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 Salje et al. (2020), 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 3 | get_p_Salje(x, p_type = c("p_hosp_inf", "p_icu_hosp", "p_dead_hosp",
"p_dead_inf"), p_stat = c("mean", "low_95", "up_95"),
p_sex = c("total", "male", "female"))
|
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") |
p_stat |
Statistic of the severity estimates to use (either "mean", "low_95", or "up_95") |
p_sex |
Use severity estimate for which sex (either "female", "male", or "total") |
Estimated outcome probability (scalar)
Anton Camacho
Patrick Barks <patrick.barks@epicentre.msf.org>
Salje, H., Kiem, C.T., Lefrancq, N., Courtejoie, N., Bosetti, P., Paireau, J., Andronico, A., Hoze, N., Richet, J., Dubost, C.L., and Le Strat, Y. (2020) Estimating the burden of SARS-CoV-2 in France. Science. https://doi.org/10.1126/science.abc3517
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_Salje(x = "CAN", p_type = "p_hosp_inf", p_stat = "mean", p_sex = "total")
# 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_Salje(x = age_df, p_type = "p_hosp_inf", p_stat = "mean", p_sex = "total")
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