Funnel Plot for COVID-19 in DKI Jakarta

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1. Importing Data

covid19 <- read_csv("/Users/sharon/OneDrive - Singapore Management University/isss608data/hands-on_exercise4/COVID-19_DKI_Jakarta.csv") %>%
  mutate_if(is.character, as.factor)
Rows: 267 Columns: 7
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (3): City, District, Sub-district
dbl (4): Sub-district ID, Positive, Recovered, Death

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

2. FunnelPlotR Methods

2.1 Basic Funnel Plot

funnel_plot(
  .data = covid19,
  numerator = Positive,
  denominator = Death,
  group = `Sub-district`
)

A funnel plot object with 267 points of which 0 are outliers. 
Plot is adjusted for overdispersion.

2.2 Makeover 1: Proportions

funnel_plot(
  .data = covid19,
  numerator = Death,
  denominator = Positive,
  group = `Sub-district`,
  data_type = "PR",
  xrange = c(0, 6500),
  yrange = c(0, 0.05)
)
Warning: The `xrange` argument deprecated; please use the `x_range` argument
instead.  For more options, see the help: `?funnel_plot`
Warning: The `yrange` argument deprecated; please use the `y_range` argument
instead.  For more options, see the help: `?funnel_plot`

A funnel plot object with 267 points of which 7 are outliers. 
Plot is adjusted for overdispersion.

2.3 Makeover 2: Customized Plot

funnel_plot(
  .data = covid19,
  numerator = Death,
  denominator = Positive,
  group = `Sub-district`,
  data_type = "PR",
  xrange = c(0, 6500),
  yrange = c(0, 0.05),
  label = NA,
  title = "Cumulative COVID-19 Fatality Rate by Cumulative Total Number of COVID-19 Positive Cases",
  x_label = "Cumulative COVID-19 Positive Cases",
  y_label = "Cumulative Fatality Rate"
)
Warning: The `xrange` argument deprecated; please use the `x_range` argument
instead.  For more options, see the help: `?funnel_plot`
Warning: The `yrange` argument deprecated; please use the `y_range` argument
instead.  For more options, see the help: `?funnel_plot`

A funnel plot object with 267 points of which 7 are outliers. 
Plot is adjusted for overdispersion.

3. ggplot2 Funnel Plot

3.1 Compute Rate & SE

df <- covid19 %>%
  mutate(rate = Death / Positive) %>%
  mutate(rate.se = sqrt((rate * (1 - rate)) / Positive)) %>%
  filter(rate > 0)

fit.mean <- weighted.mean(df$rate, 1 / df$rate.se^2)

3.2 Compute Confidence Intervals

number.seq <- seq(1, max(df$Positive), 1)
number.ll95 <- fit.mean - 1.96 * sqrt((fit.mean * (1 - fit.mean)) / number.seq)
number.ul95 <- fit.mean + 1.96 * sqrt((fit.mean * (1 - fit.mean)) / number.seq)
number.ll999 <- fit.mean - 3.29 * sqrt((fit.mean * (1 - fit.mean)) / number.seq)
number.ul999 <- fit.mean + 3.29 * sqrt((fit.mean * (1 - fit.mean)) / number.seq)

dfCI <- data.frame(number.ll95, number.ul95, number.ll999, number.ul999, number.seq, fit.mean)

3.3 Static Funnel Plot

p <- ggplot(df, aes(x = Positive, y = rate)) +
  geom_point(aes(label = `Sub-district`), alpha = 0.4) +
  geom_line(data = dfCI, aes(x = number.seq, y = number.ll95), colour = "grey40", linetype = "dashed") +
  geom_line(data = dfCI, aes(x = number.seq, y = number.ul95), colour = "grey40", linetype = "dashed") +
  geom_line(data = dfCI, aes(x = number.seq, y = number.ll999), colour = "grey40") +
  geom_line(data = dfCI, aes(x = number.seq, y = number.ul999), colour = "grey40") +
  geom_hline(aes(yintercept = fit.mean), colour = "grey40") +
  coord_cartesian(ylim = c(0, 0.05)) +
  ggtitle("Cumulative Fatality Rate by Cumulative Number of COVID-19 Cases") +
  xlab("Cumulative Number of COVID-19 Cases") +
  ylab("Cumulative Fatality Rate") +
  theme_light()
Warning in geom_point(aes(label = `Sub-district`), alpha = 0.4): Ignoring
unknown aesthetics: label
p

3.4 Interactive Funnel Plot

ggplotly(p, tooltip = c("label", "x", "y"))