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A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic

Overview of attention for article published in BMC Medical Research Methodology, February 2017
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Title
A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic
Published in
BMC Medical Research Methodology, February 2017
DOI 10.1186/s12874-017-0300-1
Pubmed ID
Authors

Ka Chun Chong, Benny Chung Ying Zee, Maggie Haitian Wang

Abstract

In a new influenza pandemic, travel data such as arrival times of cases seeded by the originating country can be regarded as a combination of the epidemic size and the mobility networks of infections connecting the originating country with other regions. It can be a complete and timely source for estimating the basic reproduction number (R 0 ), a key indicator of disease transmissibility. In this study, we developed a likelihood-based method using arrival times of infected cases in different countries to estimate R 0 for influenza pandemics. A simulation was conducted to assess the performance of the proposed method. We further applied the method to the outbreak of the influenza pandemic A/H1N1 in Mexico. In the numerical application, the estimated R 0 was equal to 1.69 with a 95% confidence interval (1.65, 1.73). For the simulation results, the estimations were robust to the decline of travel rate and other parameter assumptions. Nevertheless, the estimates were moderately sensitive to the assumption of infectious duration. Generally, the findings were in line with other relevant studies. Our approach as well as the estimate is potential to assist officials in planning control and prevention measures. Improved coordination to streamline or even centralize surveillance of imported cases among countries will thus be beneficial to public health.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 19%
Student > Master 5 16%
Student > Bachelor 4 13%
Student > Ph. D. Student 3 9%
Professor 2 6%
Other 5 16%
Unknown 7 22%
Readers by discipline Count As %
Social Sciences 5 16%
Medicine and Dentistry 5 16%
Nursing and Health Professions 4 13%
Computer Science 4 13%
Mathematics 2 6%
Other 4 13%
Unknown 8 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 February 2017.
All research outputs
#20,407,586
of 22,957,478 outputs
Outputs from BMC Medical Research Methodology
#1,889
of 2,026 outputs
Outputs of similar age
#270,766
of 310,771 outputs
Outputs of similar age from BMC Medical Research Methodology
#32
of 35 outputs
Altmetric has tracked 22,957,478 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,026 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.