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unvaccinated-maori.R
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# Charts of numbers of unvaccinated Māori people
# *****************************************************************************
# Setup ----
library(tidyverse)
library(here)
library(glue)
library(janitor)
library(scales)
library(readxl)
latest_date <- "09_11_2021"
latest_date_nice <- "9 November 2021"
# *****************************************************************************
# *****************************************************************************
# Load data ----
# Latest vaccination data from MoH
dat <- read_excel(path = here(glue("data/covid_vaccinations_{latest_date}.xlsx")),
sheet = "DHBofResidence by ethnicity") |>
clean_names() |>
select(-x10, -notes)
# *****************************************************************************
# *****************************************************************************
# Process data ----
# Manipulate vaccination data for Māori
dat_m <- dat |>
# Filter Māori and exclude unknown DHB
filter(ethnic_group == "Maori",
dhb_of_residence != "Overseas / Unknown") |>
# Assign custom age groups
mutate(age_group_2 = case_when(
age_group == "12-15" ~ "12-29",
age_group == "16-19" ~ "12-29",
age_group == "20-24" ~ "12-29",
age_group == "25-29" ~ "12-29",
age_group == "30-34" ~ "30-59",
age_group == "35-39" ~ "30-59",
age_group == "40-44" ~ "30-59",
age_group == "45-49" ~ "30-59",
age_group == "50-54" ~ "30-59",
age_group == "55-59" ~ "30-59",
age_group == "60-64" ~ "60+",
age_group == "65-69" ~ "60+",
age_group == "70-74" ~ "60+",
age_group == "75-79" ~ "60+",
age_group == "80-84" ~ "60+",
age_group == "85-89" ~ "60+",
age_group == "90+" ~ "60+"
)) |>
# Summarise population and first doses by DHB and age group
group_by(dhb_of_residence, age_group_2) |>
summarise(population = sum(population),
first_dose_administered = sum(first_dose_administered)) |>
ungroup() |>
# Calculate unvaccinated number in each group
mutate(unvax = pmax(population - first_dose_administered, 0)) |>
# Apply factors for ordering
mutate(age_group_2 = factor(x = age_group_2,
levels = c("12-29",
"30-59",
"60+"),
labels = c("12-29 years old",
"30-59 years old",
"60+ years old"),
ordered = TRUE)) |>
mutate(dhb_of_residence = factor(x = dhb_of_residence,
levels = c("Northland",
"Auckland Metro",
"Auckland",
"Waitemata",
"Counties Manukau",
"Waikato",
"Bay of Plenty",
"Taranaki",
"Lakes",
"Tairawhiti",
"Whanganui",
"MidCentral",
"Hawkes Bay",
"Capital & Coast and Hutt Valley",
"Capital and Coast",
"Hutt Valley",
"Wairarapa",
"Nelson Marlborough",
"West Coast",
"Canterbury",
"South Canterbury",
"Southern"),
ordered = TRUE)) |>
arrange(dhb_of_residence, age_group_2)
# *****************************************************************************
# *****************************************************************************
# Visualise ----
# Bar chart of numbers of unvaccinated people
chart_m_bar <- dat_m |>
ggplot(mapping = aes(x = dhb_of_residence,
y = unvax,
fill = age_group_2,
colour = age_group_2,
label = comma(x = unvax, accuracy = 1))) +
geom_hline(yintercept = 0, size = 0.25, colour = grey(0.5)) +
geom_col(size = 0) +
geom_text(nudge_y = 800,
family = "Fira Sans",
size = 3) +
facet_wrap(facets = vars(age_group_2), ncol = 1) +
scale_y_continuous(labels = comma_format(accuracy = 1),
limits = c(0, 12000),
breaks = seq(0, 24000, 2000)) +
scale_x_discrete(position = "top") +
scale_colour_manual(values = c("12-29 years old" = "#6929c4",
"30-59 years old" = "#1192e8",
"60+ years old" = "#005d5d"),
guide = "none",
aesthetics = c("colour", "fill")) +
xlab("") +
ylab("") +
ggtitle(label = glue("Number of unvaccinated Māori people as at {latest_date_nice}")) +
theme_minimal(base_family = "Fira Sans") +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major.y = element_line(size = 0.25, colour = grey(0.9)),
axis.text.x.top = element_text(angle = 45, hjust = 0, face = "bold"),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
panel.spacing.y = unit(16, "pt"),
plot.margin = margin(4, 16, 4, 4, "pt"),
strip.text = element_text(face = "bold"))
ggsave(filename = here(glue("outputs/unvax_maori_{latest_date}.png")),
plot = chart_m_bar,
width = 2800,
height = 2000,
units = "px",
device = "png",
bg = "white")
# *****************************************************************************
# *****************************************************************************
# Scratch ----
# Other charts; unused at this stage
mu <- dat |>
filter(dhb_of_residence != "Overseas / Unknown",
dhb_of_residence != "Various") |>
mutate(ethnic_group_2 = ifelse(ethnic_group == "Maori", "Māori", "Non-Māori")) |>
group_by(dhb_of_residence, ethnic_group_2) |>
summarise(population = sum(population),
first_dose_administered = sum(first_dose_administered)) |>
ungroup() |>
mutate(unvax = population - first_dose_administered) |>
group_by(dhb_of_residence) |>
mutate(population_pct = population / sum(population),
unvax_pct = unvax / sum(unvax)) |>
ungroup() |>
select(dhb_of_residence,
ethnic_group_2,
population_pct,
unvax_pct) |>
pivot_longer(cols = c(population_pct, unvax_pct),
names_to = "measure",
values_to = "value") |>
mutate(measure = factor(x = measure,
levels = c("population_pct",
"unvax_pct"),
labels = c("All people aged 12+",
"Unvaccinated people aged 12+"),
ordered = TRUE))
chart_mu <- mu |>
ggplot(mapping = aes(y = fct_rev(measure),
x = value,
label = percent(x = value,
accuracy = 0.1),
fill = fct_rev(ethnic_group_2))) +
geom_col(size = 0) +
geom_text(colour = "white",
position = position_stack(vjust = 0.5)) +
facet_wrap(facets = vars(dhb_of_residence), ncol = 3) +
scale_fill_manual(values = c("Māori" = "firebrick",
"Non-Māori" = grey(0.7)),
name = NULL) +
theme(legend.position = "top") +
xlab("") +
ylab("") +
scale_x_continuous(labels = percent_format(accuracy = 1))
chart_mu
mu2 <- dat |>
mutate(ethnic_group_2 = ifelse(ethnic_group == "Maori", "Māori", "Non-Māori")) |>
filter(age_group != "Various") |>
mutate(age_group_2 = case_when(
age_group == "12-15" ~ "12-29",
age_group == "16-19" ~ "12-29",
age_group == "20-24" ~ "12-29",
age_group == "25-29" ~ "12-29",
age_group == "30-34" ~ "30-59",
age_group == "35-39" ~ "30-59",
age_group == "40-44" ~ "30-59",
age_group == "45-49" ~ "30-59",
age_group == "50-54" ~ "30-59",
age_group == "55-59" ~ "30-59",
age_group == "60-64" ~ "60+",
age_group == "65-69" ~ "60+",
age_group == "70-74" ~ "60+",
age_group == "75-79" ~ "60+",
age_group == "80-84" ~ "60+",
age_group == "85-89" ~ "60+",
age_group == "90+" ~ "60+"
)) |>
mutate(age_group_2 = factor(x = age_group_2,
levels = c("12-29",
"30-59",
"60+"),
labels = c("12-29 years",
"30-59 years",
"60+ years"),
ordered = TRUE)) |>
mutate(dhb_of_residence_2 = case_when(
dhb_of_residence == "Auckland Metro" ~ "Auckland",
TRUE ~ "Outside Auckland"
)) |>
group_by(dhb_of_residence_2, age_group_2, ethnic_group_2) |>
summarise(population = sum(population),
first_dose_administered = sum(first_dose_administered)) |>
ungroup() |>
mutate(unvax = population - first_dose_administered)
chart_mu2 <- mu2 |>
ggplot(mapping = aes(x = age_group_2,
y = unvax,
label = comma(unvax, accuracy = 1),
fill = fct_rev(ethnic_group_2),
colour = fct_rev(ethnic_group_2))) +
geom_col() +
geom_text(position = position_stack(),
mapping = aes(y = unvax + 3000)) +
facet_wrap(facets = vars(dhb_of_residence_2), ncol = 2) +
scale_y_continuous(labels = comma_format(accuracy = 1),
breaks = seq(0, 250000, 25000)) +
scale_fill_manual(values = c("Māori" = "firebrick",
"Non-Māori" = grey(0.7)),
name = NULL,
aesthetics = c("colour", "fill")) +
ylab("") +
xlab("") +
ggtitle("Unvaccinated people") +
theme_minimal() +
theme(legend.position = "top",
legend.direction = "horizontal",
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank())
chart_mu2
# *****************************************************************************