One modelling group does not provide DALYs, and we need to calculate those, both for their central estimates (already uploaded to Montagu), and their stochastic estimates (provided as CSV files). The DALYs calculation is a simple function of the life expectancy of people (of a given age and country in a given year), and various weighted contributions of different burden outcomes.

stoner_calculate_dalys(
  con,
  touchstone,
  data,
  dalys_params,
  life_table = NULL,
  year_min = 2000,
  year_max = 2100
)

Arguments

con

DBI connection to a Montagu database. Used for retrieving demographic data for life expectancy.

touchstone

The touchstone (including version); the demographic data retrieved will be specific to this touchstone.

data

A data.frame containing burden estimates - either central or stochastic. The columns for both kinds will include country (which may be a Montagu numerical id, or the 3-letter code), year, age, and a number of burden outcomes.Stochastic data will also have a run_id.

dalys_params

A data.frame containing how to calculate dalys; each row represents a condition, and the four columns describe how to calculate the cost of that condition across the population in that year. For each condition, the outcome column must provide a burden outcome (which will be a column name in data). The proportion is the proportion of people reported as that outcome, who suffer this condition. average_duration is the number of years for which the condition is suffered, set to greater than 120 for a life-long period. And disability_weight is a measure of how severe the implications are of this particular condition. See http://ghdx.healthdata.org/record/ihme-data/gbd-2017-disability-weights for where these figures come from; the final figures are decided in discussion with the groups.

life_table

If NULL, then the life table will be looked up and interpolated to yearly for age and time. This takes a bit of time, so the resulting data is part of what this function returns, and the life table part can be provided here to speed things up. If provided, it should be a data.frame with the columns value and .code; the latter is in the format country-year-age. The type of country in .code should match with the type of the country in data. The years and ages will be interpolated down to single-years.

year_min

The first year of the range in which to calculate DALYs. (Default 2000)

year_max

The final year of the range in which to calculate DALYs. (Default 2100)

Value

A list with two named components; life_table is the result of calling the life-table function, which can then be specified in subsequent calls to stoner_calculate_dalys, and data is a version of the original dataset, now with a dalys column. Note that if data already contained a dalys column when provided to the function, that column will be overwritten with the new results.