Description Usage Arguments Value Author(s) Source Examples
View source: R/get_p_ODriscoll.R
Estimate Covid19 outcome probabilities (death|infection), using age-severity estimates from O'Driscoll 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 | get_p_ODriscoll(x, p_type = c("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 ("p_dead_inf" is the only option here) |
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>
Flavio Finger <flavio.finger@epicentre.msf.org>
O’Driscoll, M., Dos Santos, G.R., Wang, L. et al. Age-specific mortality and immunity patterns of SARS-CoV-2. Nature (2020). https://doi.org/10.1038/s41586-020-2918-0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | # mean Pr(death|infection) for Canada (ISO3 code "CAN"), taking age
# distribution from WPP2019
get_p_ODriscoll(x = "CAN", p_stat = "mean", p_sex = "total")
# use custom age-distribution
age_df <- data.frame(
age = c("0-4", "5-9", "10-14", "15-19", "20-24", "25-29", "30-34", "35-39", "40-44", "45-49",
"50-54", "55-59", "60-64", "65-69", "70-74", "75-79", "80+"),
pop = c(1023, 1720, 2422, 3456, 3866, 4104, 4003, 3576, 1210, 1023,
1720, 2422, 3456, 3866, 4104, 4003, 3576),
stringsAsFactors = FALSE
)
get_p_ODriscoll(x = age_df, p_type = "p_dead_inf", p_stat = "mean", p_sex = "total")
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