SIVEP-Malaria Brazil Notification Data, 2025 and 2026 (preliminar)

This dataset contains raw and processed SIVEP-Malaria notification data for Brazil covering the notification years 2025 and 2026. The raw files were obtained through requests under Brazil’s Access to Information Law (Lei de Acesso à Informação, LAI) from the national malaria surveillance information system, process 25072.030306202615. Those files are preliminary and will be updated monthly.

The deposit includes the original LAI response files (NOTI[YY]_SIVEP.zip) and reproducible processed outputs generated from them (sivep_malaria_[YYYY]_csv.zip and sivep_malaria_[YYYY].parquet). Processed data are provided as per-year files in Parquet and CSV formats. The processing pipeline standardizes variable names, normalizes source header inconsistencies, converts coded categorical variables to readable labels using a machine-readable SIVEP-Malaria data dictionary, parses date fields, adds derived year/month/week fields, and enriches notification, residence, and probable infection geography with IBGE municipality and state metadata.

The release also includes metadata files to support auditability and reuse: a codebook, a release manifest, checksums, and a report of unmapped values. The manifest documents source file selection, row counts, raw and processed column counts, schema differences across years, output file names, source modification times, and MD5 checksums for raw and processed files.

Because these data originate from a public health notification system, users should apply appropriate safeguards when analyzing, redistributing, or linking them with other datasets. The dataset is intended to support epidemiological research, surveillance evaluation, reproducibility, and open scientific use while preserving transparency about provenance and processing steps.

The processing code and documentation are maintained separately in the associated Git repository. Users should cite this Zenodo record, the LAI source, the processing date, and the repository when using these data.