SidneyBissoli/sipni-microdados

SI-PNI — Routine Vaccination Microdata (Brazil, 2020–present)

Individual-level vaccination records from Brazil's National Immunization Program (SI-PNI), redistributed as partitioned Apache Parquet for efficient analytical access. Each row represents one administered dose.

Part of the healthbr-data project — open redistribution of Brazilian public health data.

Summary

Item	Detail
Official source	OpenDATASUS / Ministry of Health
Temporal coverage	January 2020 – present (monthly updates)
Geographic coverage	All 5,570 Brazilian municipalities
Granularity	Individual record (one row per administered dose)
Volume	736M+ records
Format	Apache Parquet, partitioned by ano/mes/uf
Data types	All fields stored as string (preserves leading zeros)
Update frequency	Monthly
License	CC-BY 4.0

Resumo em português

SI-PNI — Microdados de Vacinação de Rotina (Brasil, 2020–presente)

Microdados individuais de vacinação de rotina do Sistema de Informação do Programa Nacional de Imunizações (SI-PNI), redistribuídos em formato Apache Parquet particionado para acesso analítico eficiente. Cada linha representa uma dose aplicada.

Item	Detalhe
Fonte oficial	OpenDATASUS / Ministério da Saúde
Cobertura temporal	Janeiro/2020 – presente (atualização mensal)
Cobertura geográfica	Todos os 5.570 municípios brasileiros
Granularidade	Registro individual (uma linha por dose aplicada)
Volume	736M+ registros
Formato	Apache Parquet, particionado por ano/mes/uf
Atualização	Mensal

Para documentação completa em português, consulte o repositório do projeto.

Data access

Data is hosted on Cloudflare R2 and accessed via S3-compatible API. The credentials below are read-only and intended for public use.

R (Arrow)

library(arrow)
library(dplyr)

Sys.setenv(
  AWS_ENDPOINT_URL      = "https://5c499208eebced4e34bd98ffa204f2fb.r2.cloudflarestorage.com",
  AWS_ACCESS_KEY_ID     = "28c72d4b3e1140fa468e367ae472b522",
  AWS_SECRET_ACCESS_KEY = "2937b2106736e2ba64e24e92f2be4e6c312bba3355586e41ce634b14c1482951",
  AWS_DEFAULT_REGION    = "auto"
)

ds <- open_dataset("s3://healthbr-data/sipni/microdados/", format = "parquet")

# Example: vaccines administered in Acre, January 2024
ds |>
  filter(ano == "2024", mes == "01", uf == "AC") |>
  count(ds_vacina) |>
  collect()

Python (PyArrow)

import pyarrow.dataset as pds
import pyarrow.fs as fs

s3 = fs.S3FileSystem(
    endpoint_override="https://5c499208eebced4e34bd98ffa204f2fb.r2.cloudflarestorage.com",
    access_key="28c72d4b3e1140fa468e367ae472b522",
    secret_key="2937b2106736e2ba64e24e92f2be4e6c312bba3355586e41ce634b14c1482951",
    region="auto"
)

dataset = pds.dataset(
    "healthbr-data/sipni/microdados/",
    filesystem=s3,
    format="parquet",
    partitioning="hive"
)

table = dataset.to_table(
    filter=(pds.field("ano") == "2024") & (pds.field("uf") == "AC")
)
print(table.to_pandas().head())

Note: These credentials are read-only and safe to use in scripts. The bucket does not allow anonymous S3 access — credentials are required.

File structure

s3://healthbr-data/sipni/microdados/
  README.md
  ano=2020/
    mes=01/
      uf=AC/
        part-0.parquet
      uf=AL/
        part-0.parquet
      ...
    mes=02/
      ...
  ano=2021/
    ...

Each Parquet file contains records for a specific month and state. Hive-style partitioning (key=value) enables automatic partition pruning in Arrow and DuckDB — filtered queries read only the relevant files.

Schema

The dataset contains 56 variables, all stored as string to preserve leading zeros in IBGE municipality codes, CNES facility codes, ZIP codes, and race/ethnicity codes. Key variables include:

Variable	Description
dt_vacina	Vaccination date (YYYY-MM-DD)
co_vacina	Immunobiological code
ds_vacina	Immunobiological description
co_dose	Dose code (1st, 2nd, 3rd, booster, etc.)
sg_uf	State abbreviation
co_municipio_ibge	IBGE municipality code (6 digits)
co_cnes	CNES health facility code
dt_nascimento	Patient date of birth
co_sexo	Sex (M/F)
co_raca_cor	Self-reported race/ethnicity

For the complete 56-variable data dictionary, see the Ministry of Health's Dicionario_tb_ria_rotina.pdf.

Source and processing

Original source: Compressed JSON files from OpenDATASUS (Ministry of Health S3 bucket).

Why JSON instead of CSV? The CSV exports from 2020–2024 contain serialization artifacts (numeric fields with .0 suffix, loss of leading zeros). JSON preserves all values as strings with full integrity.

Processing: JSON → NDJSON (via jq) → Parquet (via polars) → upload to R2 (via rclone). No transformations are applied — values are published exactly as provided by the Ministry of Health.

Known limitations

1. Government data, not ours. Errors in the original data are intentionally preserved. No cleaning or correction is applied.
2. Variable completeness. Many fields have optional reporting and may contain high proportions of empty values or "SEM INFORMACAO".
3. All fields are strings. Type casting (Date, integer) must be done by the user at analysis time.
4. Temporal coverage. Individual-level microdata is available only from January 2020. For the 1994–2019 historical series, see the aggregated datasets: sipni-agregados-doses and sipni-agregados-cobertura.
5. Lag. The Ministry may take weeks to publish a given month's data. The pipeline runs monthly and reflects what is available at the source.
6. Does not include COVID-19. COVID vaccination data is in a separate dataset: sipni-covid.

Citation

@misc{healthbrdata,
  author = {Sidney da Silva Bissoli},
  title  = {healthbr-data: Redistribution of Brazilian Public Health Data},
  year   = {2026},
  url    = {https://huggingface.co/datasets/SidneyBissoli/sipni-microdados},
  note   = {Original source: Ministry of Health / OpenDATASUS}
}

Contact

• GitHub: https://github.com/SidneyBissoli
• Hugging Face: https://huggingface.co/SidneyBissoli
• E-mail: sbissoli76@gmail.com

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Last updated: 2026-02-28