COVID-19 risk score as a public health tool to guide targeted testing: A demonstration study in Qatar. Academic Article uri icon

Overview

abstract

  • We developed a Coronavirus Disease 2019 (COVID-19) risk score to guide targeted RT-PCR testing in Qatar. The Qatar national COVID-19 testing database, encompassing a total of 2,688,232 RT-PCR tests conducted between February 5, 2020-January 27, 2021, was analyzed. Logistic regression analyses were implemented to derive the COVID-19 risk score, as a tool to identify those at highest risk of having the infection. Score cut-off was determined using the ROC curve based on maximum sum of sensitivity and specificity. The score's performance diagnostics were assessed. Logistic regression analysis identified age, sex, and nationality as significant predictors of infection and were included in the risk score. The ROC curve was generated and the area under the curve was estimated at 0.63 (95% CI: 0.63-0.63). The score had a sensitivity of 59.4% (95% CI: 59.1%-59.7%), specificity of 61.1% (95% CI: 61.1%-61.2%), a positive predictive value of 10.9% (95% CI: 10.8%-10.9%), and a negative predictive value of 94.9% (94.9%-95.0%). The concept and utility of a COVID-19 risk score were demonstrated in Qatar. Such a public health tool can have considerable utility in optimizing testing and suppressing infection transmission, while maximizing efficiency and use of available resources.

authors

  • Abu-Raddad, Laith Jamal
  • Dargham, Soha
  • Chemaitelly, Hiam Souheil
  • Coyle, Peter
  • Al Kanaani, Zaina
  • Al Kuwari, Einas
  • Butt, Adeel A
  • Jeremijenko, Andrew
  • Kaleeckal, Anvar Hassan
  • Latif, Ali Nizar
  • Shaik, Riyazuddin Mohammad
  • Abdul Rahim, Hanan F
  • Nasrallah, Gheyath K
  • Yassine, Hadi M
  • Al Kuwari, Mohamed G
  • Al Romaihi, Hamad Eid
  • Al-Thani, Mohamed H
  • Al Khal, Abdullatif
  • Bertollini, Roberto

publication date

  • July 19, 2022

Research

keywords

  • COVID-19

Identity

PubMed Central ID

  • PMC9295939

Scopus Document Identifier

  • 85134628407

Digital Object Identifier (DOI)

  • 10.1007/s11357-020-00186-0

PubMed ID

  • 35853026

Additional Document Info

volume

  • 17

issue

  • 7