ArticleNPJ digital medicine2020
Estimating the efficacy of symptom-based screening for COVID-19.
Article in NPJ digital medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
24 citing papers in PubMed.
- Identifying the optimal rapid antigen test for screening and determining the end of isolation: A modeling study.PLoS computational biology · 2026Article
- Enhancing COVID-19 Screening Models With Epidemiological and Mobility Features: Machine-Learning Model Study.JMIR AI · 2026Article
- Comparative analysis of frequentist, Bayesian, and machine learning models for predicting SARS-CoV-2 PCR positivity.Frontiers in artificial intelligence · 2025Article
- Air Passengers' Risk of SARS-CoV-2 Infection With a 14-Day Quarantine and Accuracy Assessment of a Symptom-based Screening System at an Airport.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2025Article
- SARS-CoV-2 anti-N antibodies among healthcare personnel without previous known COVID-19.Antimicrobial stewardship & healthcare epidemiology : ASHE · 2024Article
- The Stanford Medicine data science ecosystem for clinical and translational research.JAMIA open · 2023Article
- Machine learning for optimal test admission in the presence of resource constraints.Health care management science · 2023Article
- Machine learning COVID-19 detection from wearables.The Lancet. Digital health · 2023Article
- Towards an ML-based semantic IoT for pandemic management: A survey of enabling technologies for COVID-19.Neurocomputing · 2023Article
- Developing and Evaluating a Measure of the Willingness to Use Pandemic-Related mHealth Tools Using National Probability Samples in the United States: Quantitative Psychometric Analyses and Tests of Sociodemographic Group Differences.JMIR formative research · 2023Article
- Wearable technology for early detection of COVID-19: A systematic scoping review.Preventive medicine · 2022Article
- Data science approaches to confronting the COVID-19 pandemic: a narrative review.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022Review
- Estimating COVID-19 cases in Puerto Rico using an automated surveillance system.Frontiers in public health · 2022Article
- Implementation of a COVID-19 screening tool in a southern Nigerian tertiary health facility.PLOS global public health · 2022Article
- Detection of COVID-19 Using Heart Rate and Blood Pressure: Lessons Learned from Patients with ARDS.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021Article
- The Evolution of Clinical Knowledge During COVID-19: Towards a Global Learning Health System.Yearbook of medical informatics · 2021Article
- A Machine Learning Approach as an Aid for Early COVID-19 Detection.Sensors (Basel, Switzerland) · 2021Article
- Ontology-driven weak supervision for clinical entity classification in electronic health records.Nature communications · 2021Article
- Understanding On-Campus Interactions With a Semiautomated, Barcode-Based Platform to Augment COVID-19 Contact Tracing: App Development and Usage.JMIR mHealth and uHealth · 2021Article
- Screening for COVID-19 in Older Adults: Pulse Oximeter vs. Temperature.Frontiers in medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is substantial interest in using presenting symptoms to prioritize testing for COVID-19 and establish symptom-based surveillance. However, little is currently known about the specificity of COVID-19 symptoms. To assess the feasibility of symptom-based screening for COVID-19, we used data from tests for common respiratory viruses and SARS-CoV-2 in our health system to measure the ability to correctly classify virus test results based on presenting symptoms. Based on these results, symptom-based screening may not be an effective strategy to identify individuals who should be tested for SARS-CoV-2 infection or to obtain a leading indicator of new COVID-19 cases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.