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The future excess fraction model for calculating burden of disease

Overview of attention for article published in BMC Public Health, May 2016
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The future excess fraction model for calculating burden of disease
Published in
BMC Public Health, May 2016
DOI 10.1186/s12889-016-3066-1
Pubmed ID

Lin Fritschi, Jayzii Chan, Sally J. Hutchings, Tim R. Driscoll, Adrian Y. W. Wong, Renee N. Carey


Estimates of the burden of disease caused by a particular agent are used to assist in making policy and prioritizing actions. Most estimations have employed the attributable fraction approach, which estimates the proportion of disease cases or deaths in a specific year which are attributable to past exposure to a particular agent. While this approach has proven extremely useful in quantifying health effects, it requires historical data on exposures which are not always available. We present an alternative method, the future excess fraction method, which is based on the lifetime risk approach, and which requires current rather than historical exposure data. This method estimates the future number of exposure-related disease cases or deaths occurring in the subgroup of the population who were exposed to the particular agent in a specific year. We explain this method and use publically-available data on current asbestos exposure and mesothelioma incidence to demonstrate the use of the method. Our approach to modelling burden of disease is useful when there are no historical measures of exposure and where future disease rates can be projected on person years at risk.

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 14%
Researcher 2 14%
Student > Bachelor 2 14%
Unspecified 1 7%
Student > Master 1 7%
Other 3 21%
Unknown 3 21%
Readers by discipline Count As %
Medicine and Dentistry 5 36%
Nursing and Health Professions 3 21%
Unspecified 1 7%
Social Sciences 1 7%
Business, Management and Accounting 1 7%
Other 1 7%
Unknown 2 14%