R/data.R
In lshtm-vimc/prime: PRIME -- Papillomavirus Rapid Interface for Modelling and Economics
# Data.R - This file includes documentation of datasets.
#' 1-year prevalence of cervical cancer
#'
#' A dataset containing the 1-year prevalence (proportion) of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2018 database.
#'
#' As per IARC definition -- The (1-year) prevalence of a given cancer
#' is the number of individuals within a defined population who have been diagnosed with that
#' cancer (within 1 year) and who are still alive at a given point in time (i.e. the survivors).
#'
#' @format A data table containing 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.cecx_1y_prevalence"
#' 1-year prevalence of cervical cancer
#'
#' A dataset containing the 1-year prevalence (proportion) of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2020 database.
#'
#' As per IARC definition -- The (1-year) prevalence of a given cancer
#' is the number of individuals within a defined population who have been diagnosed with that
#' cancer (within 1 year) and who are still alive at a given point in time (i.e. the survivors).
#'
#' @format A data table containing 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table?v=2020}
"data.cecx_1y_prevalence2020"
#' 3-year prevalence of cervical cancer
#'
#' A dataset containing the 3-year prevalence (proportion) of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2018 database.
#'
#' As per IARC definition -- The (3-year) prevalence of a given cancer
#' is the number of individuals within a defined population who have been diagnosed with that
#' cancer (within 3 years) and who are still alive at a given point in time (i.e. the survivors).
#'
#' @format A data table containing 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.cecx_3y_prevalence"
#' 3-year prevalence of cervical cancer
#'
#' A dataset containing the 3-year prevalence (proportion) of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2020 database.
#'
#' As per IARC definition -- The (3-year) prevalence of a given cancer
#' is the number of individuals within a defined population who have been diagnosed with that
#' cancer (within 3 years) and who are still alive at a given point in time (i.e. the survivors).
#'
#' @format A data table containing 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table?v=2020}
"data.cecx_3y_prevalence2020"
#' 5-year prevalence of cervical cancer
#'
#' A dataset containing the 5-year prevalence (proportion) of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2018 database.
#'
#' As per IARC definition -- The (5-year) prevalence of a given cancer
#' is the number of individuals within a defined population who have been diagnosed with that
#' cancer (within 5 years) and who are still alive at a given point in time (i.e. the survivors).
#'
#' @format A data table with 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.cecx_5y_prevalence"
#' 5-year prevalence of cervical cancer
#'
#' A dataset containing the 5-year prevalence (proportion) of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2020 database.
#'
#' As per IARC definition -- The (5-year) prevalence of a given cancer
#' is the number of individuals within a defined population who have been diagnosed with that
#' cancer (within 5 years) and who are still alive at a given point in time (i.e. the survivors).
#'
#' @format A data table with 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table?v=2020}
"data.cecx_5y_prevalence2020"
#' Cost of cervical cancer treatment
#'
#' A dataset containing the cost of cervical cancer treatment.
#'
#' @format A data table with 194 observations of 7 variables.
#' \describe{
#' \item{country}{Country name}
#' \item{cancer_cost}{cost per cancer episode, in 2017 US$}
#' \item{cancer_cost_adj}{cost per cancer episode -- adjusted, in 2017 US$ --
#' “adjusted” cancer costs are based on a GDP/capita based adjustment
#' within the region}
#' \item{iso3}{ISO3 country code}
#' \item{cancer_cost_2011}{cost per cancer episode, in 2011 US$}
#' \item{cancer_cost_adj_2011}{cost per cancer episode --
#' adjusted, in 2011 US$ -- “adjusted” cancer costs are based on a
#' GDP/capita based adjustment within the region}
#' \item{inflation_factor}{Inflation factor from 2011 to 2017 estimated from
#' Inflation, GDP deflator (annual \%) --
#' https://data.worldbank.org/indicator/NY.GDP.DEFL.KD.ZG}
#' }
"data.costcecx"
#' Country names and codes
#'
#' A dataset containing the country names and codes (ISO/WHO/WB/UN).
#'
#' @format A data table with 251 observations of 13 variables.
#' \describe{
#' \item{name1, name2, name3, name4}{Country names}
#' \item{iso2, iso3}{ISO2 and ISO3 country codes}
#' \item{isonum}{ISO number}
#' \item{WHOcode}{WHO country code}
#' \item{who_region}{WHO region}
#' \item{who_mort}{WHO mortality stratum - A/B/C/D/E}
#' \item{WBincome}{WB income classification of countries}
#' \item{UNgroup}{UN group classification of countries}
#' \item{GDPpc2011id}{GDP per capita (2011)}
#' }
"data.countryname"
#' Global data table
#'
#' A dataset containing a global range of variables.
#'
#' @format A data table with 194 observations of 35 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso2}{ISO2 country code}
#' \item{WHO Region}{WHO regions}
#' \item{WHO Mortality Stratum}{WHO mortality stratum}
#' \item{World Bank Income Group (2011)}{World Bank income group levels}
#' \item{GAVI Eligibility}{GAVI eligibility status}
#' \item{PAHO Revolving Fund}{PAHO revolving fund status}
#' \item{Cohort size (2010) [1]}{Cohort size}
#' \item{Coverage (3 doses at year 10) [2]}{Vaccination coverage at age 10}
#' \item{Vaccine efficacy vs vaccine type infection [2]}{Vaccine efficacy}
#' \item{Duration of protection [2]}{Duration of vaccine protection}
#' \item{Age group [3]}{Age group}
#' \item{Vaccine price USD [4]}{Vaccine price for 2 doses US$}
#' \item{Vaccine delivery/ operational/ admin costs (USD) [5]}{Vaccine delivery, operational and administration costs US$}
#' \item{Cancer treatment costs - primary level hospital i$ (per episode, over lifetime) [6]}{Cancer treatment costs - primary level hospital i$ (per episode, over lifetime)}
#' \item{Cancer treatment costs - primary level hospital US$ (per episode, over lifetime) [6]}{Cancer treatment costs - primary level hospital US$ (per episode, over lifetime)}
#' \item{Cancer treatment costs - secondary level hospital i$ (per episode, over lifetime) [6]}{Cancer treatment costs - secondary level hospital i$ (per episode, over lifetime)}
#' \item{Cancer treatment costs - secondary level hospital US$ (per episode, over lifetime) [6]}{Cancer treatment costs - secondary level hospital US$ (per episode, over lifetime)}
#' \item{Cancer treatment costs - teaching hospital i$ (per episode, over lifetime) [6]}{Cancer treatment costs - teaching hospital i$ (per episode, over lifetime)}
#' \item{Cancer treatment costs - teaching hospital US$ (per episode, over lifetime) [6]}{Cancer treatment costs - teaching hospital US$ (per episode, over lifetime)}
#' \item{Discount rate [2]}{Disount rate}
#' \item{Perspective [2]}{Perspective}
#' \item{Costs [2]}{}
#' \item{Time horizon [2]}{Time horizon}
#' \item{"Percent" CeCx due to 16/18}{Percentage of cervical cancer due to HPV strains 16 and 18}
#' \item{Vaccine programme}{Vaccine programme}
#' \item{Vaccine programme Oct2013}{Vaccine programme Oct2013}
#' \item{Econ evaluation}{Economic evaluation}
#' \item{GDP per capita (2011 US$) [7]}{GDP per capita (2011 US$)}
#' \item{GDP per capita (2011 i$) [7]}{GDP per capita (2011 i$)}
#' \item{GNI per capita (2011 i$) [7]}{GNI per capita (2011 i$)}
#' \item{GNI per capita (2011 US$) [7]}{GNI per capita (2011 US$)}
#' \item{V33}{International$}
#' \item{V34}{US$}
#' \item{iso3}{ISO3 country code}
#' }
"data.global"
#' Incidence of cervical cancer, by age and country
#'
#' A dataset containing the incidence of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2018 database.
#' Crude rates, cervix uteri, females, by age.
#'
#' @format A data table with 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100 -- Crude rates, cervix uteri, females, by age; annual rate per individual}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.incidence"
#' Incidence of cervical cancer, by age and country
#'
#' A dataset containing the incidence of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2020 database.
#' Crude rates, cervix uteri, females, by age.
#'
#' @format A data table with 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100 -- Crude rates, cervix uteri, females, by age; annual rate per individual}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table?v=2020}
"data.incidence2020"
#' Incidence of cervical cancer with uncertainty intervals, all ages and by country
#'
#' A dataset containing the incidence of cervical cancer with uncertainty
#' intervals in 185 countries, as reported by IARC's Globocan 2018 database.
#' Estimated number of new cases in 2018, cervix uteri, females, all ages.
#'
#' @format A data table with 185 observations of 5 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Mid}{Estimated number of new cases in 2018, cervix uteri, females, all ages (mean)}
#' \item{Low}{Estimated number of new cases in 2018, cervix uteri, females, all ages (lower bound of 95\% uncertainty interval)}
#' \item{High}{Estimated number of new cases in 2018, cervix uteri, females, all ages (upper bound of 95\% uncertainty interval)}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.incidence_ui"
#' WHO life table
#'
#' A dataset containing the WHO life table.
#'
#' @format A data table with 196 observations of 107 variables.
#' \describe{
#' \item{Country ¦ Age [12]}{Country name}
#' \item{0..100}{Age 0-100}
#' \item{V103..V106}{na}
#' \item{iso3}{ISO3 country code}
#' }
#' @source \url{https://www.who.int/gho/mortality_burden_disease/life_tables/life_tables/en/}
"data.mortall"
#' UNWPP life table
#'
#' A dataset containing the UNWPP life table (World Population Prospects 2022).
#'
#' @format A data table with 647790 observations of 8 variables.
#' \describe{
#' \item{country_code_numeric}{Country code numeric}
#' \item{country_code}{ISO3 country code}
#' \item{country}{Country name}
#' \item{age_from}{age from (start-age)}
#' \item{age_to}{age to (end-age)}
#' \item{year}{Year}
#' \item{gender}{Gender}
#' \item{value}{nqx - probability of dying between ages x and x+n}
#' }
#' @source \url{https://population.un.org/wpp/}
"data.mortall.unwpp.nqx"
#' Mortality from cervical cancer, by age and country
#'
#' A dataset containing the mortality (crude rates)
#' from cervical cancer in 185 countries,
#' as reported by IARC's Globocan 2018 database.
#'
#' @format A data table with 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100 - Crude rates, cervix uteri, females, by age; annual rate per individual}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.mortcecx"
#' Mortality from cervical cancer, by age and country
#'
#' A dataset containing the mortality (crude rates)
#' from cervical cancer in 185 countries,
#' as reported by IARC's Globocan 2020 database.
#'
#' @format A data table with 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100 - Crude rates, cervix uteri, females, by age; annual rate per individual}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table?v=2020}
"data.mortcecx2020"
#' Mortality from cervical cancer with uncertainty intervals, all ages and by country
#'
#' A dataset containing the number of deaths from cervical cancer with uncertainty
#' intervals in 185 countries, as reported by IARC's Globocan 2018 database.
#' Estimated number of deaths in 2018, cervix uteri, females, all ages.
#'
#' @format A data table with 185 observations of 5 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Mid}{Estimated number of deaths in 2018, cervix uteri, females, all ages (mean)}
#' \item{Low}{Estimated number of deaths in 2018, cervix uteri, females, all ages (lower bound of 95\% uncertainty interval)}
#' \item{High}{Estimated number of deaths in 2018, cervix uteri, females, all ages (upper bound of 95\% uncertainty interval)}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.mortcecx_ui"
#' UNWPP population estimates
#'
#' A dataset containing the UNWPP population estimates -- World Population Prospects 2022.
#'
#' @format A data table with 3392220 observations of 8 variables.
#' \describe{
#' \item{country_code_numeric}{Country code numeric}
#' \item{country_code}{ISO3 country code}
#' \item{country}{Country name}
#' \item{age_from}{age from (start-age)}
#' \item{age_to}{age to (end-age)}
#' \item{year}{Year}
#' \item{gender}{Gender}
#' \item{value}{Population size}
#' }
#' @source \url{https://population.un.org/wpp/Download/Standard/Population/}
#' @source {VIMC}
"data.pop"
#' Population projections of 5-year old girls
#'
#' A dataset containing population projections of 5-year old girls.
#' (not used -- to be removed)
#'
#' @format A data table with 98 observations of 91 variables.
#' \describe{
#' \item{iso3}{ISO3 country code}
#' \item{2011..2100}{Year -- 2011..2100}
#' }
"data.popproj"
#' Data quality of incidence and mortality
#'
#' A dataset indicating data quality of cervical cancer incidence and mortality.
#'
#' @format A data table with 186 observations of 4 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{Incidence}{Quality of cervical cancer incidence data}
#' \item{Mortality}{Quality of cervical cancer mortality data}
#' \item{iso3}{ISO3 country code}
#' }
"data.quality"
#' Sexual debut data
#'
#' A dataset containing sexual debut data and (2) parameters for the sexual debut curve (logistic model).
#'
#' @format A data table with 94 observations of 14 variables.
#' \describe{
#' \item{V1}{Row number}
#' \item{iso2}{ISO2 country code}
#' \item{country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{who}{WHO region}
#' \item{X15}{Proportion of people who have sexually debuted at age 15}
#' \item{X18}{Proportion of people who have sexually debuted at age 18}
#' \item{X20}{Proportion of people who have sexually debuted at age 20}
#' \item{X22}{Proportion of people who have sexually debuted at age 22}
#' \item{X25}{Proportion of people who have sexually debuted at age 25}
#' \item{Never}{Proportion of people who had not sexually debuted}
#' \item{cluster.id}{Clustering countries with similar characteristics}
#' \item{a}{Parameter for sexual debut curve (logistic model)}
#' \item{b}{Parameter for sexual debut curve (logistic model)}
#' }
"data.sexual_debut"
#' Model validation
#'
#' A dataset containing data for validation.
#'
#' @format A data table with 26 observations of 49 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso2}{ISO2 country code}
#' \item{WHO Region}{WHO region}
#' \item{World Bank Income Group (2011)}{World Bank income group classification (2011)}
#' \item{Author}{Author}
#' \item{Year}{Year of publication}
#' \item{Title}{Title of publication}
#' \item{Currency}{Currency}
#' \item{Currency year}{Currency year}
#' \item{Conversion to I$2011}{International dollar (I$2011)}
#' \item{ICER vs no prevention}{Incremental cost-effectiveness ratio of vaccination versus no prevention (CHECK)}
#' \item{ICER vs screen}{Incremental cost-effectiveness ratio of vaccination versus no prevention (CHECK)}
#' \item{Denominator}{Denominator for health impact}
#' \item{Vaccine total costs}{Vaccine total costs}
#' \item{Vaccine coverage}{Vaccine coverage}
#' \item{Vaccine efficacy vs vaccine type infection}{Vaccine efficacy versus vaccine type infection}
#' \item{Duration of protection}{Duration of protective immunity from vaccination}
#' \item{Cohort size}{Cohort size}
#' \item{Age at vaccination}{Age at vaccination, years}
#' \item{Cancer treatment cost per episode}{Cancer treatment cost per episode, dollars}
#' \item{Discount rate: costs}{Discount rate for costs}
#' \item{Discount rate: benefits}{Discount rate for benefits}
#' \item{Perspective}{Perspective of economic evaluation}
#' \item{Comparator is no screening}{Comparator refers to no scereening, logical (Y/N)}
#' \item{Time horizon}{Time horizon of analysis}
#' \item{GDP per capita}{GDP per capita}
#' \item{Cervical cancer due to 16/18}{Proportion of cervical cancer due to HPV types 16 and 18}
#' \item{CeCx cost low original}{Cervical cancer cost / low / original}
#' \item{CeCx cost high original}{Cervical cancer cost / high / original}
#' \item{CeCx cost low}{Cervical cancer cost / low}
#' \item{CeCx cost high}{Cervical cancer cost / high}
#' \item{CeCx data available}{Cervical cancer data available, logical (Y/N)}
#' \item{0-4}{0-4 years}
#' \item{5-9}{5-9 years}
#' \item{9-14}{9-14 years}
#' \item{15-19}{15-19 years}
#' \item{20-24}{20-24 years}
#' \item{25-29}{25-29 years}
#' \item{30-34}{30-34 years}
#' \item{35-39}{35-39 years}
#' \item{40-44}{40-44 years}
#' \item{45-49}{45-49 years}
#' \item{50-54}{50-54 years}
#' \item{55-59}{55-59 years}
#' \item{60-64}{60-64 years}
#' \item{65-69}{65-69 years}
#' \item{70-74}{70-74 years}
#' \item{75-79}{75-79 years}
#' \item{80+}{80+ years}
#' }
"data.valid"
#' Disability weights and duration of cervical cancer stages
#'
#' A dataset containing disability weights and duration of different phases of cervical cancer.
#'
#' @format A data table with 13 observations of 8 variables.
#' \describe{
#' \item{Source}{Source of disability weights - IHME / WHO}
#' \item{Sequela}{Sequelae / stage / phase of cervical cancer}
#' \item{Duration}{Duration of cervical cancer phase}
#' \item{WHO_MortalityStratum}{WHO moratlity stratum -- applicable only for long term sequelae from WHO source}
#' \item{Mid}{Disability weight (mid)}
#' \item{Low}{Disability weight (low)}
#' \item{High}{Disability weight (high)}
#' \item{Description}{Description of cervical cancer phase}
#' }
"data.disability_weights"
#' Relative contribution of HPV 16/18/31/33/45/52/58 in ICC HPV-positive cases
#'
#' A dataset containing relative contribution of HPV 16/18/31/33/45/52/58 in
#' cases of ICC HPV-positive, by region and country
#'
#' @format A data table with 249 observations of 39 variables.
#' \describe{
#' \item{Global}{World}
#' \item{Region}{UN region}
#' \item{Subregion}{UN subregion}
#' \item{Intermediate_region}{UN intermediate region}
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{hpv_4v}{Relative contribution (\%) of HPV 16/18 in ICC HPV-positive cases (mean)}
#' \item{hpv_4v_low}{Relative contribution (\%) of HPV 16/18 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_4v_high}{Relative contribution (\%) of HPV 16/18 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_9v}{Relative contribution (\%) of HPV 16/18/31/33/45/52/58 in ICC HPV-positive cases (mean)}
#' \item{hpv_9v_low}{Relative contribution (\%) of HPV 16/18/31/33/45/52/58 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_9v_high}{Relative contribution (\%) of HPV 16/18/31/33/45/52/58 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_16}{Relative contribution (\%) of HPV 16 in ICC HPV-positive cases (mean)}
#' \item{hpv_16_low}{Relative contribution (\%) of HPV 16 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_16_high}{Relative contribution (\%) of HPV 16 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_18}{Relative contribution (\%) of HPV 18 in ICC HPV-positive cases (mean)}
#' \item{hpv_18_low}{Relative contribution (\%) of HPV 18 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_18_high}{Relative contribution (\%) of HPV 18 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_31}{Relative contribution (\%) of HPV 31 in ICC HPV-positive cases (mean)}
#' \item{hpv_31_low}{Relative contribution (\%) of HPV 31 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_31_high}{Relative contribution (\%) of HPV 31 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_33}{Relative contribution (\%) of HPV 33 in ICC HPV-positive cases (mean)}
#' \item{hpv_33_low}{Relative contribution (\%) of HPV 33 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_33_high}{Relative contribution (\%) of HPV 33 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_45}{Relative contribution (\%) of HPV 45 in ICC HPV-positive cases (mean)}
#' \item{hpv_45_low}{Relative contribution (\%) of HPV 45 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_45_high}{Relative contribution (\%) of HPV 45 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_52}{Relative contribution (\%) of HPV 52 in ICC HPV-positive cases (mean)}
#' \item{hpv_52_low}{Relative contribution (\%) of HPV 52 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_52_high}{Relative contribution (\%) of HPV 52 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_58}{Relative contribution (\%) of HPV 58 in ICC HPV-positive cases (mean)}
#' \item{hpv_58_low}{Relative contribution (\%) of HPV 58 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_58_high}{Relative contribution (\%) of HPV 58 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_6}{Relative contribution (\%) of HPV 6 in ICC HPV-positive cases (mean)}
#' \item{hpv_6_low}{Relative contribution (\%) of HPV 6 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_6_high}{Relative contribution (\%) of HPV 6 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_11}{Relative contribution (\%) of HPV 11 in ICC HPV-positive cases (mean)}
#' \item{hpv_11_low}{Relative contribution (\%) of HPV 11 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_11_high}{Relative contribution (\%) of HPV 11 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' }
#' @source {Serrano B, Alemany L, Tous S, Bruni L, Clifford GM, Weiss T, et al.
#' Potential impact of a nine-valent vaccine in human papillomavirus related cervical disease.
#' Infect Agents Cancer. 2012;7: 38. \url{https://doi.org/10.1186/1750-9378-7-38}}
"data.hpv_distribution"
#' Cross-protection effect of bivalent and quadrivalent vaccines
#'
#' A dataset containing cross-protection effect of bivalent and quadrivalent vaccines
#'
#' @format A data table with 5 observations of 7 variables.
#' \describe{
#' \item{hpv_type}{HPV strain type}
#' \item{bivalent}{Cross-protection of bivalent vaccine against the corresponding HPV strain type (mean)}
#' \item{bivalent_low}{Cross-protection of bivalent vaccine against the corresponding HPV strain type (lower bound of 95\% uncertainty interval)}
#' \item{bivalent_high}{Cross-protection of bivalent vaccine against the corresponding HPV strain type (upper bound of 95\% uncertainty interval)}
#' \item{quadrivalent}{Cross-protection of quadrivalent vaccine against the corresponding HPV strain type (mean)}
#' \item{quadrivalent_low}{Cross-protection of quadrivalent vaccine against the corresponding HPV strain type (lower bound of 95\% uncertainty interval)}
#' \item{quadrivalent_high}{Cross-protection of quadrivalent vaccine against the corresponding HPV strain type (upper bound of 95\% uncertainty interval)}
#' }
#' @source {Malagón T, Drolet M, Boily MC, Franco EL, Jit M, Brisson J, Brisson M.
#' Cross-protective efficacy of two human papillomavirus vaccines: a systematic review and meta-analysis.
#' Lancet Infect Dis. 2012 Oct;12(10):781-9. \url{https://doi.org/10.1016/S1473-3099(12)70187-1}}
"data.cross_protection"
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# Data.R - This file includes documentation of datasets.
#' 1-year prevalence of cervical cancer
#'
#' A dataset containing the 1-year prevalence (proportion) of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2018 database.
#'
#' As per IARC definition -- The (1-year) prevalence of a given cancer
#' is the number of individuals within a defined population who have been diagnosed with that
#' cancer (within 1 year) and who are still alive at a given point in time (i.e. the survivors).
#'
#' @format A data table containing 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.cecx_1y_prevalence"
#' 1-year prevalence of cervical cancer
#'
#' A dataset containing the 1-year prevalence (proportion) of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2020 database.
#'
#' As per IARC definition -- The (1-year) prevalence of a given cancer
#' is the number of individuals within a defined population who have been diagnosed with that
#' cancer (within 1 year) and who are still alive at a given point in time (i.e. the survivors).
#'
#' @format A data table containing 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table?v=2020}
"data.cecx_1y_prevalence2020"
#' 3-year prevalence of cervical cancer
#'
#' A dataset containing the 3-year prevalence (proportion) of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2018 database.
#'
#' As per IARC definition -- The (3-year) prevalence of a given cancer
#' is the number of individuals within a defined population who have been diagnosed with that
#' cancer (within 3 years) and who are still alive at a given point in time (i.e. the survivors).
#'
#' @format A data table containing 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.cecx_3y_prevalence"
#' 3-year prevalence of cervical cancer
#'
#' A dataset containing the 3-year prevalence (proportion) of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2020 database.
#'
#' As per IARC definition -- The (3-year) prevalence of a given cancer
#' is the number of individuals within a defined population who have been diagnosed with that
#' cancer (within 3 years) and who are still alive at a given point in time (i.e. the survivors).
#'
#' @format A data table containing 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table?v=2020}
"data.cecx_3y_prevalence2020"
#' 5-year prevalence of cervical cancer
#'
#' A dataset containing the 5-year prevalence (proportion) of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2018 database.
#'
#' As per IARC definition -- The (5-year) prevalence of a given cancer
#' is the number of individuals within a defined population who have been diagnosed with that
#' cancer (within 5 years) and who are still alive at a given point in time (i.e. the survivors).
#'
#' @format A data table with 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.cecx_5y_prevalence"
#' 5-year prevalence of cervical cancer
#'
#' A dataset containing the 5-year prevalence (proportion) of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2020 database.
#'
#' As per IARC definition -- The (5-year) prevalence of a given cancer
#' is the number of individuals within a defined population who have been diagnosed with that
#' cancer (within 5 years) and who are still alive at a given point in time (i.e. the survivors).
#'
#' @format A data table with 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table?v=2020}
"data.cecx_5y_prevalence2020"
#' Cost of cervical cancer treatment
#'
#' A dataset containing the cost of cervical cancer treatment.
#'
#' @format A data table with 194 observations of 7 variables.
#' \describe{
#' \item{country}{Country name}
#' \item{cancer_cost}{cost per cancer episode, in 2017 US$}
#' \item{cancer_cost_adj}{cost per cancer episode -- adjusted, in 2017 US$ --
#' “adjusted” cancer costs are based on a GDP/capita based adjustment
#' within the region}
#' \item{iso3}{ISO3 country code}
#' \item{cancer_cost_2011}{cost per cancer episode, in 2011 US$}
#' \item{cancer_cost_adj_2011}{cost per cancer episode --
#' adjusted, in 2011 US$ -- “adjusted” cancer costs are based on a
#' GDP/capita based adjustment within the region}
#' \item{inflation_factor}{Inflation factor from 2011 to 2017 estimated from
#' Inflation, GDP deflator (annual \%) --
#' https://data.worldbank.org/indicator/NY.GDP.DEFL.KD.ZG}
#' }
"data.costcecx"
#' Country names and codes
#'
#' A dataset containing the country names and codes (ISO/WHO/WB/UN).
#'
#' @format A data table with 251 observations of 13 variables.
#' \describe{
#' \item{name1, name2, name3, name4}{Country names}
#' \item{iso2, iso3}{ISO2 and ISO3 country codes}
#' \item{isonum}{ISO number}
#' \item{WHOcode}{WHO country code}
#' \item{who_region}{WHO region}
#' \item{who_mort}{WHO mortality stratum - A/B/C/D/E}
#' \item{WBincome}{WB income classification of countries}
#' \item{UNgroup}{UN group classification of countries}
#' \item{GDPpc2011id}{GDP per capita (2011)}
#' }
"data.countryname"
#' Global data table
#'
#' A dataset containing a global range of variables.
#'
#' @format A data table with 194 observations of 35 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso2}{ISO2 country code}
#' \item{WHO Region}{WHO regions}
#' \item{WHO Mortality Stratum}{WHO mortality stratum}
#' \item{World Bank Income Group (2011)}{World Bank income group levels}
#' \item{GAVI Eligibility}{GAVI eligibility status}
#' \item{PAHO Revolving Fund}{PAHO revolving fund status}
#' \item{Cohort size (2010) [1]}{Cohort size}
#' \item{Coverage (3 doses at year 10) [2]}{Vaccination coverage at age 10}
#' \item{Vaccine efficacy vs vaccine type infection [2]}{Vaccine efficacy}
#' \item{Duration of protection [2]}{Duration of vaccine protection}
#' \item{Age group [3]}{Age group}
#' \item{Vaccine price USD [4]}{Vaccine price for 2 doses US$}
#' \item{Vaccine delivery/ operational/ admin costs (USD) [5]}{Vaccine delivery, operational and administration costs US$}
#' \item{Cancer treatment costs - primary level hospital i$ (per episode, over lifetime) [6]}{Cancer treatment costs - primary level hospital i$ (per episode, over lifetime)}
#' \item{Cancer treatment costs - primary level hospital US$ (per episode, over lifetime) [6]}{Cancer treatment costs - primary level hospital US$ (per episode, over lifetime)}
#' \item{Cancer treatment costs - secondary level hospital i$ (per episode, over lifetime) [6]}{Cancer treatment costs - secondary level hospital i$ (per episode, over lifetime)}
#' \item{Cancer treatment costs - secondary level hospital US$ (per episode, over lifetime) [6]}{Cancer treatment costs - secondary level hospital US$ (per episode, over lifetime)}
#' \item{Cancer treatment costs - teaching hospital i$ (per episode, over lifetime) [6]}{Cancer treatment costs - teaching hospital i$ (per episode, over lifetime)}
#' \item{Cancer treatment costs - teaching hospital US$ (per episode, over lifetime) [6]}{Cancer treatment costs - teaching hospital US$ (per episode, over lifetime)}
#' \item{Discount rate [2]}{Disount rate}
#' \item{Perspective [2]}{Perspective}
#' \item{Costs [2]}{}
#' \item{Time horizon [2]}{Time horizon}
#' \item{"Percent" CeCx due to 16/18}{Percentage of cervical cancer due to HPV strains 16 and 18}
#' \item{Vaccine programme}{Vaccine programme}
#' \item{Vaccine programme Oct2013}{Vaccine programme Oct2013}
#' \item{Econ evaluation}{Economic evaluation}
#' \item{GDP per capita (2011 US$) [7]}{GDP per capita (2011 US$)}
#' \item{GDP per capita (2011 i$) [7]}{GDP per capita (2011 i$)}
#' \item{GNI per capita (2011 i$) [7]}{GNI per capita (2011 i$)}
#' \item{GNI per capita (2011 US$) [7]}{GNI per capita (2011 US$)}
#' \item{V33}{International$}
#' \item{V34}{US$}
#' \item{iso3}{ISO3 country code}
#' }
"data.global"
#' Incidence of cervical cancer, by age and country
#'
#' A dataset containing the incidence of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2018 database.
#' Crude rates, cervix uteri, females, by age.
#'
#' @format A data table with 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100 -- Crude rates, cervix uteri, females, by age; annual rate per individual}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.incidence"
#' Incidence of cervical cancer, by age and country
#'
#' A dataset containing the incidence of cervical cancer in 185 countries, as reported by
#' IARC's Globocan 2020 database.
#' Crude rates, cervix uteri, females, by age.
#'
#' @format A data table with 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100 -- Crude rates, cervix uteri, females, by age; annual rate per individual}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table?v=2020}
"data.incidence2020"
#' Incidence of cervical cancer with uncertainty intervals, all ages and by country
#'
#' A dataset containing the incidence of cervical cancer with uncertainty
#' intervals in 185 countries, as reported by IARC's Globocan 2018 database.
#' Estimated number of new cases in 2018, cervix uteri, females, all ages.
#'
#' @format A data table with 185 observations of 5 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Mid}{Estimated number of new cases in 2018, cervix uteri, females, all ages (mean)}
#' \item{Low}{Estimated number of new cases in 2018, cervix uteri, females, all ages (lower bound of 95\% uncertainty interval)}
#' \item{High}{Estimated number of new cases in 2018, cervix uteri, females, all ages (upper bound of 95\% uncertainty interval)}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.incidence_ui"
#' WHO life table
#'
#' A dataset containing the WHO life table.
#'
#' @format A data table with 196 observations of 107 variables.
#' \describe{
#' \item{Country ¦ Age [12]}{Country name}
#' \item{0..100}{Age 0-100}
#' \item{V103..V106}{na}
#' \item{iso3}{ISO3 country code}
#' }
#' @source \url{https://www.who.int/gho/mortality_burden_disease/life_tables/life_tables/en/}
"data.mortall"
#' UNWPP life table
#'
#' A dataset containing the UNWPP life table (World Population Prospects 2022).
#'
#' @format A data table with 647790 observations of 8 variables.
#' \describe{
#' \item{country_code_numeric}{Country code numeric}
#' \item{country_code}{ISO3 country code}
#' \item{country}{Country name}
#' \item{age_from}{age from (start-age)}
#' \item{age_to}{age to (end-age)}
#' \item{year}{Year}
#' \item{gender}{Gender}
#' \item{value}{nqx - probability of dying between ages x and x+n}
#' }
#' @source \url{https://population.un.org/wpp/}
"data.mortall.unwpp.nqx"
#' Mortality from cervical cancer, by age and country
#'
#' A dataset containing the mortality (crude rates)
#' from cervical cancer in 185 countries,
#' as reported by IARC's Globocan 2018 database.
#'
#' @format A data table with 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100 - Crude rates, cervix uteri, females, by age; annual rate per individual}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.mortcecx"
#' Mortality from cervical cancer, by age and country
#'
#' A dataset containing the mortality (crude rates)
#' from cervical cancer in 185 countries,
#' as reported by IARC's Globocan 2020 database.
#'
#' @format A data table with 185 observations of 103 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' \item{0..100}{Age 0-100 - Crude rates, cervix uteri, females, by age; annual rate per individual}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table?v=2020}
"data.mortcecx2020"
#' Mortality from cervical cancer with uncertainty intervals, all ages and by country
#'
#' A dataset containing the number of deaths from cervical cancer with uncertainty
#' intervals in 185 countries, as reported by IARC's Globocan 2018 database.
#' Estimated number of deaths in 2018, cervix uteri, females, all ages.
#'
#' @format A data table with 185 observations of 5 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{Mid}{Estimated number of deaths in 2018, cervix uteri, females, all ages (mean)}
#' \item{Low}{Estimated number of deaths in 2018, cervix uteri, females, all ages (lower bound of 95\% uncertainty interval)}
#' \item{High}{Estimated number of deaths in 2018, cervix uteri, females, all ages (upper bound of 95\% uncertainty interval)}
#' \item{Source}{Data source}
#' \item{Year}{Data source (year)}
#' }
#' @source \url{https://gco.iarc.fr/today/online-analysis-table}
"data.mortcecx_ui"
#' UNWPP population estimates
#'
#' A dataset containing the UNWPP population estimates -- World Population Prospects 2022.
#'
#' @format A data table with 3392220 observations of 8 variables.
#' \describe{
#' \item{country_code_numeric}{Country code numeric}
#' \item{country_code}{ISO3 country code}
#' \item{country}{Country name}
#' \item{age_from}{age from (start-age)}
#' \item{age_to}{age to (end-age)}
#' \item{year}{Year}
#' \item{gender}{Gender}
#' \item{value}{Population size}
#' }
#' @source \url{https://population.un.org/wpp/Download/Standard/Population/}
#' @source {VIMC}
"data.pop"
#' Population projections of 5-year old girls
#'
#' A dataset containing population projections of 5-year old girls.
#' (not used -- to be removed)
#'
#' @format A data table with 98 observations of 91 variables.
#' \describe{
#' \item{iso3}{ISO3 country code}
#' \item{2011..2100}{Year -- 2011..2100}
#' }
"data.popproj"
#' Data quality of incidence and mortality
#'
#' A dataset indicating data quality of cervical cancer incidence and mortality.
#'
#' @format A data table with 186 observations of 4 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{Incidence}{Quality of cervical cancer incidence data}
#' \item{Mortality}{Quality of cervical cancer mortality data}
#' \item{iso3}{ISO3 country code}
#' }
"data.quality"
#' Sexual debut data
#'
#' A dataset containing sexual debut data and (2) parameters for the sexual debut curve (logistic model).
#'
#' @format A data table with 94 observations of 14 variables.
#' \describe{
#' \item{V1}{Row number}
#' \item{iso2}{ISO2 country code}
#' \item{country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{who}{WHO region}
#' \item{X15}{Proportion of people who have sexually debuted at age 15}
#' \item{X18}{Proportion of people who have sexually debuted at age 18}
#' \item{X20}{Proportion of people who have sexually debuted at age 20}
#' \item{X22}{Proportion of people who have sexually debuted at age 22}
#' \item{X25}{Proportion of people who have sexually debuted at age 25}
#' \item{Never}{Proportion of people who had not sexually debuted}
#' \item{cluster.id}{Clustering countries with similar characteristics}
#' \item{a}{Parameter for sexual debut curve (logistic model)}
#' \item{b}{Parameter for sexual debut curve (logistic model)}
#' }
"data.sexual_debut"
#' Model validation
#'
#' A dataset containing data for validation.
#'
#' @format A data table with 26 observations of 49 variables.
#' \describe{
#' \item{Country}{Country name}
#' \item{iso2}{ISO2 country code}
#' \item{WHO Region}{WHO region}
#' \item{World Bank Income Group (2011)}{World Bank income group classification (2011)}
#' \item{Author}{Author}
#' \item{Year}{Year of publication}
#' \item{Title}{Title of publication}
#' \item{Currency}{Currency}
#' \item{Currency year}{Currency year}
#' \item{Conversion to I$2011}{International dollar (I$2011)}
#' \item{ICER vs no prevention}{Incremental cost-effectiveness ratio of vaccination versus no prevention (CHECK)}
#' \item{ICER vs screen}{Incremental cost-effectiveness ratio of vaccination versus no prevention (CHECK)}
#' \item{Denominator}{Denominator for health impact}
#' \item{Vaccine total costs}{Vaccine total costs}
#' \item{Vaccine coverage}{Vaccine coverage}
#' \item{Vaccine efficacy vs vaccine type infection}{Vaccine efficacy versus vaccine type infection}
#' \item{Duration of protection}{Duration of protective immunity from vaccination}
#' \item{Cohort size}{Cohort size}
#' \item{Age at vaccination}{Age at vaccination, years}
#' \item{Cancer treatment cost per episode}{Cancer treatment cost per episode, dollars}
#' \item{Discount rate: costs}{Discount rate for costs}
#' \item{Discount rate: benefits}{Discount rate for benefits}
#' \item{Perspective}{Perspective of economic evaluation}
#' \item{Comparator is no screening}{Comparator refers to no scereening, logical (Y/N)}
#' \item{Time horizon}{Time horizon of analysis}
#' \item{GDP per capita}{GDP per capita}
#' \item{Cervical cancer due to 16/18}{Proportion of cervical cancer due to HPV types 16 and 18}
#' \item{CeCx cost low original}{Cervical cancer cost / low / original}
#' \item{CeCx cost high original}{Cervical cancer cost / high / original}
#' \item{CeCx cost low}{Cervical cancer cost / low}
#' \item{CeCx cost high}{Cervical cancer cost / high}
#' \item{CeCx data available}{Cervical cancer data available, logical (Y/N)}
#' \item{0-4}{0-4 years}
#' \item{5-9}{5-9 years}
#' \item{9-14}{9-14 years}
#' \item{15-19}{15-19 years}
#' \item{20-24}{20-24 years}
#' \item{25-29}{25-29 years}
#' \item{30-34}{30-34 years}
#' \item{35-39}{35-39 years}
#' \item{40-44}{40-44 years}
#' \item{45-49}{45-49 years}
#' \item{50-54}{50-54 years}
#' \item{55-59}{55-59 years}
#' \item{60-64}{60-64 years}
#' \item{65-69}{65-69 years}
#' \item{70-74}{70-74 years}
#' \item{75-79}{75-79 years}
#' \item{80+}{80+ years}
#' }
"data.valid"
#' Disability weights and duration of cervical cancer stages
#'
#' A dataset containing disability weights and duration of different phases of cervical cancer.
#'
#' @format A data table with 13 observations of 8 variables.
#' \describe{
#' \item{Source}{Source of disability weights - IHME / WHO}
#' \item{Sequela}{Sequelae / stage / phase of cervical cancer}
#' \item{Duration}{Duration of cervical cancer phase}
#' \item{WHO_MortalityStratum}{WHO moratlity stratum -- applicable only for long term sequelae from WHO source}
#' \item{Mid}{Disability weight (mid)}
#' \item{Low}{Disability weight (low)}
#' \item{High}{Disability weight (high)}
#' \item{Description}{Description of cervical cancer phase}
#' }
"data.disability_weights"
#' Relative contribution of HPV 16/18/31/33/45/52/58 in ICC HPV-positive cases
#'
#' A dataset containing relative contribution of HPV 16/18/31/33/45/52/58 in
#' cases of ICC HPV-positive, by region and country
#'
#' @format A data table with 249 observations of 39 variables.
#' \describe{
#' \item{Global}{World}
#' \item{Region}{UN region}
#' \item{Subregion}{UN subregion}
#' \item{Intermediate_region}{UN intermediate region}
#' \item{Country}{Country name}
#' \item{iso3}{ISO3 country code}
#' \item{hpv_4v}{Relative contribution (\%) of HPV 16/18 in ICC HPV-positive cases (mean)}
#' \item{hpv_4v_low}{Relative contribution (\%) of HPV 16/18 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_4v_high}{Relative contribution (\%) of HPV 16/18 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_9v}{Relative contribution (\%) of HPV 16/18/31/33/45/52/58 in ICC HPV-positive cases (mean)}
#' \item{hpv_9v_low}{Relative contribution (\%) of HPV 16/18/31/33/45/52/58 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_9v_high}{Relative contribution (\%) of HPV 16/18/31/33/45/52/58 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_16}{Relative contribution (\%) of HPV 16 in ICC HPV-positive cases (mean)}
#' \item{hpv_16_low}{Relative contribution (\%) of HPV 16 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_16_high}{Relative contribution (\%) of HPV 16 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_18}{Relative contribution (\%) of HPV 18 in ICC HPV-positive cases (mean)}
#' \item{hpv_18_low}{Relative contribution (\%) of HPV 18 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_18_high}{Relative contribution (\%) of HPV 18 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_31}{Relative contribution (\%) of HPV 31 in ICC HPV-positive cases (mean)}
#' \item{hpv_31_low}{Relative contribution (\%) of HPV 31 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_31_high}{Relative contribution (\%) of HPV 31 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_33}{Relative contribution (\%) of HPV 33 in ICC HPV-positive cases (mean)}
#' \item{hpv_33_low}{Relative contribution (\%) of HPV 33 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_33_high}{Relative contribution (\%) of HPV 33 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_45}{Relative contribution (\%) of HPV 45 in ICC HPV-positive cases (mean)}
#' \item{hpv_45_low}{Relative contribution (\%) of HPV 45 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_45_high}{Relative contribution (\%) of HPV 45 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_52}{Relative contribution (\%) of HPV 52 in ICC HPV-positive cases (mean)}
#' \item{hpv_52_low}{Relative contribution (\%) of HPV 52 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_52_high}{Relative contribution (\%) of HPV 52 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_58}{Relative contribution (\%) of HPV 58 in ICC HPV-positive cases (mean)}
#' \item{hpv_58_low}{Relative contribution (\%) of HPV 58 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_58_high}{Relative contribution (\%) of HPV 58 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_6}{Relative contribution (\%) of HPV 6 in ICC HPV-positive cases (mean)}
#' \item{hpv_6_low}{Relative contribution (\%) of HPV 6 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_6_high}{Relative contribution (\%) of HPV 6 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' \item{hpv_11}{Relative contribution (\%) of HPV 11 in ICC HPV-positive cases (mean)}
#' \item{hpv_11_low}{Relative contribution (\%) of HPV 11 in ICC HPV-positive cases (lower bound of 95\% uncertainty interval)}
#' \item{hpv_11_high}{Relative contribution (\%) of HPV 11 in ICC HPV-positive cases (upper bound of 95\% uncertainty interval)}
#' }
#' @source {Serrano B, Alemany L, Tous S, Bruni L, Clifford GM, Weiss T, et al.
#' Potential impact of a nine-valent vaccine in human papillomavirus related cervical disease.
#' Infect Agents Cancer. 2012;7: 38. \url{https://doi.org/10.1186/1750-9378-7-38}}
"data.hpv_distribution"
#' Cross-protection effect of bivalent and quadrivalent vaccines
#'
#' A dataset containing cross-protection effect of bivalent and quadrivalent vaccines
#'
#' @format A data table with 5 observations of 7 variables.
#' \describe{
#' \item{hpv_type}{HPV strain type}
#' \item{bivalent}{Cross-protection of bivalent vaccine against the corresponding HPV strain type (mean)}
#' \item{bivalent_low}{Cross-protection of bivalent vaccine against the corresponding HPV strain type (lower bound of 95\% uncertainty interval)}
#' \item{bivalent_high}{Cross-protection of bivalent vaccine against the corresponding HPV strain type (upper bound of 95\% uncertainty interval)}
#' \item{quadrivalent}{Cross-protection of quadrivalent vaccine against the corresponding HPV strain type (mean)}
#' \item{quadrivalent_low}{Cross-protection of quadrivalent vaccine against the corresponding HPV strain type (lower bound of 95\% uncertainty interval)}
#' \item{quadrivalent_high}{Cross-protection of quadrivalent vaccine against the corresponding HPV strain type (upper bound of 95\% uncertainty interval)}
#' }
#' @source {Malagón T, Drolet M, Boily MC, Franco EL, Jit M, Brisson J, Brisson M.
#' Cross-protective efficacy of two human papillomavirus vaccines: a systematic review and meta-analysis.
#' Lancet Infect Dis. 2012 Oct;12(10):781-9. \url{https://doi.org/10.1016/S1473-3099(12)70187-1}}
"data.cross_protection"
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