The future excess fraction model for calculating burden of disease
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Published version
Author(s)
Type
Journal Article
Abstract
Background
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.
Methods
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.
Conclusions
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.
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.
Methods
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.
Conclusions
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.
Date Issued
2016-05-11
Date Acceptance
2016-04-29
Citation
BMC Public Health, 2016, 16
ISSN
1471-2458
Publisher
BioMed Central
Journal / Book Title
BMC Public Health
Volume
16
Copyright Statement
© 2016 Fritschi et al. This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
License URL
Subjects
Science & Technology
Life Sciences & Biomedicine
Public, Environmental & Occupational Health
Burden of disease
Methodology
Policy
Prevention
MALIGNANT PLEURAL MESOTHELIOMA
GLOBAL BURDEN
OCCUPATIONAL-CANCER
RISK
ASBESTOS
EXPOSURE
PROJECTIONS
BRITAIN
Public Health
1117 Public Health And Health Services
Publication Status
Published
Article Number
386