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The impact of surveillance and control on highly pathogenic avian influenza outbreaks in poultry in Dhaka division, Bangladesh

Overview of attention for article published in PLoS Computational Biology, September 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

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13 tweeters

Citations

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4 Dimensions

Readers on

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21 Mendeley
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Title
The impact of surveillance and control on highly pathogenic avian influenza outbreaks in poultry in Dhaka division, Bangladesh
Published in
PLoS Computational Biology, September 2018
DOI 10.1371/journal.pcbi.1006439
Pubmed ID
Authors

Edward M. Hill, Thomas House, Madhur S. Dhingra, Wantanee Kalpravidh, Subhash Morzaria, Muzaffar G. Osmani, Eric Brum, Mat Yamage, Md. A. Kalam, Diann J. Prosser, John Y. Takekawa, Xiangming Xiao, Marius Gilbert, Michael J. Tildesley

Abstract

In Bangladesh, the poultry industry is an economically and socially important sector, but it is persistently threatened by the effects of H5N1 highly pathogenic avian influenza. Thus, identifying the optimal control policy in response to an emerging disease outbreak is a key challenge for policy-makers. To inform this aim, a common approach is to carry out simulation studies comparing plausible strategies, while accounting for known capacity restrictions. In this study we perform simulations of a previously developed H5N1 influenza transmission model framework, fitted to two separate historical outbreaks, to assess specific control objectives related to the burden or duration of H5N1 outbreaks among poultry farms in the Dhaka division of Bangladesh. In particular, we explore the optimal implementation of ring culling, ring vaccination and active surveillance measures when presuming disease transmission predominately occurs from premises-to-premises, versus a setting requiring the inclusion of external factors. Additionally, we determine the sensitivity of the management actions under consideration to differing levels of capacity constraints and outbreaks with disparate transmission dynamics. While we find that reactive culling and vaccination policies should pay close attention to these factors to ensure intervention targeting is optimised, across multiple settings the top performing control action amongst those under consideration were targeted proactive surveillance schemes. Our findings may advise the type of control measure, plus its intensity, that could potentially be applied in the event of a developing outbreak of H5N1 amongst originally H5N1 virus-free commercially-reared poultry in the Dhaka division of Bangladesh.

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Other 5 24%
Student > Master 3 14%
Researcher 2 10%
Student > Ph. D. Student 1 5%
Student > Bachelor 1 5%
Other 2 10%
Unknown 7 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 38%
Medicine and Dentistry 3 14%
Nursing and Health Professions 1 5%
Biochemistry, Genetics and Molecular Biology 1 5%
Unknown 8 38%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 September 2018.
All research outputs
#1,994,160
of 15,864,191 outputs
Outputs from PLoS Computational Biology
#2,101
of 6,121 outputs
Outputs of similar age
#52,889
of 276,289 outputs
Outputs of similar age from PLoS Computational Biology
#33
of 83 outputs
Altmetric has tracked 15,864,191 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,121 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.9. This one has gotten more attention than average, scoring higher than 65% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 276,289 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 83 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.