Data, code and protocol for: Patient and area contributions to unfavourable treatment outcomes among new tuberculosis cases in Brazil across the COVID-19 pandemic, 2015–23: a nationwide registry-based multilevel cohort study

Data, code and study protocol accompanying the article "Patient and area contributions to unfavourable treatment outcomes among new tuberculosis cases in Brazil across the COVID-19 pandemic, 2015–23: a nationwide registry-based multilevel cohort study" (submitted to The Lancet Regional Health – Americas). Nationwide retrospective cohort of 603,664 new tuberculosis cases in 5,334 municipalities notified to SINAN, Brazil, 2015–2023.Contents: the final supplementary appendix (Tables S1–S32, Figures S1–S7, STROBE-RECORD checklist); the study protocol, version 1.1, written retrospectively (appendix section B); the data dictionary (appendix Table S2, plus a column-level dictionary of every CSV); the analysis code (Python 3.13; R 4.5.0 with lme4 1.1-37; R 4.6.1 with lme4 2.0-6 for the parametric bootstrap); derived de-identified aggregate tables (municipality, state, month, year or model level); and saved model objects (model summaries without patient rows). Methods covered: three-level logistic models (patients, municipalities, states) with parametric bootstrap (500 replicates), standardised annual proportions, a monthly interrupted time series with Monte Carlo propagation of uncertainty (1,000 draws), patient/area decomposition, spatial analysis (global and empirical Bayes Moran's I, correlogram, LISA), sensitivity analyses including multiple imputation by chained equations, the municipal Gini index and Bolsa Família coverage, SINAN–SIM linkage feasibility in Bahia and a municipal ranking for Bahia.Individual-level SINAN and SIM microdata are not redistributed; they are public at DATASUS (TUBEBR15–23; MD5 checksums in appendix Table S1) and can be regenerated with the scripts. Data, supplementary material, protocol and text are licensed under CC BY 4.0; code (scripts/) under the MIT License (LICENSE-CODE).