Review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy
Predictions of future cases of asbestos-related disease have been undertaken at a national level to inform government policy and planning for future health needs. In general, we can separate the methods used to predict future cases of mesothelioma into models that use a) direct or b) indirect estima...
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| Format: | Journal Article |
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Australia and New Zealand School of Government ANZSOG
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/38771 |
| _version_ | 1848755410097405952 |
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| author | Reid, Alison |
| author_facet | Reid, Alison |
| author_sort | Reid, Alison |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Predictions of future cases of asbestos-related disease have been undertaken at a national level to inform government policy and planning for future health needs. In general, we can separate the methods used to predict future cases of mesothelioma into models that use a) direct or b) indirect estimates of asbestos exposure. Direct estimates are those that have been derived mostly for occupationally exposed cohorts, where airborne fibre levels were measured over time. Indirect estimates tend to be information about total or fibre-specific asbestos imports or use from a range of time points. Most predictions undertaken at the national level have predicted future cases for males only and assume that indirect estimates of asbestos consumption reflect occupational asbestos exposure. These models tend to fit the observed data reasonably well but have undergone several refinements in order to improve their fit. Fewer attempts have been made to predict cases of mesothelioma resulting from non-occupational asbestos exposure, and most have not subsequently revisited their prediction to ascertain its accuracy so the robustness of these methods is unclear. Because of the change in asbestos use in recent decades, more attention should be paid to understanding the risks and burden of future cases arising from non-occupational exposure. A range of current data exist that should be sufficient to incorporate into models to predict future cases of mesothelioma arising from non-occupational asbestos exposure. Models could be tested for their accuracy by comparing them against the most recent 10 years of observed cases or against cases in women, whose most common source of exposure is non-occupational. |
| first_indexed | 2025-11-14T08:55:51Z |
| format | Journal Article |
| id | curtin-20.500.11937-38771 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:55:51Z |
| publishDate | 2016 |
| publisher | Australia and New Zealand School of Government ANZSOG |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-387712017-09-13T14:19:37Z Review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy Reid, Alison Predictions of future cases of asbestos-related disease have been undertaken at a national level to inform government policy and planning for future health needs. In general, we can separate the methods used to predict future cases of mesothelioma into models that use a) direct or b) indirect estimates of asbestos exposure. Direct estimates are those that have been derived mostly for occupationally exposed cohorts, where airborne fibre levels were measured over time. Indirect estimates tend to be information about total or fibre-specific asbestos imports or use from a range of time points. Most predictions undertaken at the national level have predicted future cases for males only and assume that indirect estimates of asbestos consumption reflect occupational asbestos exposure. These models tend to fit the observed data reasonably well but have undergone several refinements in order to improve their fit. Fewer attempts have been made to predict cases of mesothelioma resulting from non-occupational asbestos exposure, and most have not subsequently revisited their prediction to ascertain its accuracy so the robustness of these methods is unclear. Because of the change in asbestos use in recent decades, more attention should be paid to understanding the risks and burden of future cases arising from non-occupational exposure. A range of current data exist that should be sufficient to incorporate into models to predict future cases of mesothelioma arising from non-occupational asbestos exposure. Models could be tested for their accuracy by comparing them against the most recent 10 years of observed cases or against cases in women, whose most common source of exposure is non-occupational. 2016 Journal Article http://hdl.handle.net/20.500.11937/38771 10.4225/50/57CDFEBB71B93 Australia and New Zealand School of Government ANZSOG fulltext |
| spellingShingle | Reid, Alison Review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy |
| title | Review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy |
| title_full | Review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy |
| title_fullStr | Review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy |
| title_full_unstemmed | Review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy |
| title_short | Review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy |
| title_sort | review of the effectiveness of predictive models for mesothelioma to identify lessons for asbestos-related policy |
| url | http://hdl.handle.net/20.500.11937/38771 |