Evidence map›Paper›PMID 29212718›Full record

ArticleProceedings. Biological sciences2017

The persistence of multiple strains of avian influenza in live bird markets.

Amy Pinsent, Kim M Pepin, Huachen Zhu, Yi Guan, Michael T White, Steven Riley

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Interpretation of molecular detection of avian influenza A virus in respiratory specimens collected from live bird market workers in Dhaka, Bangladesh: infection or contamination?International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2023
    Article
  8. Article
  9. Article
  10. Ecological interventions to prevent and manage zoonotic pathogen spillover.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019
    Review
  11. Article
  12. Review
  13. 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

6 authors.

Amy PinsentMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK amy.pinsent@monash.edu.ORCID http://orcid.org/0000-0001-5747-5291
Kim M PepinNational Wildlife Research Center, United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, Fort Collins, CO, USA.
Huachen ZhuJoint Influenza Research Centre (SUMC/HKU), Shantou University Medical College, Shantou, People's Republic of China.
Yi GuanJoint Influenza Research Centre (SUMC/HKU), Shantou University Medical College, Shantou, People's Republic of China.
Michael T WhiteMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.
Steven RileyMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.

Funding

Models for synthesising molecular, clinical and epidemiological data, and translaU01GM110721 · NIGMS · IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE · PI CAUCHEMEZ, SIMON, FERGUSON, NEIL MORRIS · 2014 to 2018
$1.9M
Medical Research Council MR/J008761/1Medical Research Council MR/L012170/1NIGMS NIH HHS U01 GM110721
6 · The paper itself

Abstract

Multiple subtypes of avian influenza (AI) and novel reassortants are frequently isolated from live bird markets (LBMs). However, our understanding of the drivers of persistence of multiple AI subtypes is limited. We propose a stochastic model of AI transmission within an LBM that incorporates market size, turnover rate and the balance of direct versus environmental transmissibility. We investigate the relationship between these factors and the critical community size (CCS) for the persistence of single and multiple AI strains within an LBM. We fit different models of seeding from farms to two-strain surveillance data collected from Shantou, China. For a single strain and plausible estimates for continuous turnover rates and transmissibility, the CCS was approximately 11 800 birds, only a 4.2% increase in this estimate was needed to ensure persistence of the co-infecting strains (two strains in a single host). Precise values of CCS estimates were sensitive to changes in market turnover rate and duration of the latent period. Assuming a gradual daily sell rate of birds the estimated CCS was higher than when an instantaneous selling rate was assumed. We were able to reproduce prevalence dynamics similar to observations from a single market in China with infection seeded every 5-15 days, and a maximum non-seeding duration of 80 days. Our findings suggest that persistence of co-infections is more likely to be owing to sequential infection of single strains rather than ongoing transmission of both strains concurrently. In any given system for a fixed set of ecological and epidemiological conditions, there is an LBM size below which the risk of sustained co-circulation is low and which may suggest a clear policy opportunity to reduce the frequency of influenza co-infection in poultry.

Indexed as

BirdsAnimalsChinaCommerceInfluenza A virusInfluenza in BirdsModels, TheoreticalPrevalenceavian influenzaco-infectioncritical community sizeR0stochastic model

Identifiers

PMID29212718
PMCPMC5740266

What OpenQuestion holds

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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.