Plot the immunity or population size of a popim_population object

Plot the immunity or population size of a popim_population object

plot_immunity(pop, cols = c("whitesmoke", "midnightblue"))

plot_pop_size(pop, rel = FALSE, cols = c("whitesmoke", "midnightblue"))

Arguments

pop: popim_population object such as created by popim_population().
cols: vector of 2 colours to be used to generate the (continuous) colour palette for plotting. Defaults to c("whitesmoke", "midnightblue").
rel: logical to indicate whether to use relative or absolute population size in plot_pop_size(). Defaults to FALSE (plotting absolute population size).

Value

A ggplot object.

Details

The population is displayed in a grid showing the cohorts through time. Time is shown on the x-axis, age on the y-axis, such that a particular cohort tracks along diagonally from bottom left to top right. If there are several regions, these are shown as separate facets.

The colour in each cell corresponds to:

for plot_immunity(): the proportion of each cohort that is immune, therefore varying between 0 and 1.
for plot_pop_size(): the size of each cohort.

As the returned object is a regular ggplot object, it can be further modified with the ususal ggplot2 syntax.

Author

Tini Garske

Examples

## set up population and vaccination activities:
pop <- popim_population(region = "UK", year_min = 2000, year_max = 2005,
                        age_min = 0, age_max = 10)
vacc <- popim_vacc_activities(region = "UK", year = c(2001, 2002),
                              age_first = 0, age_last = 0,
                              coverage = 0.8, doses = NA,
                              targeting = "random")

## update the population immunity based on the vaccination activities:
pop <- apply_vacc(pop, vacc)

## plot the population immunity by age and time:
plot_immunity(pop)


## adding some population size manually:
##  adding some population size manually:
pop$pop_size <- pop$cohort - 1990

## plot the population size by age and time:
plot_pop_size(pop)


##-----------------------------------------------------------------------
## setting up a population with multiple regions:
pop <- popim_population(region = c("A", "B"),
                        year_min = 2000, year_max = 2005,
                        age_min = 0, age_max = 10)
pop$pop_size <- pop$cohort - 1990
pop$pop_size[pop$region == "A"] <- 5 * pop$pop_size[pop$region == "A"]

## adding some vaccination activities:
vacc <- popim_vacc_activities(region = c("A", "A", "B"),
                              year = c(2001, 2002, 2003),
                              age_first = c(0,0,0), age_last = c(0,0,10),
                              coverage = 0.8, doses = NA,
                              targeting = "random")
pop <- apply_vacc(pop, vacc)

plot_immunity(pop)


plot_pop_size(pop)

plot_pop_size(pop, rel = TRUE)