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A New Interactive Tool to Visualize and Analyze COVID-19 Data: The PERISCOPE Atlas

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  • Daniele Pala

    (Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
    Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA)

  • Enea Parimbelli

    (Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
    Telfer School of Management, University of Ottawa, Ottawa, ON K1N 6N5, Canada)

  • Cristiana Larizza

    (Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy)

  • Cindy Cheng

    (Hochschule für Politik, The TUM School of Governance, Technical University of Munich (TUM), 80333 Munich, Germany)

  • Manuel Ottaviano

    (Departamento de Tecnología Fotónica y Bioingeniería, Universidad Politècnica de Madrid, 28040 Madrid, Spain)

  • Andrea Pogliaghi

    (GeneGIS GI Srl, 20148 Milan, Italy)

  • Goran Đukić

    (Research & Development Department Belit Ltd., Trg Nikole Pašića 9, 11000 Belgrade, Serbia)

  • Aleksandar Jovanović

    (Research & Development Department Belit Ltd., Trg Nikole Pašića 9, 11000 Belgrade, Serbia)

  • Ognjen Milićević

    (Research & Development Department Belit Ltd., Trg Nikole Pašića 9, 11000 Belgrade, Serbia)

  • Vladimir Urošević

    (Research & Development Department Belit Ltd., Trg Nikole Pašića 9, 11000 Belgrade, Serbia)

  • Paola Cerchiello

    (Dipartimento di Scienze Economiche e Aziendali, University of Pavia, 27100 Pavia, Italy)

  • Paolo Giudici

    (Dipartimento di Scienze Economiche e Aziendali, University of Pavia, 27100 Pavia, Italy)

  • Riccardo Bellazzi

    (Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy)

Abstract

Since the start of the 21st century, the world has not confronted a more serious threat to global public health than the COVID-19 pandemic. While governments initially took radical actions in response to the pandemic to avoid catastrophic collapse of their health care systems, government policies have also had numerous knock-on socioeconomic, political, behavioral and economic effects. Researchers, thus, have a unique opportunity to forward our collective understanding of the modern world and to respond to the emergency situation in a way that optimizes resources and maximizes results. The PERISCOPE project, funded by the European Commission, brings together a large number of research institutions to collect data and carry out research to understand all the impacts of the pandemic, and create predictive models that can be used to optimize intervention strategies and better face possible future health emergencies. One of the main tangible outcomes of this project is the PERISCOPE Atlas: an interactive tool that allows to visualize and analyze COVID-19-related health, economic and sociopolitical data, featuring a WebGIS and several dashboards. This paper describes the first release of the Atlas, listing the data sources used, the main functionalities and the future development.

Suggested Citation

  • Daniele Pala & Enea Parimbelli & Cristiana Larizza & Cindy Cheng & Manuel Ottaviano & Andrea Pogliaghi & Goran Đukić & Aleksandar Jovanović & Ognjen Milićević & Vladimir Urošević & Paola Cerchiello & , 2022. "A New Interactive Tool to Visualize and Analyze COVID-19 Data: The PERISCOPE Atlas," IJERPH, MDPI, vol. 19(15), pages 1-16, July.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:9136-:d:872439
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    References listed on IDEAS

    as
    1. Alessandro Bitetto & Paola Cerchiello & Charilaos Mertzanis, 2021. "A data-driven approach to measuring epidemiological susceptibility risk around the world," DEM Working Papers Series 200, University of Pavia, Department of Economics and Management.
    2. Ahelegbey, Daniel Felix & Cerchiello, Paola & Scaramozzino, Roberta, 2022. "Network based evidence of the financial impact of Covid-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 81(C).
    3. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
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    Cited by:

    1. Petr Iakovlevitch Ekel & Sandro Laudares & Adriano José de Barros & Douglas Alexandre Gomes Vieira & Carlos Augusto Paiva da Silva Martins & Matheus Pereira Libório, 2023. "Geovisualization: A Practical Approach for COVID-19 Spatial Analysis," Geographies, MDPI, vol. 3(4), pages 1-16, December.
    2. Cheng, Cindy & Messerschmidt, Luca & Bravo, Isaac & Waldbauer, Marco & Bhavikatti, Rohan & Schenk, Caress & Grujic, Vanja & Model, Tim & Kubinec, Robert & Barceló, Joan, 2023. "A General Guide for Harmonizing Data," OSF Preprints baf2j, Center for Open Science.
    3. Nathaniel R. Geyer & Eugene J. Lengerich, 2023. "LionVu: A Data-Driven Geographical Web-GIS Tool for Community Health and Decision-Making in a Catchment Area," Geographies, MDPI, vol. 3(2), pages 1-17, April.
    4. Ekaterina Ignatenko & Manuel Ribeiro & Mónica D. Oliveira, 2022. "Informing the Design of Data Visualization Tools to Monitor the COVID-19 Pandemic in Portugal: A Web-Delphi Participatory Approach," IJERPH, MDPI, vol. 19(17), pages 1-18, September.

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