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This document describes a framework for quantitative assessment of health risks and benefits of dietary change, developed by the EU research project Qalibra. It also outlines how this framework has been implemented in software developed by Qalibra, which can be accessed (subject to registration) at www.qalibra.eu .
It is efficient to adopt a tiered approach to risk-benefit assessment, so that the degree of complexity and effort is adjusted to the needs of decision-making. The related EU project BRAFO has developed a tiered approach for risk-benefit assessment with 4 tiers: Tiers 1 and 2 use simpler methods to determine whether a quantitative assessment is necessary. The Qalibra framework and software are intended for quantitative assessment for risks and benefits, corresponding to Tiers 3 and 4 of the BRAFO approach.
This document begins by introducing the principles of risk-benefit assessment and the types of questions it can answer. It discusses the need for a common metric which enables different risks and benefits to be compared on the same scale, introduces the common metrics used in the Qalibra framework (disability-adjusted life years or DALYs, and quality-adjusted life years or QALYs), and explains how they are calculated in the Qalibra framework. The types of data and assumptions required for the calculations are described. The importance of addressing uncertainties is emphasised, and qualitative, deterministic and probabilistic methods for this are presented. Finally the document describes with examples the main types of output produced by the Qalibra software, and discusses its interpretation.
It is emphasised that risk-benefit assessment is inherently complex and requires a high level of expertise in the relevant fields of science including nutrition, toxicology and epidemiology. Quantitative risk-benefit assessment additionally requires significant expertise in modelling and statistics.
In this context it is hoped that the Qalibra framework will help by providing a common conceptual framework, and help users to identify important issues and data gaps. The Qalibra software is designed to provide a user-friendly environment within which users can start with a simple deterministic assessment and progressively refine it by treating key elements probabilistically (when needed). The software also helps the user to organise the large number of datasets and model runs that may be needed, and to share them with colleagues of their choosing.