Evidence map›Paper›PMID 26825326›Full record

ArticleBMC infectious diseases2016

Construction of the influenza A virus transmission tree in a college-based population: co-transmission and interactions between influenza A viruses.

Xu-Sheng Zhang, Daniela De Angelis

Abstract read
In one paragraph

Article in BMC infectious diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

2 authors.

Xu-Sheng ZhangCentre for Infectious Disease Surveillance and Control, Public Health England, 61 Colindale Avenue, London, NW9 5EQ, UK. xu-sheng.zhang@phe.gov.uk.
Daniela De AngelisCentre for Infectious Disease Surveillance and Control, Public Health England, 61 Colindale Avenue, London, NW9 5EQ, UK.

Funding

Medical Research Council MC_U105260556
6 · The paper itself

Abstract

backgroundCo-infection of different influenza A viruses is known to occur but how viruses interact within co-infection remains unknown. An outbreak in a college campus during the 2009 pandemic involved two subtypes of influenza A: persons infected with pandemic A/H1N1; persons infected with seasonal A/H3N2 viruses; and persons infected with both at the same time (co-infection). This provides data to analyse the possible interaction between influenza A viruses within co-infection.

methodsWe extend a statistical inference method designed for outbreaks caused by one virus to that caused by two viruses. The method uses knowledge of which subtype each case is infected with (and whether they were co-infected), contact information and symptom onset date of each case in the influenza outbreak. We then apply it to construct the most likely transmission tree during the outbreak in the college campus.

resultsAnalysis of the constructed transmission tree shows that the simultaneous presence of the two influenza viruses increases the infectivity and the transmissibility of A/H1N1 virus but whether it changes the infectivity of A/H3N2 is unclear. The estimation also shows that co-transmission of both subtypes from co-infection is low and therefore co-infection cannot be sustained on its own.

conclusionsThis study suggests that influenza A viruses within co-infected patients can interact in some ways rather than transmit independently, and this can enhance the spread of influenza A virus infection.

Indexed as

AlgorithmsCoinfectionDisease OutbreaksHumansInfluenza A Virus, H1N1 SubtypeInfluenza A Virus, H3N2 SubtypeInfluenza, Human

Identifiers

PMID26825326
PMCPMC4731987

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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.