Overview
healthbR provides easy access to Brazilian public health data directly from R. The package downloads, caches, and processes data from official sources, returning clean, analysis-ready tibbles following tidyverse conventions.
Surveys (IBGE / Ministry of Health)
| Module | Description | Years |
|---|---|---|
| VIGITEL | Surveillance of Risk Factors for Chronic Diseases by Telephone Survey | 2006–2024 |
| PNS | National Health Survey (microdata + SIDRA API) | 2013, 2019 |
| PNAD Continua | Continuous National Household Sample Survey | 2012–2024 |
| POF | Household Budget Survey (food security, consumption, anthropometry) | 2002–2018 |
| Censo | Population denominators via SIDRA API | 1970–2022 |
DATASUS (Ministry of Health FTP)
| Module | Description | Granularity | Years |
|---|---|---|---|
| SIM | Mortality Information System (deaths) | Annual/UF | 1996–2024 |
| SINASC | Live Birth Information System | Annual/UF | 1996–2024 |
| SIH | Hospital Information System (admissions) | Monthly/UF | 2008–2024 |
| SIA | Outpatient Information System (13 file types) | Monthly/UF | 2008–2024 |
| SINAN | Notifiable Diseases Surveillance (31 diseases) | Annual/UF | 2007–2024 |
| CNES | National Health Facility Registry (13 file types) | Monthly/UF | 2005–2024 |
| SI-PNI | National Immunization Program (FTP 1994–2019, CSV 2020+) | Annual or Monthly/UF | 1994–2025 |
DATASUS modules download .dbc files (compressed DBF) and decompress them internally using vendored C code – no external dependencies required.
Primary Care & Regulatory Agencies
| Module | Source | Description | Years |
|---|---|---|---|
| SISAB | Ministry of Health REST API | Primary Care coverage indicators (APS, oral health, community agents, PNS) | 2007–present |
| ANS | ANS Open Data Portal | Supplementary health beneficiaries, consumer complaints, financial statements | 2007–present |
| ANVISA | ANVISA Open Data Portal | Product registrations, pharmacovigilance, hemovigilance, technovigilance, SNGPC | snapshot + 2014–present |
Installation
You can install the development version of healthbR from GitHub:
# install.packages("pak")
pak::pak("SidneyBissoli/healthbR")Quick start
library(healthbR)
# see all available data sources
list_sources()DATASUS modules
All DATASUS modules follow a consistent API: *_years(), *_info(), *_variables(), *_dictionary(), *_data(), *_cache_status(), *_clear_cache().
# mortality data -- deaths in Acre, 2022
obitos <- sim_data(year = 2022, uf = "AC")
# filter by cause of death (CID-10 prefix)
obitos_cardio <- sim_data(year = 2022, uf = "AC", cause = "I")
# live births in Acre, 2022
nascimentos <- sinasc_data(year = 2022, uf = "AC")
# hospital admissions in Acre, January 2022
internacoes <- sih_data(year = 2022, month = 1, uf = "AC")
# filter by diagnosis (CID-10 prefix)
intern_resp <- sih_data(year = 2022, month = 1, uf = "AC", diagnosis = "J")
# outpatient production in Acre, January 2022
ambulatorial <- sia_data(year = 2022, month = 1, uf = "AC")
# different file type (e.g., high-cost medications)
medicamentos <- sia_data(year = 2022, month = 1, uf = "AC", type = "AM")Additional DATASUS modules
# disease notifications -- dengue, 2022
dengue <- sinan_data(year = 2022, disease = "DENG")
# health facilities in Acre, January 2023
cnes <- cnes_data(year = 2023, month = 1, uf = "AC")
# vaccination data -- Acre, 2019 (FTP) or 2024 (CSV)
vacinas <- sipni_data(year = 2019, uf = "AC")Survey modules
# VIGITEL telephone survey
vigitel <- vigitel_data(year = 2024)
# PNS national health survey
pns <- pns_data(year = 2019)
# PNAD Continua
pnadc <- pnadc_data(year = 2023, quarter = 1)
# POF household budget survey
pof <- pof_data(year = 2018, register = "morador")
# Census population
pop <- censo_populacao(year = 2022, territorial_level = "state")Primary care & regulatory agencies
# SISAB -- primary care coverage by state, January 2024
sisab <- sisab_data(year = 2024, month = 1)
# ANS -- health plan beneficiaries in Acre, December 2023
ans <- ans_data(year = 2023, month = 12, uf = "AC")
# ANVISA -- registered medicines
med <- anvisa_data(type = "medicines")Explore variables and dictionaries
# list variables for any module
sim_variables()
sia_variables(search = "sexo")
sinan_diseases(search = "dengue")
# data dictionary with category labels
sim_dictionary("SEXO")
sia_dictionary("PA_RACACOR")Parallel downloads
When downloading multiple files (e.g., several years, months, or states), you can speed up downloads by enabling parallel processing. Install furrr and future, then set a parallel plan before calling any *_data() function:
install.packages(c("furrr", "future"))
library(future)
plan(multisession, workers = 4)
# downloads 4 states in parallel
df <- sih_data(year = 2022, month = 1:6, uf = c("SP", "RJ", "MG", "BA"))
# reset to sequential when done
plan(sequential)All 12 download-based modules support parallel downloads: SIM, SINASC, SIH, SIA, SINAN, CNES, SI-PNI, SISAB, ANS, ANVISA, PNS, and PNADC.
Caching
All modules cache downloaded data automatically. Install arrow for optimized Parquet caching:
install.packages("arrow")Each module provides cache management functions:
# check what is cached
sim_cache_status()
sih_cache_status()
sia_cache_status()
# clear cache for a module
sim_clear_cache()Data sources
All data is downloaded from official Brazilian government repositories:
- VIGITEL: Ministry of Health
- PNS / PNAD Continua / POF / Censo: IBGE
- SIM / SINASC / SIH / SIA / SINAN / CNES / SI-PNI: DATASUS FTP
- SISAB: Ministry of Health REST API
- ANS: ANS Open Data Portal
- ANVISA: ANVISA Open Data Portal
Contributing
Please see CONTRIBUTING.md for guidelines on how to contribute to this project.
Code of Conduct
Please note that the healthbR project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.