rj_mortality: Rio de Janeiro Infant Mortality (2016)

In treeSS: Tree-Spatial Scan Statistic for Cluster Detection

Rio de Janeiro Infant Mortality (2016)

Description

Combined long-format dataset of infant mortality in the 92 municipalities of Rio de Janeiro state, Brazil, 2016. Each row represents a (municipality, ICD-10 leaf) combination with at least one death; missing combinations are implicitly zero. Use together with rj_tree.

Usage

rj_mortality

Format

A data.frame in long format with columns:

region_id

Integer identifier of the municipality.

ibge_code

6-digit IBGE municipality code.

name

Municipality name.

population

IBGE municipal population estimate for 2016.

live_births

Number of live births in 2016 (SINASC). Used as the population denominator in Section 5.2 of Cancado et al. (2025).

x

Longitude of the municipality centroid.

y

Latitude of the municipality centroid.

node_id

Character ICD-10 leaf code (4 characters), matching a leaf of rj_tree.

cases

Integer count of infant deaths.

Details

To reproduce Section 5.2 of Cancado et al. (2025), use live_births as the population denominator:

  data <- rj_mortality
  data$population <- data$live_births
  treespatial_scan(data, rj_tree, ...)

Municipality polygons can be obtained via geobr::read_municipality().

Source

Population: IBGE municipal estimates. Live births: DATASUS/SINASC via TabNet. Deaths: DATASUS/SIM microdata via OpenDATASUS (https://opendatasus.saude.gov.br). Centroids: geobr.

References

Cancado, A.L.F., Oliveira, G.S., Quadros, A.V.C., Duczmal, L. (2025). A tree-spatial scan statistic. Environmental and Ecological Statistics, 32, 953–978. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s10651-025-00670-w")}

See Also

rj_tree

Examples

data(rj_mortality)
head(rj_mortality)
cat("Total deaths:", sum(rj_mortality$cases), "\n")

treeSS documentation built on May 16, 2026, 1:08 a.m.