Predicting the effectiveness of prevention: A role for epidemiological modeling
It is well known that the current combination of aging populations and advances in health technology is resulting in burgeoning health costs in developed countries. Prevention is a potentially important way of containing health costs. In an environment of intense cost pressures, coupled with develop...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Published: |
Springer
2008
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| Online Access: | http://hdl.handle.net/20.500.11937/24011 |
| _version_ | 1848751310611939328 |
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| author | Walls, H. Peeters, A. Reid, Christopher Liew, D. McNeil, J. |
| author_facet | Walls, H. Peeters, A. Reid, Christopher Liew, D. McNeil, J. |
| author_sort | Walls, H. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | It is well known that the current combination of aging populations and advances in health technology is resulting in burgeoning health costs in developed countries. Prevention is a potentially important way of containing health costs. In an environment of intense cost pressures, coupled with developments in disease prevention and health promotion, it is increasingly important for decision-makers to have a systematic, coordinated approach to the targeting and prioritization of preventive strategies. However, such a systematic approach is made difficult by the fact that preventive strategies need to be compared over the long term, in a variety of populations, and in real life settings not found in most trials. Information from epidemiological models can provide the required evidence base. In this review, we outline the role of epidemiological modeling in this context and detail its application using examples. Editors' Strategic Implications: Policymakers and researchers will benefit from this description of the utility of epidemiological modeling as a means of generating translational evidence that helps to prioritize data-based prevention approaches and bridge the gap between clinical research and public health practice. © 2008 Springer Science+Business Media, LLC. |
| first_indexed | 2025-11-14T07:50:42Z |
| format | Journal Article |
| id | curtin-20.500.11937-24011 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:50:42Z |
| publishDate | 2008 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-240112017-09-13T13:56:21Z Predicting the effectiveness of prevention: A role for epidemiological modeling Walls, H. Peeters, A. Reid, Christopher Liew, D. McNeil, J. It is well known that the current combination of aging populations and advances in health technology is resulting in burgeoning health costs in developed countries. Prevention is a potentially important way of containing health costs. In an environment of intense cost pressures, coupled with developments in disease prevention and health promotion, it is increasingly important for decision-makers to have a systematic, coordinated approach to the targeting and prioritization of preventive strategies. However, such a systematic approach is made difficult by the fact that preventive strategies need to be compared over the long term, in a variety of populations, and in real life settings not found in most trials. Information from epidemiological models can provide the required evidence base. In this review, we outline the role of epidemiological modeling in this context and detail its application using examples. Editors' Strategic Implications: Policymakers and researchers will benefit from this description of the utility of epidemiological modeling as a means of generating translational evidence that helps to prioritize data-based prevention approaches and bridge the gap between clinical research and public health practice. © 2008 Springer Science+Business Media, LLC. 2008 Journal Article http://hdl.handle.net/20.500.11937/24011 10.1007/s10935-008-0143-y Springer restricted |
| spellingShingle | Walls, H. Peeters, A. Reid, Christopher Liew, D. McNeil, J. Predicting the effectiveness of prevention: A role for epidemiological modeling |
| title | Predicting the effectiveness of prevention: A role for epidemiological modeling |
| title_full | Predicting the effectiveness of prevention: A role for epidemiological modeling |
| title_fullStr | Predicting the effectiveness of prevention: A role for epidemiological modeling |
| title_full_unstemmed | Predicting the effectiveness of prevention: A role for epidemiological modeling |
| title_short | Predicting the effectiveness of prevention: A role for epidemiological modeling |
| title_sort | predicting the effectiveness of prevention: a role for epidemiological modeling |
| url | http://hdl.handle.net/20.500.11937/24011 |