Rates and Ratios

Calculate attack rate, case fatality rate, and mortality rate

attack_rate(
  cases,
  population,
  conf_level = 0.95,
  multiplier = 100,
  mergeCI = FALSE,
  digits = 2
)

case_fatality_rate(
  deaths,
  population,
  conf_level = 0.95,
  multiplier = 100,
  mergeCI = FALSE,
  digits = 2
)

case_fatality_rate_df(
  x,
  deaths,
  group = NULL,
  conf_level = 0.95,
  multiplier = 100,
  mergeCI = FALSE,
  digits = 2,
  add_total = FALSE
)

mortality_rate(
  deaths,
  population,
  conf_level = 0.95,
  multiplier = 10^4,
  mergeCI = FALSE,
  digits = 2
)

Arguments

cases, deaths

number of cases or deaths in a population. For _df functions, this can be the name of a logical column OR an evaluated logical expression (see examples).

population

the number of individuals in the population.

conf_level

a number representing the confidence level for which to calculate the confidence interval. Defaults to 0.95, representing a 95% confidence interval using binom::binom.wilson()

multiplier

The base by which to multiply the output:

• multiplier = 1: ratio between 0 and 1

• multiplier = 100: proportion

• multiplier = 10^4: x per 10,000 people

mergeCI

Whether or not to put the confidence intervals in one column (default is FALSE)

digits

if mergeCI = TRUE, this determines how many digits are printed

x

a data frame

group

the bare name of a column to use for stratifying the output

add_total

if group is not NULL, then this will add a row containing the total value across all groups.

Value

a data frame with five columns that represent the numerator, denominator, rate, lower bound, and upper bound.

• attack_rate(): cases, population, ar, lower, upper

• case_fatality_rate(): deaths, population, cfr, lower, upper