RunCohort | R Documentation |
Runs PRIME for one birth-cohort. Usually called by another function such as RunCountry().
RunCohort(
lifetab,
cohort,
incidence,
mortality_cecx,
prevalence,
agevac,
coverage,
campaigns,
vaccine_efficacy_nosexdebut,
vaccine_efficacy_sexdebut,
cost_cancer,
discounting = FALSE,
disc.cost = 0.03,
disc.ben = 0.03,
country_iso3 = NULL,
run_country = FALSE,
disability.weights = "gbd_2017"
)
lifetab |
Data.table: The life-table for this cohort. Can be created using the lifeTable() function. |
cohort |
Number: The cohort-size of this birth-cohort at the time where the lifetable starts. |
incidence |
Numeric vector: Age-specific CeCx(16/18) incidence-rates. |
mortality_cecx |
Numeric vector: Age-specific CeCx(16/18) mortality-rates. |
prevalence |
Numeric vector: Age-specific CeCx(16/18) prevalence rates (5-year prevalence) – referring to people who are alive within 5 years of diagnosis. |
agevac |
Number: Age at which the cohort is vaccinated. |
coverage |
Number: Proportion of the cohort that will receive a vaccination. |
campaigns |
List or number: MAC cohort-vaccinations (needs to be changed). |
vaccine_efficacy_nosexdebut |
Number: proportion indicating vaccine-efficacy before sexual debut. |
vaccine_efficacy_sexdebut |
Number: proportion indicating vaccine-efficacy after sexual debut. |
cost_cancer |
Number: total per capita cost of cancer. |
discounting |
Logical (optional): If TRUE, run cost-effectiveness analysis undiscounted and discounted. If FALSE, only uses undiscounted |
disc.cost |
Number (optional): Discounting for health costs (only if discounting=TRUE) |
disc.ben |
Number (optional): Discounting for health outcomes (only if discounting=TRUE) |
Returns a data.table with size of the birth-cohort and age-specific incidence-rates, mortality-rates, years-of-life-lost, years-of-healthy-life-lost, and cancer-costs before and after vaccination. Also displays whether discounting has been used ("type" column).
lifetab <- lifeTable(unlist(data.mortall[iso3=="AFG",
as.character(0:100), with=FALSE], use.names=FALSE), 9)
cohort <- -1
incidence <- unlist(data.incidence[iso3=="AFG", as.character(0:100), with=FALSE],
use.names=FALSE)
mortality_cecx <- unlist(data.mortall[iso3=="AFG", as.character(0:100), with=FALSE],
use.names=FALSE)
prevalence <- unlist(data.cecx_5y_prevalence[iso3=="AFG",
as.character(0:100), with=FALSE], use.names=FALSE)
agevac <- 9
coverage <- 0.8
campaigns <- -1
vaccine_efficacy_nosexdebut <- 0.95
vaccine_efficacy_sexdebut <- 0
cost_cancer <- 100
RunCohort(lifetab, cohort, incidence, mortality_cecx, prevalence, agevac,
coverage, campaigns, vaccine_efficacy_nosexdebut, vaccine_efficacy_sexdebut,
cost_cancer, disc.cost=0.03, disc.ben=0.03,
discounting=FALSE, country_iso3="AFG", run_country=FALSE)
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