Growth rate timeseries diagram

Usage

plot_growth_rate(
  modelled = i_timeseries,
  ...,
  mapping = if (interfacer::is_col_present(modelled, class)) ggplot2::aes(colour = class)
    else ggplot2::aes(),
  events = i_events
)

Arguments

modelled

Either:

A dataframe containing the following columns:

time (as.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 (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)
growth.fit (double) - an estimate of the growth rate
growth.se.fit (double) - the standard error the growth rate
growth.0.025 (double) - lower confidence limit of the growth rate
growth.0.5 (double) - median estimate of the growth rate
growth.0.975 (double) - upper confidence limit of the growth rate

No mandatory groupings.

No default value.

OR:

A dataframe containing the following columns:

time (as.time_period + group_unique) - A (usually complete) set of singular observations per unit time as a time_period
proportion.fit (double) - an estimate of the proportion on a logit scale
proportion.se.fit (double) - the standard error of proportion estimate on a logit scale
proportion.0.025 (proportion) - lower confidence limit of proportion (true scale)
proportion.0.5 (proportion) - median estimate of proportion (true scale)
proportion.0.975 (proportion) - upper confidence limit of proportion (true scale)
relative.growth.fit (double) - an estimate of the relative growth rate
relative.growth.se.fit (double) - the standard error the relative growth rate
relative.growth.0.025 (double) - lower confidence limit of the relative growth rate
relative.growth.0.5 (double) - median estimate of the relative growth rate
relative.growth.0.975 (double) - upper confidence limit of the relative growth rate

No mandatory groupings.

No default value.

...

Arguments passed on to geom_events

mapping

a ggplot2::aes mapping. Most importantly setting the colour to something if there are multiple incidence time series in the plot

events

Significant events or time spans

A dataframe containing the following columns:

label (character) - the event label
start (date) - the start date, or the date of the event
end (date) - the end date or NA if a single event

No mandatory groupings.

A default value is defined.

Value

a ggplot timeseries

Examples

# example code
tmp = growthrates::england_covid %>%
  time_aggregate(count=sum(count))

tmp_pop = growthrates::england_demographics %>%
  dplyr::ungroup() %>%
  dplyr::summarise(population = sum(population))



# If the incidence is normalised by population
tmp2 = tmp %>%
  poisson_locfit_model() %>%
  normalise_incidence(tmp_pop)

# Default pdf device doesn't support unicode
plot_growth_rate(tmp2,colour="blue")


tmp3 = growthrates::england_covid %>%
  proportion_locfit_model()

# Default pdf device doesn't support unicode
plot_growth_rate(tmp3)