ArticleThe journal of primary prevention2008
Predicting the effectiveness of prevention: a role for epidemiological modeling.
Article in The journal of primary prevention, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of economic evaluations of interventions to tackle cardiovascular disease in low- and middle-income countries.BMC public health · 2012Pooled it
- Catastrophic Health Expenditure and Its Determinants in Patients With Ischemic Heart Disease and Their Households: A Cross-Sectional Study From Iran in 2024.Health science reports · 2025Article
- Temporal trends in cardiovascular disease risk factors attributed burden in Iran, 1990-2021.Scientific reports · 2025Article
- Estimation of myocardial infarction death in Iran: artificial neural network.BMC cardiovascular disorders · 2022Article
- The age-related decline in spatiotemporal gait characteristics is moderated by concerns of falling, history of falls & diseases, and sociodemographic-anthropometric characteristics in 60-94 years old adults.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2021Article
- Modelling microbial infection to address global health challenges.Nature microbiology · 2019Review
- Modeling the Burden of Cardiovascular Diseases in Iran from 2005 to 2025: The Impact of Demographic Changes.Iranian journal of public health · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
18581234What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.