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Calculate QCI component ratios

Source: R/ratios.R
qci_ratios.Rd

Computes the four epidemiological ratios that form the basis of the QCI:

  • MIR = Deaths / Incidence (Mortality-to-Incidence Ratio)

  • YLLtoYLD = YLLs / YLDs (YLL-to-YLD Ratio)

  • DALtoPER = DALYs / Prevalence (DALY-to-Prevalence Ratio)

  • PERtoINC = Prevalence / Incidence (Prevalence-to-Incidence Ratio)

Usage

qci_ratios(wide_number)

Arguments

wide_number

A data.table in wide format for the Number metric (the wide_number element from qci_clean()).

Value

The input data.table with 12 new columns appended: MIR, lower_MIR, upper_MIR, YLLtoYLD, lower_YLLtoYLD, upper_YLLtoYLD, DALtoPER, lower_DALtoPER, upper_DALtoPER, PERtoINC, lower_PERtoINC, upper_PERtoINC.

Details

Each ratio is computed for point estimates (val), upper, and lower uncertainty bounds. Inf and NaN values from division by zero are replaced with NA.

Examples

data(sample_gbd)
cleaned <- qci_clean(sample_gbd)
#> ✔ Cleaned data: 9 locations, 3 years.
with_ratios <- qci_ratios(cleaned$wide_number)
head(with_ratios[, .(location_name, year, MIR, YLLtoYLD, DALtoPER, PERtoINC)])
#>    location_name  year        MIR  YLLtoYLD  DALtoPER PERtoINC
#>           <char> <int>      <num>     <num>     <num>    <num>
#> 1:         China  1990 0.15101818 10.450506 0.7062324 20.75489
#> 2:         China  1990 0.12605741  8.187540 0.5649204 22.18755
#> 3:         China  1990 0.17373700 12.850767 0.8575658 19.33898
#> 4:         China  2005 0.08362720  3.988318 0.3092202 29.98444
#> 5:         China  2005 0.06973195  3.241955 0.2620949 30.86632
#> 6:         China  2005 0.09544737  4.676373 0.3531796 29.07491