Reproduction number from renewal equation applied to modelled incidence using statistical re-sampling

Calculate a reproduction number estimate from modelled incidence estimates, by statistical sampling from a log-normally distributed incidence estimate, combined with uncertain infectivity profile specified as multiple discrete empirical distributions.

Usage

rt_from_renewal(
  df = i_incidence_model,
  ip = i_discrete_ip,
  bootstraps = 1000,
  seed = Sys.time()
)

Arguments

df

modelled incidence estimate

A dataframe containing the following columns:

• time (ggoutbreak::time_period + group_unique) - A (usually complete) set of singular observations per unit time as a `time_period`

• incidence.fit (double) - an estimate of the incidence rate on a log scale

• incidence.se.fit (positive_double) - the standard error of the incidence rate estimate on a log scale

• incidence.0.025 (positive_double) - lower confidence limit of the incidence rate (true scale)

• incidence.0.5 (positive_double) - median estimate of the incidence rate (true scale)

• incidence.0.975 (positive_double) - upper confidence limit of the incidence rate (true scale)

Any grouping allowed.

ip

infectivity profile

A dataframe containing the following columns:

• boot (anything + default(1)) - a bootstrap identifier

• probability (proportion) - the probability of new event during this period.

• tau (integer + complete) - the days since the index event.

Must be grouped by: boot (exactly).

A default value is defined.

bootstraps

the number of samples to take at each time point. This will be rounded up to a whole multiple of the infectivity profile distribution length.

seed

a random number seed for reproducibility

Value

A dataframe containing the following columns:

• time (ggoutbreak::time_period + group_unique) - A (usually complete) set of singular observations per unit time as a time_period

• rt.fit (double) - an estimate of the reproduction number

• rt.se.fit (positive_double) - the standard error of the reproduction number

• rt.0.025 (double) - lower confidence limit of the reproduction number

• rt.0.5 (double) - median estimate of the reproduction number

• rt.0.975 (double) - upper confidence limit of the reproduction number

Any grouping allowed.

Examples

df = ggoutbreak::england_covid %>%
  time_aggregate(count=sum(count)) %>%
    poisson_locfit_model()

if (interactive()) {
  # not run
  withr::with_options(list("ggoutbreak.keep_cdf"=TRUE),{
   tmp2 = df %>%
      rt_from_renewal(ganyani_ip)
  })

}