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MMAING-Arbo

MMAING-Arbo is an extension of the Mixed Model of Artificial Intelligence and Next-Generation (MMAING) ensemble designed for the early detection of dengue outbreaks using routine Primary Health Care (PHC) syndromic data at the municipality level in Brazil.

This repository contains code and resources to reproduce the analyses and evaluation presented in the manuscript below.

Citation

If you use this code, please cite:

Borges DGF, Coutinho ER, Santos-Silva R, Cerqueira-Silva T, Florentino PTV, Marcilio I, Ramos PIP, Barral-Netto M, Landau L, Coutinho ALGA, Barreto ME, Pinho STR, Andrade RFS. Early detection of dengue outbreaks from routine primary health care records: evaluation by an extended version of the Mixed Model of Artificial Intelligence and Next-Generation (MMAING). (under revision). 

Contributing authors • Dérick G. F. Borges • Eluã R. Coutinho • Rejane Santos-Silva • Thiago Cerqueira-Silva • Pilar T. V. Florentino • Izabel Marcilio • Pablo I. P. Ramos • Manoel Barral-Netto • Luiz Landau • Alvaro L. G. A. Coutinho • Marcos E. Barreto • Suani T. R. Pinho • Roberto F. S. Andrade 

Acknowledgements

This work is part of the Alert-Early System of Outbreaks with Pandemic Potential (ÆSOP) initative (http://aesop.health) and is supported by The Rockefeller Foundation, Juntos pela Saúde (a joint BNDES/Umane program), the National Council for Scientific and Technological Research (CNPq), and Brazil's Ministry of Health.

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Code and data for MMAING-Arbo, a Mixed Model of Artificial Intelligence and Next-Generation that performs anomaly detection in time series data.

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