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Possible interference between seasonal epidemics of influenza and other respiratory viruses in Hong Kong, 2014–2017

Overview of attention for article published in BMC Infectious Diseases, December 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
6 news outlets
blogs
1 blog
policy
1 policy source
twitter
28 X users
facebook
1 Facebook page
reddit
1 Redditor

Citations

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30 Dimensions

Readers on

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53 Mendeley
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Title
Possible interference between seasonal epidemics of influenza and other respiratory viruses in Hong Kong, 2014–2017
Published in
BMC Infectious Diseases, December 2017
DOI 10.1186/s12879-017-2888-5
Pubmed ID
Authors

Xueying Zheng, Zhengyu Song, Yapeng Li, Juanjuan Zhang, Xi-Ling Wang

Abstract

Unlike influenza viruses, little is known about the prevalence and seasonality of other respiratory viruses because laboratory surveillance for non-influenza respiratory viruses is not well developed or supported in China and other resource-limited countries. We studied the interference between seasonal epidemics of influenza viruses and five other common viruses that cause respiratory illnesses in Hong Kong from 2014 to 2017. The weekly laboratory-confirmed positive rates of each virus were analyzed from 2014 to 2017 in Hong Kong to describe the epidemiological trends and interference between influenza viruses, respiratory syncytial virus (RSV), parainfluenza virus (PIV), adenovirus, enterovirus and rhinovirus. A sinusoidal model was established to estimate the peak timing of each virus by phase angle parameters. Seasonal features of the influenza viruses, PIV, enterovirus and adenovirus were obvious, whereas annual peaks of RSV and rhinovirus were not observed. The incidence of the influenza viruses usually peaked in February and July, and the summer peaks in July were generally caused by the H3 subtype of influenza A alone. When influenza viruses were active, other viruses tended to have a low level of activity. The peaks of the influenza viruses were not synchronized. An epidemic of rhinovirus tended to shift the subsequent epidemics of the other viruses. The evidence from recent surveillance data in Hong Kong suggests that viral interference during the epidemics of influenza viruses and other common respiratory viruses might affect the timing and duration of subsequent epidemics of a certain or several viruses.

X Demographics

X Demographics

The data shown below were collected from the profiles of 28 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 19%
Student > Master 9 17%
Researcher 8 15%
Professor > Associate Professor 4 8%
Other 4 8%
Other 9 17%
Unknown 9 17%
Readers by discipline Count As %
Medicine and Dentistry 13 25%
Biochemistry, Genetics and Molecular Biology 5 9%
Agricultural and Biological Sciences 4 8%
Nursing and Health Professions 2 4%
Immunology and Microbiology 2 4%
Other 11 21%
Unknown 16 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 77. 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 13 August 2023.
All research outputs
#560,466
of 25,649,244 outputs
Outputs from BMC Infectious Diseases
#135
of 8,667 outputs
Outputs of similar age
#12,554
of 445,924 outputs
Outputs of similar age from BMC Infectious Diseases
#3
of 166 outputs
Altmetric has tracked 25,649,244 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,667 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has done particularly well, scoring higher than 98% 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 445,924 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 166 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.