get_p_Neher: 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|hospitalization, and death|infection, using age-severity estimates from the Neher Lab, 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_Neher(x, p_type = c("p_hosp_inf", "p_icu_hosp", "p_dead_hosp",
  "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
p_type	Outcome to estimate (either "p_hosp_inf", "p_icu_hosp", "p_dead_hosp", or "p_dead_inf")

Value

Estimated outcome probability (scalar)

Author(s)

Flavio Finger

Patrick Barks <[e-mail]>

Source

https://covid19-scenarios.org/

Examples

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

# use custom age-distribution
age_df <- data.frame(
  age = c("0-9", "10-19", "20-29", "30-39", "40-49", "50-59", "60-69", "70-79", "80+"),
  pop = c(1023, 1720, 2422, 3456, 3866, 4104, 4003, 3576, 1210),
  stringsAsFactors = FALSE
)

get_p_Neher(x = age_df, p_type = "p_hosp_inf")

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