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The role of vaccination coverage, individual behaviors, and the public health response in the control of measles epidemics: an agent-based simulation for California

Overview of attention for article published in BMC Public Health, May 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)

Mentioned by

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6 tweeters
facebook
1 Facebook page

Citations

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29 Dimensions

Readers on

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93 Mendeley
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Title
The role of vaccination coverage, individual behaviors, and the public health response in the control of measles epidemics: an agent-based simulation for California
Published in
BMC Public Health, May 2015
DOI 10.1186/s12889-015-1766-6
Pubmed ID
Authors

Fengchen Liu, Wayne T A Enanoria, Jennifer Zipprich, Seth Blumberg, Kathleen Harriman, Sarah F Ackley, William D Wheaton, Justine L Allpress, Travis C Porco

Abstract

Measles cases continue to occur among susceptible individuals despite the elimination of endemic measles transmission in the United States. Clustering of disease susceptibility can threaten herd immunity and impact the likelihood of disease outbreaks in a highly vaccinated population. Previous studies have examined the role of contact tracing to control infectious diseases among clustered populations, but have not explicitly modeled the public health response using an agent-based model. We developed an agent-based simulation model of measles transmission using the Framework for Reconstructing Epidemiological Dynamics (FRED) and the Synthetic Population Database maintained by RTI International. The simulation of measles transmission was based on interactions among individuals in different places: households, schools, daycares, workplaces, and neighborhoods. The model simulated different levels of immunity clustering, vaccination coverage, and contact investigations with delays caused by individuals' behaviors and/or the delay in a health department's response. We examined the effects of these characteristics on the probability of uncontrolled measles outbreaks and the outbreak size in 365 days after the introduction of one index case into a synthetic population. We found that large measles outbreaks can be prevented with contact investigations and moderate contact rates by having (1) a very high vaccination coverage (≥ 95%) with a moderate to low level of immunity clustering (≤ 0.5) for individuals aged less than or equal to 18 years, or (2) a moderate vaccination coverage (85% or 90%) with no immunity clustering for individuals (≤18 years of age), a short intervention delay, and a high probability that a contact can be traced. Without contact investigations, measles outbreaks may be prevented by the highest vaccination coverage with no immunity clustering for individuals (≤18 years of age) with moderate contact rates; but for the highest contact rates, even the highest coverage with no immunity clustering for individuals (≤18 years of age) cannot completely prevent measles outbreaks. The simulation results demonstrated the importance of vaccination coverage, clustering of immunity, and contact investigations in preventing uncontrolled measles outbreaks.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
Indonesia 1 1%
Australia 1 1%
Unknown 87 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 22%
Researcher 19 20%
Student > Ph. D. Student 17 18%
Student > Bachelor 13 14%
Professor > Associate Professor 5 5%
Other 13 14%
Unknown 6 6%
Readers by discipline Count As %
Medicine and Dentistry 24 26%
Agricultural and Biological Sciences 10 11%
Nursing and Health Professions 9 10%
Social Sciences 7 8%
Computer Science 6 6%
Other 23 25%
Unknown 14 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 22 February 2019.
All research outputs
#7,230,129
of 14,372,231 outputs
Outputs from BMC Public Health
#5,308
of 9,887 outputs
Outputs of similar age
#80,729
of 229,326 outputs
Outputs of similar age from BMC Public Health
#1
of 3 outputs
Altmetric has tracked 14,372,231 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,887 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.5. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
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 229,326 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them