Evidence map›Paper›PMID 34953903›Full record

ArticleThe Journal of infection2022

Sensitivity and specificity of surveillance case definitions in detection of influenza and respiratory syncytial virus among hospitalized patients, New Zealand, 2012-2016.

William Davis, Jazmin Duque, Q Sue Huang, Natalie Olson, Cameron C Grant, E Claire Newbern, Mark Thompson, Ben Waite, Namrata Prasad, Adrian Trenholme and 1 more

Open access · hybridAbstract read
In one paragraph

Article in The Journal of infection, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 4 pooled it
2.3field-weighted citation impact, top 11% of its field
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.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 4 syntheses or guidelines pooled it, 24 citations in OpenAlex.

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  7. Evaluation of COVID-19 and Influenza-like Illness Surveillance Case Definitions in a Prospective Cohort of Healthcare Personnel in Peru.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 2 countries.

William DavisUS Centers for Disease Control and Prevention, Atlanta, USA.
Jazmin DuqueUS Centers for Disease Control and Prevention, Atlanta, USA; Battelle Atlanta, Atlanta, USA; The University of Auckland, Auckland, New Zealand.
Q Sue HuangInstitute of Environmental Science and Research, Wellington, New Zealand.
Natalie OlsonUS Centers for Disease Control and Prevention, Atlanta, USA.
Cameron C GrantThe University of Auckland, Auckland, New Zealand; Starship Children's Hospital, Auckland, New Zealand.
E Claire NewbernInstitute of Environmental Science and Research, Wellington, New Zealand.
Mark ThompsonUS Centers for Disease Control and Prevention, Atlanta, USA.
Ben WaiteInstitute of Environmental Science and Research, Wellington, New Zealand.
Namrata PrasadThe University of Auckland, Auckland, New Zealand; Institute of Environmental Science and Research, Wellington, New Zealand.
Adrian TrenholmeThe University of Auckland, Auckland, New Zealand; Middlemore Hospital, Auckland, New Zealand.
Eduardo Azziz-BaumgartnerUS Centers for Disease Control and Prevention, Atlanta, USA. Electronic address: lyo0@cdc.gov.
Centers for Disease Control and Prevention · USNew Zealand Institute for Public Health and Forensic Science · NZMiddlemore Hospital · NZStarship Children's Health · NZUniversity of Auckland · NZ

Funding

Southern Hemisphere Influenza and Vaccine Effectiveness Research and SurveillanceU01IP000480 · IP · INST OF ENVIRONMENTAL SCIENCE & RESEARCH · PI HUANG, SUE · 2011 to 2015
$7.0M
Intramural CDC HHS CC999999NCIRD CDC HHS U01 IP000480
6 · The paper itself

Abstract

backgroundThe WHO is exploring the value of adding RSV testing to existing influenza surveillance systems to inform RSV control programs. We evaluate the usefulness of four commonly used influenza surveillance case-definitions for influenza and RSV surveillance.

methodsSHIVERS, a multi-institutional collaboration, conducted surveillance for influenza and RSV in four New Zealand hospitals. Nurses reviewed admission logs, enrolled patients with suspected acute respiratory infections (ARI), and obtained nasopharyngeal swabs for RT-PCR. We compared the performance characteristics for identifying laboratory-confirmed influenza and RSV severe acute respiratory infection (SARI), defined as persons admitted with measured or reported fever and cough within 10 days of illness, to three other case definitions: 1. reported fever and cough or shortness of breath, 2. cough and shortness of breath, or 3. cough.

resultsDuring April-September 2012-2016, SHIVERS identified 16,055 admissions with ARI; of 6374 cases consented and tested for influenza or RSV, 5437 (85%) had SARI and 937 (15%) did not. SARI had the highest specificity in detecting influenza (40.6%) and RSV (40.8%) but the lowest sensitivity (influenza 78.8%, RSV 60.3%) among patients of all ages. Cough or shortness of breath had the highest sensitivity (influenza 99.3%, RSV 99.9%) but the lowest specificity (influenza 1.6%, RSV 1.9%). SARI sensitivity among children aged <3 months was 60.8% for influenza and 43.6% for RSV-both lower than in other age groups.

conclusionsWhile SARI had the highest specificity, its sensitivity was limited, especially among children aged <3 months. Cough or shortness of breath was the most sensitive.

Indexed as

Influenza, HumanRespiratory Syncytial Virus, HumanRespiratory Syncytial Virus InfectionsRespiratory Tract InfectionsChildHospitalizationHumansInfantNew ZealandCase definitionClinicalInfluenzaNew ZealandRespiratory syncytial virusShiversSymptomsWHO

Identifiers

PMID34953903
PMCPMC11753188
OpenAlexW4200480647

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.