Predicting the effectiveness of prevention: a role for epidemiological modeling

Walls, Helen L., Peeters, Anna, Reid, Christopher M., Liew, Danny and McNeil, John J. 2008, Predicting the effectiveness of prevention: a role for epidemiological modeling, Journal of primary prevention, vol. 29, no. 4, pp. 295-305, doi: 10.1007/s10935-008-0143-y.

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Title Predicting the effectiveness of prevention: a role for epidemiological modeling
Author(s) Walls, Helen L.
Peeters, AnnaORCID iD for Peeters, Anna orcid.org/0000-0003-4340-9132
Reid, Christopher M.
Liew, Danny
McNeil, John J.
Journal name Journal of primary prevention
Volume number 29
Issue number 4
Start page 295
End page 305
Total pages 11
Publisher Springer
Place of publication New York, N.Y.
Publication date 2008-07
ISSN 0278-095X
Keyword(s) Epidemiologic Methods
Health Care Costs
Health Policy
Health Priorities
Humans
Outcome Assessment (Health Care)
Primary Prevention
Science & Technology
Life Sciences & Biomedicine
Public, Environmental & Occupational Health
PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH, SSCI
Epidemiological modelling
Prevention
Prioritisation
CORONARY-HEART-DISEASE
COST-EFFECTIVENESS
DRUG-THERAPY
RISK
MORTALITY
SMOKING
STATINS
TRIALS
HEALTH
POLICY
Summary 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.
Language eng
DOI 10.1007/s10935-008-0143-y
Field of Research 111799 Public Health and Health Services not elsewhere classified
1117 Public Health And Health Services
Socio Economic Objective 920499 Public Health (excl. Specific Population Health) not elsewhere classified
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2008, Springer Science+Business Media, LLC
Persistent URL http://hdl.handle.net/10536/DRO/DU:30081695

Document type: Journal Article
Collections: Faculty of Health
School of Health and Social Development
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