Evidence map›Paper›PMID 29049288›Full record

ArticlePLoS computational biology2017

Seasonality in risk of pandemic influenza emergence.

Spencer J Fox, Joel C Miller, Lauren Ancel Meyers

Abstract read
In one paragraph

Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
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  8. Review
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  14. Comparable seasonal pattern for COVID-19 and flu-like illnesses.One health (Amsterdam, Netherlands) · 2021
    Article
  15. Does airborne pollen influence COVID-19 outbreak?Sustainable cities and society · 2021
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

3 authors.

Spencer J FoxIntegrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.ORCID http://orcid.org/0000-0003-1969-3778
Joel C MillerMathematical Sciences, Monash University, Frankston, Victoria, Australia.ORCID http://orcid.org/0000-0003-4426-0405
Lauren Ancel MeyersIntegrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.

Funding

Impacts of Individual and Social Behavior on Influenza Dynamics and ControlU01GM087719 · NIGMS · YALE UNIVERSITY · PI GALVANI, ALISON P, MEYERS, LAUREN ANCEL · 2009 to 2018
$6.3M
International Clinics on Infectious Disease Dynamics and Data (ICI3D Program)R25GM102149 · NIGMS · UNIVERSITY OF FLORIDA · PI PULLIAM, JULIET RC, WELTE, ALEX · 2012 to 2015
$696k
NIGMS NIH HHS R25 GM102149NIGMS NIH HHS U01 GM087719
6 · The paper itself

Abstract

Influenza pandemics can emerge unexpectedly and wreak global devastation. However, each of the six pandemics since 1889 emerged in the Northern Hemisphere just after the flu season, suggesting that pandemic timing may be predictable. Using a stochastic model fit to seasonal flu surveillance data from the United States, we find that seasonal flu leaves a transient wake of heterosubtypic immunity that impedes the emergence of novel flu viruses. This refractory period provides a simple explanation for not only the spring-summer timing of historical pandemics, but also early increases in pandemic severity and multiple waves of transmission. Thus, pandemic risk may be seasonal and predictable, with the accuracy of pre-pandemic and real-time risk assessments hinging on reliable seasonal influenza surveillance and precise estimates of the breadth and duration of heterosubtypic immunity.

Indexed as

Models, BiologicalComputational BiologyHumansInfluenza, HumanPandemicsRiskSeasons

Identifiers

PMID29049288
PMCPMC5654262

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.