HackerPapers

arXiv:2003.07347stat.AP

Building a COVID-19 Vulnerability Index

Dave DeCaprio, Joseph Gartner, Thadeus Burgess, Kristian Garcia, Sarthak Kothari, Shaayan Sayed, Carol J. McCall

HN submission. Found in a submission link or body. Submitters do not count as commenters in the main ranking; a submission is not an endorsement.

Abstract

COVID-19 is an acute respiratory disease that has been classified as a pandemic by the World Health Organization. Characterization of this disease is still in its early stages. However, it is known to have high mortality rates, particularly among individuals with preexisting medical conditions. Creating models to identify individuals who are at the greatest risk for severe complications due to COVID-19 will be useful for outreach campaigns to help mitigate the disease's worst effects. While information specific to COVID-19 is limited, a model using complications due to other upper respiratory infections can be used as a proxy to help identify those individuals who are at the greatest risk. We present the results for three models predicting such complications, with each model increasing predictive effectiveness at the expense of ease of implementation.

arXiv comments
Journal reference
DOI
Subjects
stat.APApplications (Statistics) cs.AIArtificial Intelligence

On Hacker News

No comments linking this paper were found in the collected sources. Found in 1 HN submission from Apr 2020 to Apr 2020. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments0 threads

No comments linking this paper were found in the collected sources. Open submission discussions.

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.