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A large-scale study of a poultry trading network in Bangladesh: implications for control and surveillance of avian influenza viruses

Overview of attention for article published in BMC Veterinary Research, January 2018
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Mentioned by

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3 tweeters

Citations

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26 Dimensions

Readers on

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55 Mendeley
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Title
A large-scale study of a poultry trading network in Bangladesh: implications for control and surveillance of avian influenza viruses
Published in
BMC Veterinary Research, January 2018
DOI 10.1186/s12917-018-1331-5
Pubmed ID
Authors

N. Moyen, G. Ahmed, S. Gupta, T. Tenzin, R. Khan, T. Khan, N. Debnath, M. Yamage, D.U. Pfeiffer, G. Fournie

Abstract

Since its first report in 2007, avian influenza (AI) has been endemic in Bangladesh. While live poultry marketing is widespread throughout the country and known to influence AI dissemination and persistence, trading patterns have not been described. The aim of this study is to assess poultry trading practices and features of the poultry trading networks which could promote AI spread, and their potential implications for disease control and surveillance. Data on poultry trading practices was collected from 849 poultry traders during a cross-sectional survey in 138 live bird markets (LBMs) across 17 different districts of Bangladesh. The quantity and origins of traded poultry were assessed for each poultry type in surveyed LBMs. The network of contacts between farms and LBMs resulting from commercial movements of live poultry was constructed to assess its connectivity and to identify the key premises influencing it. Poultry trading practices varied according to the size of the LBMs and to the type of poultry traded. Industrial broiler chickens, the most commonly traded poultry, were generally sold in LBMs close to their production areas, whereas ducks and backyard chickens were moved over longer distances, and their transport involved several intermediates. The poultry trading network composed of 445 nodes (73.2% were LBMs) was highly connected and disassortative. However, the removal of only 5.6% of the nodes (25 LBMs with the highest betweenness scores), reduced the network's connectedness, and the maximum size of output and input domains by more than 50%. Poultry types need to be discriminated in order to understand the way in which poultry trading networks are shaped, and the level of risk of disease spread that these networks may promote. Knowledge of the network structure could be used to target control and surveillance interventions to a small number of LBMs.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 16%
Student > Master 8 15%
Researcher 5 9%
Other 5 9%
Student > Bachelor 3 5%
Other 12 22%
Unknown 13 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 15%
Veterinary Science and Veterinary Medicine 6 11%
Medicine and Dentistry 5 9%
Computer Science 3 5%
Mathematics 3 5%
Other 14 25%
Unknown 16 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 17 January 2018.
All research outputs
#12,831,782
of 19,985,377 outputs
Outputs from BMC Veterinary Research
#1,104
of 2,716 outputs
Outputs of similar age
#276,770
of 487,291 outputs
Outputs of similar age from BMC Veterinary Research
#126
of 237 outputs
Altmetric has tracked 19,985,377 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,716 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 54% 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 487,291 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 237 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.