get_p_Imperial: Estimate Covid2019 outcome probabilities for a population...

In epicentre-msf/covidestim: Estimates Of Epidemiological Parameters For COVID19

Description

Estimate Covid19 outcome probabilities including hospitalizion|infection, ICU|hospitalization, death|ICU, death|non-ICU, and death|infection, using age-severity estimates from MRC-IDE at Imperial College, and the population age distribution for a given country, either taken from the UN World Population Prospects 2019 (WPP2019) or directly supplied by the user.

Usage

get_p_Imperial(x, p_type = c("p_hosp_inf", "p_icu_hosp", "p_dead_icu",
  "p_dead_nonicu", "p_dead_inf"))

Arguments

x	Either an ISO3 country code used to extract age-specific population estimates from the UN World Population Prospects 2019 dataset, or, a data.frame containing age categories in the first column and population counts (or proportions) in the second column. To match the severity estimates, age groups must match or be aggregatable to 5-year intervals (0-4, 5-9, ...).
p_type	Outcome to estimate (either "p_hosp_inf", "p_icu_hosp", "p_dead_icu", "p_dead_nonicu", or "p_dead_inf")

Value

Estimated outcome probability (scalar)

Author(s)

Patrick Barks <[e-mail]>

Source

https://mrc-ide.github.io/global-lmic-reports/parameters.html

Examples

# mean Pr(hospitalization|infection) for Canada (ISO3 code "CAN"), taking age
# distribution from WPP2019
get_p_Imperial(x = "CAN", p_type = "p_hosp_inf")

epicentre-msf/covidestim documentation built on Jan. 1, 2021, 1:06 a.m.