Evidence map›Paper›PMID 23409145›Full record

ArticlePloS one2013

Anticipating the prevalence of avian influenza subtypes H9 and H5 in live-bird markets.

Kim M Pepin, Jia Wang, Colleen T Webb, Jennifer A Hoeting, Mary Poss, Peter J Hudson, Wenshan Hong, Huachen Zhu, Yi Guan, Steven Riley

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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  4. Review
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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

10 authors.

Kim M PepinFogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.
Jia Wang
Colleen T Webb
Jennifer A Hoeting
Mary Poss
Peter J Hudson
Wenshan Hong
Huachen Zhu
Yi Guan
Steven Riley

Funding

Ecology of Infectious Diseases (EID)-Immune Landscapes of Human Influenza in HousR01TW008246 · FIC · JOHNS HOPKINS UNIVERSITY · PI CUMMINGS, DEREK A · 2008 to 2011
$1.9M
FIC NIH HHS R01 TW008246FIC NIH HHS R01 TW008246-01Medical Research Council MR/J008761/1Medical Research Council MR/K010174/1Wellcome TrustWellcome Trust 093488/Z/10/Z
6 · The paper itself

Abstract

An ability to forecast the prevalence of specific subtypes of avian influenza viruses (AIV) in live-bird markets would facilitate greatly the implementation of preventative measures designed to minimize poultry losses and human exposure. The minimum requirement for developing predictive quantitative tools is surveillance data of AIV prevalence sampled frequently over several years. Recently, a 4-year time series of monthly sampling of hemagglutinin subtypes 1-13 in ducks, chickens and quail in live-bird markets in southern China has become available. We used these data to investigate whether a simple statistical model, based solely on historical data (variables such as the number of positive samples in host X of subtype Y time t months ago), could accurately predict prevalence of H5 and H9 subtypes in chickens. We also examined the role of ducks and quail in predicting prevalence in chickens within the market setting because between-species transmission is thought to occur within markets but has not been measured. Our best statistical models performed remarkably well at predicting future prevalence (pseudo-R(2) = 0.57 for H9 and 0.49 for H5), especially considering the multi-host, multi-subtype nature of AIVs. We did not find prevalence of H5/H9 in ducks or quail to be predictors of prevalence in chickens within the Chinese markets. Our results suggest surveillance protocols that could enable more accurate and timely predictive statistical models. We also discuss which data should be collected to allow the development of mechanistic models.

Indexed as

Models, StatisticalAnimalsBirdsEpidemiological MonitoringInfluenza A virusInfluenza in BirdsPrevalenceRegression Analysis

Identifiers

PMID23409145
PMCPMC3567063

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Registered trials

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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.