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Abstracts published in conference proceedings

2023

ARAUJO, E. C.; COELHO, FLÁVIO CODEÇO . Evaluating transfer learning for forecasting chikungunya cases. In: XLII CNMAC, 2023, Bonito - MS. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, 2023. v. 10.

ARAUJO, E. C.; COELHO, FLÁVIO CODEÇO . Forecasting dengue burden using machine learning. In: E-Vigilância 2023, 2023, Rio de Janeiro. Livro de Resumos, 2023.

2024

ALMEIDA, I. F.; LANA, R. M. ; COELHO, F. C. ; CODECO, C. T. . PERFIS DE TRANSMISSÃO DE DENGUE: ANÁLISE DOS MUNICÍPIOS BRASILEIROS (2010-2022). In: 12° Congresso Brasileiro de Epidemiologia, 2024, Rio de Janeiro. Anais do 12º Congresso Brasileiro de Epidemiologia - Vol.3, 2024.

ARAUJO, E. C.; CARVALHO, L. M. ; VACARO, L. B. ; BASTOS, M. M. ; BASTOS, L. S. ; LANA, R. M. ; CODECO, C. T. ; ALMEIDA, I. F. ; FREITAS, L. P. ; SEGUNDO, Z. R. C. ; COELHO, F. C. . MOSQLIMATE: A PLATFORM FOR COMPARING ARBOVIRAL DISEASES FORECASTING MODELS. In: 12° Congresso Brasileiro de Epidemiologia, 2024, Rio de Janeiro. Anais do 12º Congresso Brasileiro de Epidemiologia - Vol.3, 2024.

SEGUNDO, Zuilho Rodrigues Castro , 2025, MODELOS DE DECISÃO PARA TESTAGEM DE CASOS SUSPEITOS DE ARBOVIROSES POR RL. In: 12° Congresso Brasileiro de Epidemiologia, 2024, Rio de Janeiro. Anais do 12º Congresso Brasileiro de Epidemiologia - Vol.3, 2024.

Publications

2024

Magalhaes, T., Coelho, F. C., Souza, W. V., Viana, I. F., Jaenisch, T., Marques, E. T., ... & Braga, C. (2024). Effect of Sexual Partnerships on Zika Virus Transmission in Virus-Endemic Region, Northeast Brazil. Emerging Infectious Diseases, 30(12), 2559. https://doi.org/10.3201/eid3012.231733.

2025

Araujo, E. C., Codeço, C. T., Loch, S., Vacaro, L. B., Freitas, L. P., Lana, R. M., ... & Coelho, F. C. (2025). Large-scale epidemiological modelling: scanning for mosquito-borne diseases spatio-temporal patterns in Brazil. Royal Society Open Science, 12(5), 241261. https://doi.org/10.1098/rsos.241261.

Preprints

2024

Ganem, F., Vacaro, L. B., Araujo, E. C., Alves, L. D., Bastos, L., Carvalho, L. M., ... & Coelho, F. C. (2024). Mosqlimate: a platform to providing automatable access to data and forecasting models for arbovirus disease. arXiv preprint arXiv:2410.18945. https://arxiv.org/abs/2410.18945.

Bastos, M. M., Carvalho, L. M., Araujo, E. C., & Coelho, F. C. (2024). Long-term predictive models for mosquito borne diseases: a narrative review. arXiv preprint arXiv:2411.13680. https://doi.org/10.48550/arXiv.2411.13680.

2025

Araujo, E. C., Carvalho, L. M., Ganem, F., Vacaro, L. B., Bastos, L. S., Freitas, L. P., ... & Coelho, F. C. (2025). Leveraging probabilistic forecasts for dengue preparedness and control: the 2024 Dengue Forecasting Sprint in Brazil. medRxiv, 2025-05. https://www.medrxiv.org/content/10.1101/2025.05.12.25327419v1.

Picinini Freitas, L., Ferreira, D. A. D. C., Martins Lana, R., Câmara, D. C. P., Portella, T. P., Carvalho, M. S., ... & Bastos, L. S. (2025). A statistical model for forecasting probabilistic epidemic bands for dengue cases in Brazil. medRxiv, 2025-06. https://www.medrxiv.org/content/10.1101/2025.06.12.25329525v1.

Theses and dissertations

2024

Santos, J. P. S. dos. (2024). Analyzing dengue epidemic dynamics using physics informed neural networks [Doctoral dissertation, Fundação Getulio Vargas]. Fundação Getulio Vargas EMAp. https://emap.fgv.br/en/tese/analyzing-dengue-epidemic-dynamics-using-physics-informed-neural-networks

Datasets

Softwares

Webinars

Seminario Web:Preparing for the 2025 dengue season: insights from predictive models

Seminars

In February 2025, Mosqlimate launched a seminar series held on the first Thursday of every month, featuring various guest speakers presenting their work on modeling.

  • 06/02 - Analyzing Dengue Epidemic Dynamics Using Physics-Informed Neural Networks Julie Souza, Ph.D. (FGV/EMAp)
  • 03/04 - Modelando os mosquitos e a dinâmica da dengue em Foz do Iguaçu - Caio Souza Rauh (Universidade Federal da Bahia)
  • 08/05 - Data-Driven Modelling of Vector-Borne Diseases - Davide Nicola (Universit degli Studi di Torino)
  • 05/06 - Social vulnerability in epidemic mathematical modelling - Megan Naidoo (University of Barcelona)

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