseppe Maffeis
    TerrAria s.r.l, Via Melchiorre Gioia, 132, 20125 Milan, Italy.
  • Roberta Gianfreda
    TerrAria s.r.l, Via Melchiorre Gioia, 132, 20125 Milan, Italy.
  • Daniele Jahier Pagliari
    Polytechnic of Turin, Department of Control and Computer Engineering, Italy.
  • Tommaso Filippini
    Section of Public Health, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.
  • Pamela Mancuso
    Epidemiology Unit, Azienda Unità Sanitaria Locale-Istituto di Ricovero e Cura a Carattere Scientifico di Reggio Emilia, 42123 Reggio Emilia, Italy.
  • Paolo Giorgi-Rossi
    Epidemiology Unit, Azienda Unità Sanitaria Locale-Istituto di Ricovero e Cura a Carattere Scientifico di Reggio Emilia, 42123 Reggio Emilia, Italy.
  • Leonardo Alberto Dal Zovo
    Studiomapp s.r.l., Via Pietro Alighieri, 43, 48121 Ravenna, Italy.
  • Angela Corbari
    Studiomapp s.r.l., Via Pietro Alighieri, 43, 48121 Ravenna, Italy.
  • Marco Vinceti
  • Paola Berchialla
    Medical Statistics Unit, Department of Clinical and Biological Sciences, University of Torino, Italy.

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