• Medientyp: E-Artikel
  • Titel: International COVID-19 mortality forecast visualization: covidcompare.io
  • Beteiligte: Akre, Samir; Liu, Patrick Y; Friedman, Joseph R; Bui, Alex A T
  • Erschienen: Oxford University Press (OUP), 2021
  • Erschienen in: JAMIA Open, 4 (2021) 4
  • Sprache: Englisch
  • DOI: 10.1093/jamiaopen/ooab113
  • ISSN: 2574-2531
  • Schlagwörter: Health Informatics
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: Abstract COVID-19 mortality forecasting models provide critical information about the trajectory of the pandemic, which is used by policymakers and public health officials to guide decision-making. However, thousands of published COVID-19 mortality forecasts now exist, many with their own unique methods, assumptions, format, and visualization. As a result, it is difficult to compare models and understand under which circumstances a model performs best. Here, we describe the construction and usability of covidcompare.io, a web tool built to compare numerous forecasts and offer insight into how each has performed over the course of the pandemic. From its launch in December 2020 to June 2021, we have seen 4600 unique visitors from 85 countries. A study conducted with public health professionals showed high usability overall as formally assessed using a Post-Study System Usability Questionnaire. We find that covidcompare.io is an impactful tool for the comparison of international COVID-19 mortality forecasting models.
  • Zugangsstatus: Freier Zugang