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International COVID-19 mortality forecast visualization: covidcompare.io.
Akre, Samir; Liu, Patrick Y; Friedman, Joseph R; Bui, Alex A T.
Affiliation
  • Akre S; Medical Informatics Home Area, University of California, Los Angeles, California, USA.
  • Liu PY; Department of Radiological Sciences, University of California, Los Angeles, California, USA.
  • Friedman JR; Medical Informatics Home Area, University of California, Los Angeles, California, USA.
  • Bui AAT; Medical Informatics Home Area, University of California, Los Angeles, California, USA.
JAMIA Open ; 4(4): ooab113, 2021 Oct.
Article in En | MEDLINE | ID: mdl-34988383
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Qualitative_research Language: En Journal: JAMIA Open Year: 2021 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Qualitative_research Language: En Journal: JAMIA Open Year: 2021 Document type: Article Affiliation country: