9.3 Mapping malaria prevalence

index <- inla.stack.index(stack = stk.full, 
                          tag = "pred")$data

# res$summary.fitted.values

prev_mean <- res$summary.fitted.values[index, "mean"]
prev_ll <- res$summary.fitted.values[index, "0.025quant"]
prev_ul <- res$summary.fitted.values[index, "0.975quant"]

pal <- colorNumeric("viridis", c(0, 1), na.color = "transparent")

leaflet() %>%
  addProviderTiles(providers$CartoDB.Positron) %>%
  addCircles(
    lng = coop[, 1], lat = coop[, 2],
    color = pal(prev_mean)
  ) %>%
  addLegend("bottomright",
    pal = pal, values = prev_mean,
    title = "Prev."
  ) %>%
  addScaleBar(position = c("bottomleft"))

r_prev_mean <- rasterize(
  x = coop, y = ra, field = prev_mean,
  fun = mean
)

pal <- colorNumeric("viridis", c(0, 1), na.color = "transparent")

leaflet() %>%
  addProviderTiles(providers$CartoDB.Positron) %>%
  addRasterImage(r_prev_mean, colors = pal, opacity = 0.5) %>%
  addLegend("bottomright",
    pal = pal,
    values = values(r_prev_mean), title = "Prev."
  ) %>%
  addScaleBar(position = c("bottomleft"))

r_prev_ll <- rasterize(
  x = coop, y = ra, 
  field = prev_ll,
  fun = mean
)

leaflet() %>%
  addProviderTiles(providers$CartoDB.Positron) %>%
  addRasterImage(r_prev_ll, colors = pal, opacity = 0.5) %>%
  addLegend("bottomright",
    pal = pal,
    values = values(r_prev_ll), title = "LL"
  ) %>%
  addScaleBar(position = c("bottomleft"))

r_prev_ul <- rasterize(
  x = coop, y = ra, field = prev_ul,
  fun = mean
)

leaflet() %>%
  addProviderTiles(providers$CartoDB.Positron) %>%
  addRasterImage(r_prev_ul, colors = pal, opacity = 0.5) %>%
  addLegend("bottomright",
    pal = pal,
    values = values(r_prev_ul), title = "UL"
  ) %>%
  addScaleBar(position = c("bottomleft"))