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 Glossary
 Model parameters [current page]
 Summary
 1. Introduction
 1.1 General framework
 1.2 Relationship to the BRAFO tiered approach
 2. Problem formulation
 2.1 Dietary scenarios
 2.2 Population
 3. Common metrics for integration of risks & benefits
 3.1 DALY versus QALY.
 3.2 Alternative approaches for calculating DALY/QALYs
 4. Main elements of the Qalibra framework
 5. When is use of the Qalibra framework appropriate?
 6. Calculation of DALYs for quantal health effects
 7. Calculation of DALYs for continuous health effects
 8. Calculation of QALYs for quantal and continuous health effects
 9. Recurrent effects
 10. Effects on the next generation
 11. Multiple effects on the same health endpoint
 12. Calculating the net health impact of a dietary change
 13. Direct health loss calculations for a single individual
 14. Data needed as inputs to the Qalibra framework
 14.1 Individuals and their attributes
 14.2 Life expectancy
 14.3 Health effects to be quantified
 14.4 Dietary intakes
 14.5 Probability of quantal effects
 14.6 Probability and magnitude of continuous effects
 14.7 Probabilities of recovery and death
 14.8 Duration of disease
 14.9 Severity of effect (disease weights)
 15. Addressing uncertainty in riskbenefit assessment
 15.1 Qualitative evaluation of uncertainties
 15.2 Quantitative evaluation of uncertainties
 15.3 Probabilistic treatment of uncertainty in Qalibra
 16. Treatment of variability in the Qalibra framework
 17. Treatment of dependencies in Qalibra framework
 18. Presentation of results
 19. Interpretation of results
 20. Risk management considerations
 21. Final remarks
 Acknowledgements
 References
Model Parameters
Click on a parameter name to view the help for that parameter
Global Options
 Individuals

Parameter Help
A set of individuals I to be used in the model calculations. They may be real (e.g. from a dietary survey) or generic types (e.g. adults, children, vegetarians).
In simpler (lower tier) assessments, the model can be run for a single individual (e.g. an average or typical individual).
Each individual is represented by a row of data.
Single value help
A single value for age.
IMPORTANT
This parameter defines the number of individuals being modelled. Entering a single value here implies that the whole assessment, for all health effects, refers to a single individual who is assumed to represent either the whole population or some subgroup of particular interest (e.g. an average individual, or a high consumer). It also implies that the assessment cannot take account of variation in exposure or any other personal attribute (e.g. age, gender). However, such an assessment may be very useful for lower tier/screening purposes.
File Structure Help [show]
The file consists of a row for each of the individuals in your population.
Each row contains: The age I_{age} of each individual. This is required even when no health effects are agedependent, because current age is an essential part of the daly/qaly calculation.
 Any personal attributes (optional) that may be needed for this assessment, e.g. sex, smoker/nonsmoke, number of children
 A scaling factor I_{SF} specifying how many individuals in the true population this individual represents (this may come from dietary survey data).
IMPORTANT The first row should be a header row, containing the names of the columns
 If an enumeration has been used to represent a categorical attribute, the column header for that attribute must contain the letters 'enum'
 If the letters 'enum' do not appear, the attribute will be considered as a continuous attribute (e.g. bodyweight)
 All values in the file MUST be numeric e.g. sex may be represented by the enumeration 0 = Male, 1 = female
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
By supplying Attributes for the individuals, dependencies between these attributes and the values in the other datasets can then be specified e.g. sex specific probability of effect relationships.
Parameter specific questions
None  Life Expectancy

Parameter Help
Life expectancy is the average number of years of life remaining at a given age. The data provided should be relevant to the Individuals you include in your Model Run.Single value help
A single value for life expectancy, which is assumed to apply to all members of the population regardless of age and other factors.
File Structure Help [show]
Each row of the file represents a different subgroup defined by a set of upper bounds. individuals will be assigned a life expectancy value according to which Subgroup they belong.
Each row contains: An upper bound for I_{age} e.g. for I_{age} upper bounds 10, 20, 100 will contain individuals aged 0 – 10, 11 – 20 and 21100 respectively.
 Upper bounds for the attributes you specified (if any) in the individuals dataset
 Average life expectancy values LE for this Subgroup of the population. This may be a single value or multiple columns containing representing the uncertainty around the life expectancy. See the uncertainty page in Qalibra framework for more information.
IMPORTANT The first row should be a header row, containing the names of the columns
 All values in the file MUST be numeric e.g. sex may be represented by the enumeration 0 = Male, 1 = female
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
 To specify a Subgroup which is not dependent on a particular Attribute, leave the Attribute column blank (apart from the column name)
 If you use Subgroups, you must ensure they cover every value in the individuals file
Parameter specific questions
None
Health Effect
 Exposure Reference Scenario

Parameter Help
A measure of exposure or dose, in the Reference Scenario, for the substance or food type causing or associated with this health effect. The units of the exposure data must be the same as those used in the Probability of Effect (e.g. mg/kg bw/day, ml/person/day, portions of fish, etc.).Single value help
A single value representing exposure in the reference scenario, which is assumed to apply to all members of the population.
File Structure Help [show]
Each row of the file represents one of the individuals.
The file may contain a single column with one exposure value for each individual, or multiple columns containing representing the uncertainty around the exposure for each individual. See the uncertainty page in Qalibra framework for more information.
The units of the exposure data must be the same as those used in the probability of effect input (e.g. mg/kg bw/day, ml/person/day, portions of fish, etc.).
Note that the exposure files for the alternative scenario and reference scenario both refer to the same set of individuals, and their exposures should be listed in the same order in both files.
Often, intakes of different foods or substances in the same assessment will be correlated (e.g. fish intake is correlated with methyl mercury intake). Where such correlations exist, it is the responsibility of the user to represent them appropriately in the input data (e.g. the fish intake for an individual should be consistent with the methyl mercury intake for the same individual). Qalibra will then keep these intakes together in the calculations and thus incorporate the correlation specified by the user.
IMPORTANT The first row should be a header row, containing the names of the columns. Names are not essential but the header row must be included even if it is empty.
 All values in the file MUST be numeric
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
 If uncertainty iterations are provided, there must be the same number of columns in the exposure alternative scenario file
Parameter specific questions
None  Exposure Alternative Scenario

Parameter Help
A measure of exposure or dose, in the alternative scenario, for the substance or food type causing or associated with this health effect. The units of the exposure data must be the same as those used in the probability of effect (e.g. mg/kg bw/day, ml/person/day, portions of fish, etc.).Single value help
A single value representing exposure in the alternative scenario, which is assumed to apply to all members of the population.
File Structure Help [show]
Each row of the file represents one of the individuals.
The file may contain a single column with one exposure value for each individual, or multiple columns containing representing the uncertainty around the exposure for each individual. See the uncertainty page in Qalibra framework for more information.
The units of the exposure data must be the same as those used for dose in the probability of effect (e.g. mg/kg bw/day, ml/person/day, portions of fish, etc.).
Note that the exposure files for the alternative scenario and reference scenario both refer to the same set of individuals, and their exposures should be listed in the same order in both files.
Often, intakes of different foods or substances in the same assessment will be correlated (e.g. fish intake is correlated with methyl mercury intake). Where such correlations exist, it is the responsibility of the user to represent them appropriately in the input data (e.g. the fish intake for an individual should be consistent with the methyl mercury intake for the same individual). Qalibra will then keep these intakes together in the calculations and thus incorporate the correlation specified by the user.
IMPORTANT The first row should be a header row, containing the names of the columns
 All values in the file MUST be numeric
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
 If uncertainty iterations are provided, there must be the same number of columns in the exposure reference scenario file
Parameter specific questions
None  Probability of Effect

Parameter Help
Describes the probability that individuals get that health effect at different levels of exposure to a chemical, nutrient or food type. Can also be a function of individual attributes such as age, gender, etc.
Single value help
A threshold dose  individuals with exposures greater than this dose always get the health effect.
File Structure Help [show]
Each row of the file represents a different combination of exposure and subgroup defined by a set of upper bounds. individuals will be assigned a probability of effect value according to which Subgroup they belong.
Each row contains: An upper bound for I_{age} e.g. for I_{age} upper bounds 10, 20, 100 will contain individuals aged 0 – 10, 11 – 20 and 21100 respectively.
 Upper bounds for the attributes you specified (if any) in the individuals dataset
 Exposure levels. For individuals with exposures lying between two of these exposure levels, their probability of effect value will be calculated by linear interpolation. The user must ensure the number and spacing of exposure levels specified is sufficient to ensure adequate approximation to the actual relationship between the probability of effect and exposure (which is often nonlinear). These exposure levels must cover the range of values in the corresponding exposure files.
 Probability of effect value P_{eff} for this Subgroup of the population. These values should be the proportion of individuals affected e.g. 0.1, 0.2, 0.3. P_{eff} may be a single value or multiple columns representing the uncertainty around the probability of effect. See the uncertainty page in Qalibra framework for more information.
IMPORTANT The first row should be a header row, containing the names of the columns
 All values in the file MUST be numeric e.g. sex may be represented by the enumeration 0 = Male, 1 = female
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
 To specify a subgroup which is not dependent on a particular attribute, leave the attribute column blank (apart from the column name)
 The total number of rows = one (the header row) + the number of exposure levels used to represent the probability of effect x by the number of subgroups that have different probability of effect relationships.
 If the same probability of effect relationship applies to all individuals, the age and attributes columns must be present but should be left blank, and the number of rows should equal to the number of exposure levels plus one (the header row).
 If you use subgroups, you must ensure they cover every value in the individuals
Parameter specific questions
None  Magnitude of Effect

Parameter Help
Describes the effect size that individuals get from a health effect at different levels of exposure to a chemical, nutrient or food type. Can also be a function of individual attributes such as age, gender, etc.Single value help
Single values for this parameter are not permitted.
File Structure Help [show]
Each row of the file represents a different combination of exposure and subgroup defined by a set of upper bounds. individuals will be assigned a magnitude of effect value according to which subgroup they belong.
Each row contains: An upper bound for I_{age} e.g. for I_{age} upper bounds 10, 20, 100 will contain individuals aged 0 – 10, 11 – 20 and 21100 respectively.
 Upper bounds for the attributes you specified (if any) in the individuals dataset
 Exposure (or dose) levels. For individuals with exposures lying between two of these exposure levels, their magnitude of effect value will be calculated by linear interpolation. The user must ensure the number and spacing of exposure levels specified is sufficient to ensure adequate approximation to the actual relationship between magnitude of effect and exposure (which is often nonlinear). These exposure levels must cover the range of values in the corresponding exposure files.
 Magnitude of effect value M_{eff} for this subgroup of the population.
 M_{eff} may be a single value or multiple columns representing the uncertainty around M_{eff}. See the uncertainty page in Qalibra framework for more information.
IMPORTANT The first row should be a header row, containing the names of the columns
 All values in the file MUST be numeric e.g. sex may be represented by the enumeration 0 = Male, 1 = female
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
 To specify a Subgroup which is not dependent on a particular attribute, leave the attribute column blank (apart from the column name)
 The total number of rows = one (the header row) + the number of exposure levels used to represent the magnitude of effect x by the number of subgroups that have different probability of effect relationships.
 If the same magnitude of effect relationship applies to all individuals, the age and attributes columns must be present but should be left blank, and the number of rows should equal to the number of exposure levels plus one (the header row).
 If you use subgroups, you must ensure they cover every value in the individuals file
Parameter specific questions
None  Weight if Recover (from effect)

Parameter Help
A value between 0 and 1 that describes, for those who recover, the severity of the health effect. This can be a function of individual attributes such as age, gender, etc. For quantal effects, the weight can be a function of exposure. For continuous effects, the weight can be a function of effect size. If calculating DALYs, a value of 0 indicates that the health effect has no adverse effects and is equivalent to ‘perfect health’. A value of 1 indicates that the health effect is equivalent to death. For QALYs, the reverse is true.Single value help
The severity of the health effect for those who recover. If using dalys, 0 implies no adverse effects, 1 implies the effect is equivalent to death. For qalys the reverse is true. When a single value is specified it is assumed the severity of the effect is the same for all those who recover, regardless of age and other factors. Single value input is not appropriate for continuous effects, where severity must be a function of the effect size.
File Structure Help [show]
Each row of the file represents a different subgroup defined by a set of upper bounds. individuals will be assigned a response value according to which subgroup they belong.
Each row contains: An upper bound for I_{age} e.g. for I_{age} upper bounds 10, 20, 100 will contain individuals aged 0 – 10, 11 – 20 and 21100 respectively.
 Upper bounds for the attributes you specified (if any) in the individuals dataset
 If the health effect is a quantal effect, the file must include a column for exposure (or dose) levels. If the severity of the effect (as well as its occurrence) is not related to dose, then this column should be left blank (apart from the column name). If severity is related to dose, the relationship can be specified by using this column to specify upper bounds for a series of exposure levels, and the following columns to show the corresponding weights representing the severity of the effect. For individuals lying between the specified exposure levels, the weight will be calculated by linear interpolation. The exposure levels must cover the range of values in the corresponding exposure files.
 If the health effect is a continuous effect, the file must include a column for effect size. This column should be used to specify how the severity of the health effect is related to effect size, by entering upper bounds for a series of effect sizes, and using the following columns to show the corresponding weights representing the severity of the effect. For individuals lying between the specified effect sizes, the weight will be calculated by linear interpolation. The user must ensure that the effect sizes cover the range of values that will be generated by probability of effect for the Continuous Effect.
 W_{rec} may be a single value or multiple columns containing representing the uncertainty around the weight. See the uncertainty page in Qalibra framework for more information.
IMPORTANT The first row should be a header row, containing the names of the columns
 All values in the file MUST be numeric e.g. sex may be represented by the enumeration 0 = Male, 1 = female
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
 To specify a subgroup which is not dependent on a particular attribute, leave the attribute column blank (apart from the column name)
 If you use Subgroups, you must ensure they cover every value in the individuals file
Parameter specific questions
None  Weight if Die (from effect)

Parameter Help
A value between 0 and 1 that describes, for those who die of the health effect, the severity of the effect during the period prior to death. This can be a function of individual attributes such as age, gender, etc. For quantal effects, the weight can be a function of exposure. For continuous effects, the weight can be a function of effect size. If calculating DALYs, a value of 0 indicates that the health effect has no adverse effects and is equivalent to ‘perfect health’. A value of 1 indicates that the health effect is equivalent to death. For QALYs, the reverse is true.Single value help
The severity of the health effect for those who die. If using dalys 0 implies no adverse effects, 1 implies the effect is equivalent to death. For qalys the reverse is true. When a single value is specified it is assumed the severity of the effect is the same for all those who recover, regardless of age and other factors. A single value input is not appropriate for continuous effects, where severity must be a function of the effect size.
File Structure Help [show]
Each row of the file represents a different subgroup defined by a set of upper bounds. individuals will be assigned a response value according to which subgroup they belong.
Each row contains: An upper bound for I_{age} e.g. for I_{age} upper bounds 10, 20, 100 will contain individuals aged 0 – 10, 11 – 20 and 21100 respectively.
 Upper bounds for the attributes you specified (if any) in the individuals dataset
 If the health effect is a quantal effect, the file must include a column for exposure (or dose) levels. If the severity of the effect (as well as its occurrence) is not related to dose, then this column should be left blank (apart from the column name). If severity is related to dose, the relationship can be specified by using this column to specify upper bounds for a series of exposure levels, and the following columns to show the corresponding weights representing the severity of the effect. For individuals lying between the specified exposure levels, the weight will be calculated by linear interpolation. The exposure levels must cover the range of values in the corresponding exposure files.
 If the health effect is a continuous effect, the file must include a column for effect size. This column should be used to specify how the severity of the health effect is related to effect size, by entering upper bounds for a series of effect sizes, and using the following columns to show the corresponding weights representing the severity of the effect. For individuals lying between the specified effect sizes, the weight will be calculated by linear interpolation. The user must ensure that the effect sizes cover the range of values that will be generated by probability of effect for the Continuous Effect.
 W_{die} may be a single value or multiple columns containing representing the uncertainty around the weight. See the uncertainty page in Qalibra framework for more information.
IMPORTANT The first row should be a header row, containing the names of the columns
 All values in the file MUST be numeric e.g. sex may be represented by the enumeration 0 = Male, 1 = female
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
 To specify a subgroup which is not dependent on a particular attribute, leave the attribute column blank (apart from the column name)
 If you use subgroups, you must ensure they cover every value in the individuals file
Parameter specific questions
None  Weight if Live (with effect)

Parameter Help
A value between 0 and 1 that describes, for those who live for the rest of their normal life with the effect, the severity of the health effect. This can be a function of individual attributes such as age, gender, etc. For quantal effects, the weight can be a function of exposure. For continuous effects, the weight can be a function of effect size. If calculating DALYs, a value of 0 indicates that the health effect has no adverse effects and is equivalent to ‘perfect health’. A value of 1 indicates that the health effect is equivalent to death. For QALYs, the reverse is true.Single value help
The severity of the health effect for those who live with the effect for the rest of their life. If using dalys 0 implies no adverse effects, 1 implies the effect is equivalent to death. For qalys the reverse is true. When a single value is specified it is assumed the severity of the effect is the same for all those who recover, regardless of age and other factors. Single value input is not appropriate for continuous effects, where severity must be a function of the effect size.
File Structure Help [show]
Each row of the file represents a different subgroup defined by a set of upper bounds. individuals will be assigned a response value according to which subgroup they belong.
Each row contains: An upper bound for I_{age} e.g. for I_{age} upper bounds 10, 20, 100 will contain individuals aged 0 – 10, 11 – 20 and 21100 respectively.
 Upper bounds for the attributes you specified (if any) in the individuals dataset
 If the health effect is a quantal effect, the file must include a column for exposure (or dose) levels. If the severity of the effect (as well as its occurrence) is not related to dose, then this column should be left blank (apart from the column name). If severity is related to dose, the relationship can be specified by using this column to specify upper bounds for a series of exposure levels, and the following columns to show the corresponding weights representing the severity of the effect. For individuals lying between the specified exposure levels, the weight will be calculated by linear interpolation. The exposure levels must cover the range of values in the corresponding exposure files.
 If the health effect is a continuous effect, the file must include a column for effect size. This column should be used to specify how the severity of the health effect is related to effect size, by entering upper bounds for a series of effect sizes, and using the following columns to show the corresponding weights representing the severity of the effect. For individuals lying between the specified effect sizes, the weight will be calculated by linear interpolation. The user must ensure that the effect sizes cover the range of values that will be generated by the probability of effect for the continuous effect.
 W_{live}_{ }may be a single value or multiple columns containing representing the uncertainty around the weight. See the uncertainty page in Qalibra framework for more information.
IMPORTANT The first row should be a header row, containing the names of the columns
 All values in the file MUST be numeric e.g. sex may be represented by the enumeration 0 = Male, 1 = female
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
 To specify a subgroup which is not dependent on a particular attribute, leave the attribute column blank (apart from the column name)
 If you use subgroups, you must ensure they cover every value in the individuals file
Parameter specific questions
None  Recovery Probablility

Parameter Help
The probability (value between 0 and 1) that someone recovers (completely) from the health effect. Often this will be a single number, but optionally P_{rec} may depend on characteristics such as age or sex, and/or be a function of exposure (dose).Single value help
A single value representing the probability of recovery, which is assumed to apply to all members of the population who experience the health effect. E.g. if 30% of affected individuals recover, the recovery probability is 0.3.
File Structure Help [show]
Each row of the file represents a different subgroup defined by a set of upper bounds. individuals will be assigned a response value according to which subgroup they belong.
Each row contains: An upper bound for I_{age} e.g. for I_{age} upper bounds 10, 20, 100 will contain individuals aged 0 – 10, 11 – 20 and 21100 respectively.
 Upper bounds for the attributes you specified (if any) in the individuals dataset
 A column for exposure. If the probability of recovery is not dependent on the level of exposure, then this column should be left blank (apart from the column name). If P_{rec} is related to exposure, the relationship can be specified by using this column to specify upper bounds for a series of exposure levels, and the following columns to show the corresponding values of P_{rec}. For individuals lying between the specified exposure levels, P_{rec} will be calculated by linear interpolation. The specified exposure levels must cover the range of values in the corresponding exposure files.
 P_{rec} may be a single value or multiple columns containing representing the uncertainty around the probability. See the uncertainty page in Qalibra framework for more information.
IMPORTANT The first row should be a header row, containing the names of the columns
 All values in the file MUST be numeric e.g. sex may be represented by the enumeration 0 = Male, 1 = female
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
 To specify a subgroup which is not dependent on a particular attribute, leave the attribute column blank (apart from the column name)
 If you use subgroups, you must ensure they cover every value in the individuals file
Parameter specific questions
None  YLD if Recover

Parameter Help
The average duration (in years) of the health effect before someone recovers. Often this is a single number but optionally it may depend on characteristics such as age or sex, and/or be a function of exposure.Single value help
A single value representing the average duration (in years) of the health effect before someone recovers, which is assumed to apply to all members of the population who recover from the effect.
File Structure Help [show]
Each row of the file represents a different subgroup defined by a set of upper bounds. individuals will be assigned a response value according to which subgroup they belong.
Each row contains: An upper bound for I_{age} e.g. for I_{age} upper bounds 10, 20, 100 will contain individuals aged 0 – 10, 11 – 20 and 21100 respectively.
 Upper bounds for the attributes you specified (if any) in the individuals dataset
 A column for exposure. If the YLD_{rec} is not dependent on the level of exposure, then this column should be left blank (apart from the column name). If YLD_{rec} is related to exposure, the relationship can be specified by using this column to specify upper bounds for a series of exposure levels, and the following columns to show the corresponding values of YLD_{rec}. For individuals lying between the specified exposure levels, YLD_{rec} will be calculated by linear interpolation. The specified exposure levels must cover the range of values in the corresponding exposure files.
 YLD_{rec} may be a single value or multiple columns containing representing the uncertainty around the number of years. See the uncertainty page in Qalibra framework for more information.
IMPORTANT The first row should be a header row, containing the names of the columns
 All values in the file MUST be numeric e.g. sex may be represented by the enumeration 0 = Male, 1 = female
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
 To specify a subgroup which is not dependent on a particular attribute, leave the attribute column blank (apart from the column name)
 If you use subgroups, you must ensure they cover every value in the individuals file
Parameter specific questions
None  Death (from effect) Probability

Parameter Help
The probability (value between 0 and 1) that someone who has the health effect dies early as a result of it. Often this will be a single number, but optionally P_{die} may depend on characteristics such as age or sex, and/or be a function of exposure (dose).Single value help
A single value representing the probability of death, which is assumed to apply to all members of the population who experience the health effect. E.g. if 30% of affected individuals die, Pdie is 0.3.
File Structure Help [show]
Each row of the file represents a different subgroup defined by a set of upper bounds. individuals will be assigned a response value according to which subgroup they belong.
Each row contains: An upper bound for I_{age} e.g. for I_{age} upper bounds 10, 20, 100 will contain individuals aged 0 – 10, 11 – 20 and 21100 respectively.
 Upper bounds for the attributes you specified (if any) in the individuals dataset
 A column for exposure. If P_{die} is not dependent on the level of exposure, then this column should be left blank (apart from the column name). If P_{die} is related to exposure, the relationship can be specified by using this column to specify upper bounds for a series of exposure levels, and the following columns to show the corresponding values of P_{die}. For individuals lying between the specified exposure levels, P_{die} will be calculated by linear interpolation. The specified exposure levels must cover the range of values in the corresponding exposure files.
 P_{die} may be a single value or multiple columns containing representing the uncertainty around the probability. See the uncertainty page in Qalibra framework for more information.
IMPORTANT The first row should be a header row, containing the names of the columns
 All values in the file MUST be numeric e.g. sex may be represented by the enumeration 0 = Male, 1 = female
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
 To specify a subgroup which is not dependent on a particular attribute, leave the attribute column blank (apart from the column name)
 If you use subgroups, you must ensure they cover every value in the individuals file
Parameter specific questions
None  YLD if Die (from effect)

Parameter Help
The average duration (in years) of the health effect, for those individuals who die as a result of it. Often this is a single number but optionally it may depend on characteristics such as age or sex, and/or be a function of exposure.Single value help
A single value representing the average duration (in years) of the health effect for someone who dies of it, which is assumed to apply to all members of the population who die from the effect.
File Structure Help [show]
Each row of the file represents a different subgroup defined by a set of upper bounds. individuals will be assigned a response value according to which subgroup they belong.
Each row contains: An upper bound for I_{age} e.g. for I_{age} upper bounds 10, 20, 100 will contain individuals aged 0 – 10, 11 – 20 and 21100 respectively.
 Upper bounds for the attributes you specified (if any) in the individuals dataset
 A column for exposure. If YLD_{die} is not dependent on the level of exposure, then this column should be left blank (apart from the column name). If YLD_{die} is related to exposure, the relationship can be specified by using this column to specify upper bounds for a series of exposure levels, and the following columns to show the corresponding values of YLD_{die}. For individuals lying between the specified exposure levels, YLD_{die} will be calculated by linear interpolation. The specified exposure levels must cover the range of values in the corresponding exposure files.
 YLD_{die} may be a single value or multiple columns containing representing the uncertainty around the number of years. See the uncertainty page in Qalibra framework for more information.
IMPORTANT The first row should be a header row, containing the names of the columns
 All values in the file MUST be numeric e.g. sex may be represented by the enumeration 0 = Male, 1 = female
 The file must be ‘rectangular’ – rows must be equal lengths and columns must be equal lengths
 To specify a subgroup which is not dependent on a particular attribute, leave the attribute column blank (apart from the column name)
 If you use subgroups, you must ensure they cover every value in the individuals file
Parameter specific questions
None