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Estimating disease burden of a potential A(H7N9) pandemic influenza outbreak in the United States

Overview of attention for article published in BMC Public Health, November 2017
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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 (90th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

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1 blog
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1 Redditor

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50 Mendeley
Title
Estimating disease burden of a potential A(H7N9) pandemic influenza outbreak in the United States
Published in
BMC Public Health, November 2017
DOI 10.1186/s12889-017-4884-5
Pubmed ID
Authors

Walter Silva, Tapas K. Das, Ricardo Izurieta

Abstract

Since spring 2013, periodic emergence of avian influenza A(H7N9) virus in China has heightened the concern for a possible pandemic outbreak among humans, though it is believed that the virus is not yet human-to-human transmittable. Till June 2017, A(H7N9) has resulted in 1533 laboratory-confirmed cases of human infections causing 592 deaths. The aim of this paper is to present disease burden estimates (measured by infection attack rates (IAR) and number of deaths) in the event of a possible pandemic outbreak caused by human-to-human transmission capability acquired by A(H7N9) virus. Even though such a pandemic will likely spread worldwide, our focus in this paper is to estimate the impact on the United States alone. The method first uses a data clustering technique to divide 50 states in the U.S. into a small number of clusters. Thereafter, for a few selected states in each cluster, the method employs an agent-based (AB) model to simulate human A(H7N9) influenza pandemic outbreaks. The model uses demographic and epidemiological data. A few selected non-pharmaceutical intervention (NPI) measures are applied to mitigate the outbreaks. Disease burden for the U.S. is estimated by combining results from the clusters applying a method used in stratified sampling. Two possible pandemic scenarios with R 0 = 1.5 and 1.8 are examined. Infection attack rates with 95% C.I. (Confidence Interval) for R 0 = 1.5 and 1.8 are estimated to be 18.78% (17.3-20.27) and 25.05% (23.11-26.99), respectively. The corresponding number of deaths (95% C.I.), per 100,000, are 7252.3 (6598.45-7907.33) and 9670.99 (8953.66-10,389.95). The results reflect a possible worst-case scenario where the outbreak extends over all states of the U.S. and antivirals and vaccines are not administered. Our disease burden estimations are also likely to be somewhat high due to the fact that only dense urban regions covering approximately 3% of the geographic area and 81% of the population are used for simulating sample outbreaks. Outcomes from these simulations are extrapolated over the remaining 19% of the population spread sparsely over 97% of the area. Furthermore, the full extent of possible NPIs, if deployed, could also have lowered the disease burden estimates.

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Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 24%
Student > Master 11 22%
Student > Bachelor 5 10%
Other 3 6%
Student > Ph. D. Student 3 6%
Other 7 14%
Unknown 9 18%
Readers by discipline Count As %
Medicine and Dentistry 8 16%
Nursing and Health Professions 6 12%
Biochemistry, Genetics and Molecular Biology 5 10%
Social Sciences 3 6%
Environmental Science 3 6%
Other 12 24%
Unknown 13 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 16 April 2020.
All research outputs
#1,893,503
of 24,744,050 outputs
Outputs from BMC Public Health
#2,123
of 16,394 outputs
Outputs of similar age
#42,119
of 449,015 outputs
Outputs of similar age from BMC Public Health
#36
of 169 outputs
Altmetric has tracked 24,744,050 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 16,394 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one has done well, scoring higher than 87% 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 449,015 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 90% of its contemporaries.
We're also able to compare this research output to 169 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.