Evidence map›Paper›PMID 23587010›Full record

ArticleBMC infectious diseases2013

Age-specific contacts and travel patterns in the spatial spread of 2009 H1N1 influenza pandemic.

Andrea Apolloni, Chiara Poletto, Vittoria Colizza

Abstract read
In one paragraph

Article in BMC infectious diseases, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 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

41 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. The use and reporting of airline passenger data for infectious disease modelling: a systematic review.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2019
    Pooled it
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  13. Impacts of COVID-19 on the usage of public bicycle share in London.Transportation research. Part A, Policy and practice · 2021
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  18. Oscillatory dynamics in the dilemma of social distancing.Proceedings. Mathematical, physical, and engineering sciences · 2020
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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

3 authors.

Andrea ApolloniDepartment of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
Chiara Poletto
Vittoria Colizza

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundConfirmed H1N1 cases during late spring and summer 2009 in various countries showed a substantial age shift between importations and local transmission cases, with adults mainly responsible for seeding unaffected regions and children most frequently driving community outbreaks.

methodsWe introduce a multi-host stochastic metapopulation model with two age classes to analytically investigate the role of a heterogeneously mixing population and its associated non-homogeneous travel behaviors on the risk of a major epidemic. We inform the model with demographic data, contact data and travel statistics of Europe and Mexico, and calibrate it to the 2009 H1N1 pandemic early outbreak. We allow for variations of the model parameters to explore the conditions of invasion under different scenarios.

resultsWe derive the expression for the potential of global invasion of the epidemic that depends on the transmissibility of the pathogen, the transportation network and mobility features, the demographic profile and the mixing pattern. Higher assortativity in the contact pattern greatly increases the probability of spatial containment of the epidemic, this effect being contrasted by an increase in the social activity of adults vs. children. Heterogeneous features of the mobility network characterizing its topology and traffic flows strongly favor the invasion of the pathogen at the spatial level, as also a larger fraction of children traveling. Variations in the demographic profile and mixing habits across countries lead to heterogeneous outbreak situations. Model results are compatible with the H1N1 spatial transmission dynamics observed.

conclusionsThis work illustrates the importance of considering age-dependent mixing profiles and mobility features coupled together to study the conditions for the spatial invasion of an emerging influenza pandemic. Its results allow the immediate assessment of the risk of a major epidemic for a specific scenario upon availability of data, and the evaluation of the potential effectiveness of public health interventions targeting specific age groups, their interactions and mobility behaviors. The approach provides a general modeling framework that can be used for other types of partitions of the host population and applied to different settings.

Indexed as

PandemicsTravelAdolescentAdultAge FactorsChildChild, PreschoolEuropeFemaleHumansInfantInfluenza A Virus, H1N1 SubtypeInfluenza, HumanMaleMexicoModels, Statistical

Identifiers

PMID23587010
PMCPMC3644502

What OpenQuestion holds

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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.