Description Usage Arguments Value Author(s) Source Examples
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.
1 2 | get_p_Neher(x, p_type = c("p_hosp_inf", "p_icu_hosp", "p_dead_hosp",
"p_dead_inf"))
|
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") |
Estimated outcome probability (scalar)
Flavio Finger
Patrick Barks <patrick.barks@epicentre.msf.org>
https://covid19-scenarios.org/
1 2 3 4 5 6 7 8 9 10 11 12 | # 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")
|
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