R: Download spatial data of Brazilian health regions and health...

read_health_region {geobr}

R Documentation

Download spatial data of Brazilian health regions and health macro regions

Description

Health regions are used to guide the the regional and state planning of health services. Macro health regions, in particular, are used to guide the planning of high complexity health services. These services involve larger economics of scale and are concentrated in few municipalities because they are generally more technology intensive, costly and face shortages of specialized professionals. A macro region comprises one or more health regions.

Usage

read_health_region(
  year = 2013,
  macro = FALSE,
  simplified = TRUE,
  showProgress = TRUE
)

Arguments

`year`	Numeric. Year of the data in YYYY format. Defaults to `2013`, the latest available.
`macro`	Logic. If `FALSE` (default), the function downloads health regions data. If `TRUE`, the function downloads macro regions data.
`simplified`	Logic `FALSE` or `TRUE`, indicating whether the function should return the data set with 'original' spatial resolution or a data set with 'simplified' geometry. Defaults to `TRUE`. For spatial analysis and statistics users should set `simplified = FALSE`. Borders have been simplified by removing vertices of borders using `⁠st_simplify{sf}⁠` preserving topology with a `dTolerance` of 100.
`showProgress`	Logical. Defaults to `TRUE` display progress bar.

Value

An ⁠"sf" "data.frame"⁠ object

Other area functions: read_amazon(), read_biomes(), read_capitals(), read_comparable_areas(), read_country(), read_disaster_risk_area(), read_health_facilities(), read_immediate_region(), read_indigenous_land(), read_intermediate_region(), read_meso_region(), read_metro_area(), read_micro_region(), read_municipal_seat(), read_municipality(), read_neighborhood(), read_pop_arrangements(), read_region(), read_schools(), read_semiarid(), read_state(), read_statistical_grid(), read_urban_area(), read_urban_concentrations(), read_weighting_area()

Examples


# Read all health regions for a given year
hr <- read_health_region( year=2013 )

# Read all macro health regions
mhr <- read_health_region( year=2013, macro =TRUE)