New! Sign up for our free email newsletter.
Science News
from research organizations

Seven symptoms jointly predict COVID-19 diagnosis, study finds

Date:
September 28, 2021
Source:
PLOS
Summary:
A set of 7 symptoms, considered together, can be used to maximize detection of COVID-19 in the community, according to researchers.
Share:
FULL STORY

A set of 7 symptoms, considered together, can be used to maximize detection of COVID-19 in the community, according to a new paper published this week in PLOS Medicine by Marc Chadeau-Hyam and Paul Elliott of Imperial College London, UK, and colleagues.

The rapid detection of SARS-CoV-2 infection in the community is key to ensuring efficient control of transmission. When testing capacity is limited, it is important to use tests in the most efficient way possible, including using the most informative symptoms for test allocation. In the new study, researchers obtained throat and nose swabs with valid SARS-CoV-2 PCR test results from 1,147,345 volunteers in England aged 5 years and above. The data were collected over 8 testing rounds conducted between June 2020 and January 2021 as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Participants were asked about symptoms they experienced in the week prior to testing.

A model was developed based on the data obtained during rounds 2 to 7, with 7 symptoms selected as jointly positively predictive of PCR positivity: loss or change of smell, loss or change of taste, fever, new persistent cough, chills, appetite loss, and muscle aches. The first 4 of those symptoms are currently used in the UK to determine eligibility for community PCR testing. In round 8 of testing, the resulting model predicted PCR positivity with an area under the curve of 0.77, and testing people in the community with at least 1 of the 7 selected positively predictive symptoms gave sensitivity, specificity, and positive predictive values of 74%, 64%, and 9.7%, respectively. Modeling suggested that the use of the 7 symptoms identified for PCR test allocation would result in 30% to 40% of symptomatic individuals in England being eligible for a test (versus 10% currently) and, if all those eligible were tested, would result in the detection of 70% to 75% of positive cases.

"In order to improve PCR positivity detection rates and consequently improve control of viral transmission via isolation measures, we would propose to extend the list of symptoms used for triage to all 7 symptoms we identified," the authors say.

"These findings suggest many people with COVID-19 won't be getting tested -- and therefore won't be self-isolating -- because their symptoms don't match those used in current public health guidance to help identify infected people," Elliott adds. "We understand that there is a need for clear testing criteria, and that including lots of symptoms which are commonly found in other illnesses like seasonal flu could risk people self-isolating unnecessarily. I hope that our findings on the most informative symptoms mean that the testing programme can take advantage of the available evidence, helping to optimise the detection of infected people."


Story Source:

Materials provided by PLOS. Note: Content may be edited for style and length.


Journal Reference:

  1. Joshua Elliott, Matthew Whitaker, Barbara Bodinier, Oliver Eales, Steven Riley, Helen Ward, Graham Cooke, Ara Darzi, Marc Chadeau-Hyam, Paul Elliott. Predictive symptoms for COVID-19 in the community: REACT-1 study of over 1 million people. PLOS Medicine, 2021; 18 (9): e1003777 DOI: 10.1371/journal.pmed.1003777

Cite This Page:

PLOS. "Seven symptoms jointly predict COVID-19 diagnosis, study finds." ScienceDaily. ScienceDaily, 28 September 2021. <www.sciencedaily.com/releases/2021/09/210928141836.htm>.
PLOS. (2021, September 28). Seven symptoms jointly predict COVID-19 diagnosis, study finds. ScienceDaily. Retrieved November 20, 2024 from www.sciencedaily.com/releases/2021/09/210928141836.htm
PLOS. "Seven symptoms jointly predict COVID-19 diagnosis, study finds." ScienceDaily. www.sciencedaily.com/releases/2021/09/210928141836.htm (accessed November 20, 2024).

Explore More

from ScienceDaily

RELATED STORIES