get_p_severe_JHU: Estimate probability distribution of mild/moderate/severe...

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

Description

Based on age-specific outcome severity data from Shenzhen, China (Bi et al. 2020). Population age distributions can either be taken from the UN World Population Prospects 2019 (WPP2019), or directly supplied by the user.

Usage

get_p_severe_JHU(x, outcome = c("severe", "moderate", "mild"),
  model = c("Update", "JHU Original"), return_draws = FALSE)

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
outcome	Outcome category ("severe", "moderate", or "mild")
model	Which model to use to derive posterior probabilities ("Update" or "JHU Original")
return_draws	Logical indicating whether to include vector of draws from the posterior distribution of outcome probabilities in the returned list. Defaults to FALSE.

Value

A list with 8 elements relating to the posterior distribution of outcome probabilities for the population of interest, taken over all age classes:

ests	vector of 2000 draws from posterior distribution
mean	mean of posterior distribution
ll	lower 95% CI of posterior distribution
ul	upper 95% CI of posterior distribution
q25	lower 50% CI of posterior distribution
q75	upper 50% CI of posterior distribution
shape	shape parameter of gamma distribution fit to posterior distribution
rate	rate parameter of gamma distribution fit to posterior distribution

Author(s)

Patrick Barks <[e-mail]>

Source

Bi, Q., Wu, Y., Mei, S., Ye, C., Zou, X., Zhang, Z., Liu, X., Wei, L., Truelove, S., Zhang, T., Gao, W., Cheng, C., Tang, X., ..., and Feng, .T. (2020) Epidemiology and Transmission of COVID-19 in Shenzhen China: Analysis of 391 cases and 1,286 of their close contacts. medRxiv preprint. https://doi.org/10.1101/2020.03.03.20028423

Examples

# expected population distribution of severe outcomes for Canada (ISO3 code
# "CAN"), taking age distribution from WPP2019
get_p_severe_JHU(x = "CAN", outcome = "severe")

# 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+"),
  pop = c(1023, 1720, 2422, 3456, 3866, 4104, 4003, 3576),
  stringsAsFactors = FALSE
)

get_p_severe_JHU(x = age_df, outcome = "severe")

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