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Measuring influenza laboratory capacity: use of a tool to measure improvements

Overview of attention for article published in BMC Infectious Diseases, June 2017
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3 tweeters
1 Facebook page


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5 Mendeley
Measuring influenza laboratory capacity: use of a tool to measure improvements
Published in
BMC Infectious Diseases, June 2017
DOI 10.1186/s12879-017-2521-7
Pubmed ID

Pam Kennedy, Tricia Aden, Po Yung Cheng, Ann Moen


To collect information, identify training needs, and assist with influenza capacity building voluntary laboratory capacity assessments were conducted using a standardized tool in CDC cooperative agreement countries. To understand the usefulness of comparing results from repeat assessments and to determine if targeted training supported improvements, this paper details comparison of assessment results of conducting 17 repeat laboratory assessments between 2009 and 2013. Laboratory assessments were conducted by SMEs in 17 laboratories (16 countries). We reviewed the quantitative assessment results of the laboratories that conducted both an initial and follow up assessment between 2009 to 2013 using repeated measures of Anova, (Mixed procedure of SAS (9.3)). Additionally, we compared the overall summary scores and the assessor recommendations from the two assessments. We were able to document a statistically significant improvement between the first and second assessments both on an aggregate as well as individual indicator score. Within the international capacity tool three of the eight categories recorded statistically significant improvement (equipment, management, and QA/QC), while the other tool categories (molecular, NIC, specimen, safety and virology) showed improvement in scores although not statistically significant. We found that using a standardized tool and quantitative framework is useful for documenting capacity and performance improvement in identified areas over time. The use of the tool and standard reports with assessor recommendations assisted laboratories with establishing, maintaining, and improving influenza laboratory practices. On-going assessments and the consistent application of the analytic framework over time will continue to aid in building a measurement knowledge base for laboratory capacity.

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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 40%
Student > Ph. D. Student 2 40%
Researcher 1 20%
Readers by discipline Count As %
Nursing and Health Professions 1 20%
Economics, Econometrics and Finance 1 20%
Chemistry 1 20%
Medicine and Dentistry 1 20%
Engineering 1 20%
Other 0 0%

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 20 June 2017.
All research outputs
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Outputs from BMC Infectious Diseases
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Outputs of similar age
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Outputs of similar age from BMC Infectious Diseases
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Altmetric has tracked 13,534,740 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,047 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 50% of its peers.
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