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Influence of demographic changes on the impact of vaccination against varicella and herpes zoster in Germany – a mathematical modelling study

Overview of attention for article published in BMC Medicine, January 2018
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Mentioned by

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1 policy source
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5 X users

Citations

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19 Dimensions

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55 Mendeley
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Title
Influence of demographic changes on the impact of vaccination against varicella and herpes zoster in Germany – a mathematical modelling study
Published in
BMC Medicine, January 2018
DOI 10.1186/s12916-017-0983-5
Pubmed ID
Authors

Johannes Horn, Oliver Damm, Wolfgang Greiner, Hartmut Hengel, Mirjam E. Kretzschmar, Anette Siedler, Bernhard Ultsch, Felix Weidemann, Ole Wichmann, André Karch, Rafael T. Mikolajczyk

Abstract

Epidemiological studies suggest that reduced exposure to varicella might lead to an increased risk for herpes zoster (HZ). Reduction of exposure to varicella is a consequence of varicella vaccination but also of demographic changes. We analyzed how the combination of vaccination programs and demographic dynamics will affect the epidemiology of varicella and HZ in Germany over the next 50 years. We used a deterministic dynamic compartmental model to assess the impact of different varicella and HZ vaccination strategies on varicella and HZ epidemiology in three demographic scenarios, namely the projected population for Germany, the projected population additionally accounting for increased immigration as observed in 2015/2016, and a stationary population. Projected demographic changes alone result in an increase of annual HZ cases by 18.3% and a decrease of varicella cases by 45.7% between 1990 and 2060. Independently of the demographic scenario, varicella vaccination reduces the cumulative number of varicella cases until 2060 by approximately 70%, but also increases HZ cases by 10%. Unlike the currently licensed live attenuated HZ vaccine, the new subunit vaccine candidate might completely counteract this effect. Relative vaccine effects were consistent across all demographic scenarios. Demographic dynamics will be a major determinant of HZ epidemiology in the next 50 years. While stationary population models are appropriate for assessing vaccination impact, models incorporating realistic population structures allow a direct comparison to surveillance data and can thus provide additional input for immunization decision-making and resource planning.

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X Demographics

The data shown below were collected from the profiles of 5 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 18%
Student > Master 8 15%
Student > Bachelor 6 11%
Student > Ph. D. Student 4 7%
Student > Doctoral Student 2 4%
Other 9 16%
Unknown 16 29%
Readers by discipline Count As %
Medicine and Dentistry 15 27%
Nursing and Health Professions 6 11%
Biochemistry, Genetics and Molecular Biology 3 5%
Agricultural and Biological Sciences 2 4%
Immunology and Microbiology 2 4%
Other 9 16%
Unknown 18 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 14 September 2021.
All research outputs
#5,875,992
of 23,577,761 outputs
Outputs from BMC Medicine
#2,340
of 3,568 outputs
Outputs of similar age
#115,087
of 445,933 outputs
Outputs of similar age from BMC Medicine
#31
of 49 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 3,568 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 44.5. This one is in the 34th percentile – i.e., 34% 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 445,933 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 74% of its contemporaries.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.