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Optimal symptom combinations to aid COVID-19 case identification: Analysis from a community-based, prospective, observational cohort.
Antonelli, M; Capdevila, J; Chaudhari, A; Granerod, J; Canas, L S; Graham, M S; Klaser, K; Modat, M; Molteni, E; Murray, B; Sudre, C H; Davies, R; May, A; Nguyen, L H; Drew, D A; Joshi, A; Chan, A T; Cramer, J P; Spector, T; Wolf, J; Ourselin, S; Steves, C J; Loeliger, A E.
  • Antonelli M; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Capdevila J; Zoe Global, London, United Kingdom.
  • Chaudhari A; Coalition for Epidemic Preparedness Innovations, London, United Kingdom.
  • Granerod J; Coalition for Epidemic Preparedness Innovations, London, United Kingdom.
  • Canas LS; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Graham MS; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Klaser K; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Modat M; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Molteni E; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Murray B; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Sudre CH; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom; MRC Unit for Lifelong Health and Ageing at UCL/Centre for Medical Image Computing, Department of Computer Science, UCL, London, United Kingdom.
  • Davies R; Zoe Global, London, United Kingdom.
  • May A; Zoe Global, London, United Kingdom.
  • Nguyen LH; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Drew DA; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Joshi A; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Chan AT; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Cramer JP; Coalition for Epidemic Preparedness Innovations, London, United Kingdom.
  • Spector T; Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom.
  • Wolf J; Zoe Global, London, United Kingdom.
  • Ourselin S; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Steves CJ; Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom. Electronic address: Claire.j.steves@kcl.ac.uk.
  • Loeliger AE; Coalition for Epidemic Preparedness Innovations, London, United Kingdom.
J Infect ; 82(3): 384-390, 2021 03.
Article in English | MEDLINE | ID: covidwho-1080546
ABSTRACT

OBJECTIVES:

Diagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health.

METHODS:

UK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity.

FINDINGS:

UK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC.

INTERPRETATION:

We confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Diagnostic study / Observational study / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: J Infect Year: 2021 Document Type: Article Affiliation country: J.jinf.2021.02.015

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Diagnostic study / Observational study / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: J Infect Year: 2021 Document Type: Article Affiliation country: J.jinf.2021.02.015