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Alcohol consumption’s attributable disease burden and cost-effectiveness of targeted public health interventions: a systematic review of mathematical models
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Alcohol consumption’s attributable disease burden and cost-effectiveness of targeted public health interventions: a systematic review of mathematical models
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Journal Article
Alcohol consumption’s attributable disease burden and cost-effectiveness of targeted public health interventions: a systematic review of mathematical models
2019
Overview
Background
Around 6% of total deaths are related to alcohol consumption worldwide. Mathematical models are important tools to estimate disease burden and to assess the cost-effectiveness of interventions to address this burden.
Methods
We carried out a systematic review on models, searching main health literature databases up to July 2017. Pairs of reviewers independently selected, extracted data and assessed the quality of the included studies. Discrepancies were resolved by consensus. We selected those models exploring: a) disease burden (main metrics being attributable deaths, disability-adjusted life years, quality-adjusted life years) or b) economic evaluations of health interventions or policies, based on models including the aforementioned outcomes. We grouped models into broad families according to their common central methodological approach.
Results
Out of 4295 reports identified, 63 met our inclusion criteria and were categorized in three main model families that were described in detail: 1) State transition -i.e Markov- models, 2) Life Table-based models and 3) Attributable fraction-based models. Most studies pertained to the latter one (
n
= 29, 48.3%). A few miscellaneous models could not be framed into these families.
Conclusions
Our findings can be useful for future researchers and decision makers planning to undertake alcohol-related disease burden or cost-effectiveness studies. We found several different families of models. Countries interested in adopting relevant public health measures may choose or adapt the one deemed most convenient, based on the availability of existing data at the local level, burden of work, and public health and economic outcomes of interest.
Publisher
BioMed Central,BioMed Central Ltd,BMC
Subject
