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TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions

Overview of attention for article published in BMC Medicine, March 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)

Mentioned by

1 policy source
13 tweeters


37 Dimensions

Readers on

187 Mendeley
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TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions
Published in
BMC Medicine, March 2016
DOI 10.1186/s12916-016-0608-4
Pubmed ID

R. M. G. J. Houben, M. Lalli, T. Sumner, M. Hamilton, D. Pedrazzoli, F. Bonsu, P. Hippner, Y. Pillay, M. Kimerling, S. Ahmedov, C. Pretorius, R. G. White


Tuberculosis (TB) is the leading cause of death from infectious disease worldwide, predominantly affecting low- and middle-income countries (LMICs), where resources are limited. As such, countries need to be able to choose the most efficient interventions for their respective setting. Mathematical models can be valuable tools to inform rational policy decisions and improve resource allocation, but are often unavailable or inaccessible for LMICs, particularly in TB. We developed TIME Impact, a user-friendly TB model that enables local capacity building and strengthens country-specific policy discussions to inform support funding applications at the (sub-)national level (e.g. Ministry of Finance) or to international donors (e.g. the Global Fund to Fight AIDS, Tuberculosis and Malaria).TIME Impact is an epidemiological transmission model nested in TIME, a set of TB modelling tools available for free download within the widely-used Spectrum software. The TIME Impact model reflects key aspects of the natural history of TB, with additional structure for HIV/ART, drug resistance, treatment history and age. TIME Impact enables national TB programmes (NTPs) and other TB policymakers to better understand their own TB epidemic, plan their response, apply for funding and evaluate the implementation of the response.The explicit aim of TIME Impact's user-friendly interface is to enable training of local and international TB experts towards independent use. During application of TIME Impact, close involvement of the NTPs and other local partners also builds critical understanding of the modelling methods, assumptions and limitations inherent to modelling. This is essential to generate broad country-level ownership of the modelling data inputs and results. In turn, it stimulates discussions and a review of the current evidence and assumptions, strengthening the decision-making process in general.TIME Impact has been effectively applied in a variety of settings. In South Africa, it informed the first South African HIV and TB Investment Cases and successfully leveraged additional resources from the National Treasury at a time of austerity. In Ghana, a long-term TIME model-centred interaction with the NTP provided new insights into the local epidemiology and guided resource allocation decisions to improve impact.

Twitter Demographics

The data shown below were collected from the profiles of 13 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 187 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 1%
Mexico 1 <1%
United States 1 <1%
Unknown 183 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 19%
Student > Master 30 16%
Student > Ph. D. Student 27 14%
Other 10 5%
Student > Bachelor 9 5%
Other 33 18%
Unknown 43 23%
Readers by discipline Count As %
Medicine and Dentistry 51 27%
Nursing and Health Professions 22 12%
Social Sciences 13 7%
Immunology and Microbiology 10 5%
Mathematics 7 4%
Other 30 16%
Unknown 54 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 01 January 2021.
All research outputs
of 21,636,364 outputs
Outputs from BMC Medicine
of 3,169 outputs
Outputs of similar age
of 280,433 outputs
Outputs of similar age from BMC Medicine
of 1 outputs
Altmetric has tracked 21,636,364 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,169 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 41.4. This one is in the 47th percentile – i.e., 47% 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 280,433 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 1 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