Article in Influenza and other respiratory viruses, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
2 · The registry
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
11 authors.
Xinyi LiWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.ORCID https://orcid.org/0009-0004-2440-0946
Samuel M S ChengWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.ORCID https://orcid.org/0000-0001-7293-2331
Yuyun ChenWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Faith HoWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Gigi LiuWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Alan AuWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Natalie YuWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Dennis K M IpWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.ORCID https://orcid.org/0000-0003-3592-8709
Malik PeirisWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.ORCID https://orcid.org/0000-0001-8217-5995
Benjamin J CowlingWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.ORCID https://orcid.org/0000-0002-6297-7154
Nancy H L LeungWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.ORCID https://orcid.org/0000-0001-7314-840X
Funding
Health and Medical Research Fund of the Hong Kong SAR Government COVID1903001Research Grants Council of the Hong Kong Special Administrative Region, China T11-705/21-N
6 · The paper itself
Abstract
backgroundReassurance over the quality of self-collected swabs could provide additional evidence to support the self-collection of respiratory specimens as a valid and efficient method in large-scale cohort studies.
methodsThis study assessed the diagnostic performance of self-collected pooled nasal and throat swabs compared to staff-collected swabs for detecting SARS-CoV-2 and influenza virus by RT-PCR in a cohort of older adults (aged 69-87 years) from March to October 2024.
resultsSelf-collected swabs demonstrated high sensitivity (95.2% for SARS-CoV-2, 100% for influenza A) and specificity (99.2% and 100%, respectively) against staff-collected swabs. Cycle threshold values showed no statistically significant differences and strong correlations between the two methods.
conclusionsThese findings suggest self-collected swabs are a reliable alternative for community-based respiratory viruses surveillance in older adults, supporting their use in large-scale studies.
Indexed as
COVID-19Influenza, HumanSARS-CoV-2Specimen HandlingAgedAged, 80 and overFemaleHumansInfluenza A virusMalePharynxSensitivity and SpecificityCOVID‐19diagnostic performanceinfluenzasampling methodself‐swab
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.
Diagnostic Performance of Self-Collected Respiratory Swabs for SARS-CoV-2 and Influenza Virus in Community-Dwelling Older Adults. · full record | OpenQuestion