Evidence map›Paper›PMID 21719743›Full record

ArticleAmerican journal of epidemiology2011

Comparability of different methods for estimating influenza infection rates over a single epidemic wave.

Vernon J Lee, Mark I Chen, Jonathan Yap, Jocelyn Ong, Wei-Yen Lim, Raymond T P Lin, Ian Barr, Jimmy B S Ong, Tze Minn Mak, Lee Gan Goh and 3 more

Abstract readComparative Study
In one paragraph

Article in American journal of epidemiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 4 pooled it
–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.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

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

13 authors.

Vernon J LeeDepartment of Epidemiology and Public Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. vernonljm@hotmail.com
Mark I Chen
Jonathan Yap
Jocelyn Ong
Wei-Yen Lim
Raymond T P Lin
Ian Barr
Jimmy B S Ong
Tze Minn Mak
Lee Gan Goh
Yee Sin Leo
Paul M Kelly
Alex R Cook

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Estimation of influenza infection rates is important for determination of the extent of epidemic spread and for calculation of severity indicators. The authors compared estimated infection rates from paired and cross-sectional serologic surveys, rates of influenza like illness (ILI) obtained from sentinel general practitioners (GPs), and ILI samples that tested positive for influenza using data from similar periods collected during the 2009 H1N1 epidemic in Singapore. The authors performed sensitivity analyses to assess the robustness of estimates to input parameter uncertainties, and they determined sample sizes required for differing levels of precision. Estimates from paired seroconversion were 17% (95% Bayesian credible interval (BCI): 14, 20), higher than those from cross-sectional serology (12%, 95% BCI: 9, 17). Adjusted ILI estimates were 15% (95% BCI: 10, 25), and estimates computed from ILI and laboratory data were 12% (95% BCI: 8, 18). Serologic estimates were least sensitive to the risk of input parameter misspecification. ILI-based estimates were more sensitive to parameter misspecification, though this was lessened by incorporation of laboratory data. Obtaining a 5-percentage-point spread for the 95% confidence interval in infection rates would require more than 1,000 participants per serologic study, a sentinel network of 90 GPs, or 50 GPs when combined with laboratory samples. The various types of estimates will provide comparable findings if accurate input parameters can be obtained.

Indexed as

Influenza A Virus, H1N1 SubtypeAdultBayes TheoremCross-Sectional StudiesFemaleHumansIncidenceInfluenza, HumanMaleMiddle AgedPopulation SurveillanceSensitivity and SpecificitySentinel SurveillanceSeroepidemiologic StudiesSeverity of Illness IndexSingapore

Identifiers

PMID21719743
PMCPMC3148265

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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.