Publications

Papers (full list)

Book

  1. BASTOS, LEONARDO S.; WILKINSON, R. D. . Análise Estatística de Simuladores. São Paulo: Associação Brasileira de Estatística, 2010. 91p . PDF

Book chapters

  1. Silva, João Flávio Andrade ; IZBICKI, RAFAEL ; BASTOS, LEONARDO S. ; Soares, Guilherme P. . Monitoring Viral Infections in Severe Acute Respiratory Syndrome Patients in Brazil. Contributions to Statistics. 1ed.: Springer Nature Switzerland, 2024, v. , p. 75-80.

  2. Gamerman, Dani ; MAYRINK, V. D. ; BASTOS, LEONARDO S. . Pandemic Data. In: Dani Gamerman; Marcos O. Prates; Thaís Paiva; Vinícius D. Mayrink. (Org.). Building a Platform for Data-Driven Pandemic Prediction From Data Modelling to Visualisation - The CovidLP Project. 1ed.Oxon: Chapman and Hall/CRC, 2022, v. , p. 17-30.

  3. BASTOS, LEONARDO S.; Carvalho, Luiz Max ; GOMES, MARCELO F. C. . Modelling misreported data. In: Dani Gamerman; Marcos O. Prates; Thaís Paiva; Vinícius D. Mayrink. (Org.). Building a Platform for Data-Driven Pandemic Prediction From Data Modelling to Visualisation - The CovidLP Project. 1ed.Oxon: Chapman and Hall/CRC, 2022, v. , p. 113-140.

  4. PONTES, A. L. M. ; CARDOSO, A. M. ; BASTOS, LEONARDO S. ; SANTOS, R. V. . Pandemia de Covid-19 e os Povos Indígenas no Brasil: cenários sociopolíticos e epidemiológicos. In: MATTA, G.C., REGO, S., SOUTO, E.P., and SEGATA, J.. (Org.). Os impactos sociais da Covid-19 no Brasil: populações vulnerabilizadas e respostas à pandemia. 1ed.Rio de Janeiro: Editora Fiocruz, 2021, v. , p. 123-.

  5. CODEÇO, C. T. ; VILLELA, DANIEL A. M. ; COELHO, FLAVIO CODEÇO ; BASTOS, LEONARDO S. ; Carvalho, Luiz Max ; GOMES, MARCELO F. C. ; CRUZ, OSWALDO G ; LANA, RAQUEL M. . Estimativa de risco de espalhamento da Covid-19 no Brasil e avaliação da vulnerabilidade socioeconômica nas microrregiões brasileiras. In: FREITAS, C. M.; BARCELLOS, C.; VILLELA, D. A. M.,. (Org.). Covid-19 no Brasil: cenários epidemiológicos e vigilância em saúde. 1aed.Rio de Janeiro: Editora Fiocruz, 2021, v. , p. 75-84.

  6. LANA, RAQUEL M. ; CODEÇO, C. T. ; SANTOS, R. V. ; CUNHA, B. ; COELHO, FLAVIO C ; CRUZ, OSWALDO G ; CALDAS, A. D. R. ; SOUZA, M. C. ; BASTOS, LEONARDO S. ; PONTES, A. L. M. ; GOMES, MARCELO F. C. ; TAVARES, I. N. ; DAL?ASTA, A. P. ; RORATO, A. C. ; ESCADA, M. I. S. ; Carvalho, Luiz Max ; VILLELA, DANIEL A. M. ; DAMASCO, F. S. ; CARDOSO, A. M. . Vulnerabilidade das populações indígenas à pandemia de COVID-19 no Brasil e os desafios para o seu monitoramento. In: FREITAS, C. M.; BARCELLOS, C.; VILLELA, D. A. M.,. (Org.). Covid-19 no Brasil: cenários epidemiológicos e vigilância em saúde. 1aed.Rio de Janeiro: Editora Fiocruz, 2021, v. , p. 127-142.

  7. CORTES, J. J. C. ; ALBUQUERQUE, B. C. ; HERKRATH, F. J. ; NAVECA, F. G. ; LUZ, S. L. B. ; LIMA, R. T. S. ; GOMES, MARCELO F. C. ; VILLELA, DANIEL A. M. ; BARCELLOS, CHRISTOVAM ; FREITAS, C. M. ; BASTOS, LEONARDO S. ; PORTELA, M. C. ; FERNANDES, V. R. . Pandemia pelo SARS-CoV-2 no estado do Amazonas. In: FREITAS, C. M.; BARCELLOS, C.; VILLELA, D. A. M.,. (Org.). Covid-19 no Brasil: cenários epidemiológicos e vigilância em saúde. 1aed.Rio de Janeiro: Editora Fiocruz, 2021, v. , p. 143-158.

  8. Carvalho, Luiz Max ; Struchiner, Claudio J. ; BASTOS, LEONARDO S. . Bayesian Inference of Deterministic Population Growth Models. In: Polpo de Campos, A.; Neto, F.L.; Ramos Rifo, L.; Stern, J.M., Lauretto, M.. (Org.). Interdisciplinary Bayesian Statistics: EBEB 2014. 1ed.: Springer International Publishing, 2015, v. 168, p. 217-228.

Packages

  1. Lopes, Rafael et al. (2025) Nowcaster (site; github)

Pre-prints

  1. Freitas, Laís Picinini et al. (2025) A statistical model for forecasting probabilistic epidemic bands for dengue cases in Brazil medrxiv

  2. Rauth, Caio S. et al. Assessing mosquito dynamics and dengue transmission in Foz do Iguaçu, Brazil through an enhanced temperature-dependent mathematical model medrxiv

  3. Koemen, Silas et al. (2025) Fast and Trustworthy Nowcasting of Dengue Fever: A Case Study Using Attention-Based Probabilistic Neural Networks in São Paulo, Brazil medrxiv

  4. Araújo, Eduardo Correa (2025) Leveraging probabilistic forecasts for dengue preparedness and control: the 2024 Dengue Forecasting Sprint in Brazil medrxiv

  5. Lopez Velma K. et al. (2024) A roadmap to account for reporting delays for public health situational awareness – a case study with COVID-19 and dengue in United States jurisdictions medrxiv

  6. Xiao, Yang et al. (2024) Dengue nowcasting in Brazil by combining official surveillance data and Google Trends information medrxiv

  7. Skarstein, Emma et al. (2024) Bayesian models for missing and misclassified variables using integrated nested Laplace approximations. arxiv

  8. Araújo, Eduardo et al. (2024) Large-scale Epidemiological modeling: Scanning for Mosquito-Borne Diseases Spatio-temporal Patterns in Brazil. arxiv

  9. Ganem, Fabiana et al. (2024) Mosqlimate: a platform to providing automatable access to data and forecasting models for arbovirus disease. arxiv

  10. Moreira, Rodrigo et al (2023) Persistent high mortality rates for Diabetes Mellitus and Hypertension after excluding deaths associated with COVID-19 in Brazil, 2020-2022 medrxiv

  11. Sperandei, Sandro et al. (2021) Evaluation of Logistic Regression Applied to Respondent-Driven Samples: Simulated and Real Data arxiv

  12. Mizzi, Giovanni et al. (2021) Faster indicators of dengue fever case counts using Google and Twitter arxiv

  13. Ferreira, Leonardo Souto et al. (2021) Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysis medrxiv

  14. Brizzi, Andrea et al. (2021) Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals medrxiv

  15. Villela, Daniel A.M. et al. (2021) Effectiveness of Mass Vaccination in Brazil against Severe COVID-19 Cases medrxiv

  16. Ayala, Mario J.C. et al. (2021) On multifactorial drivers for malaria rebound in Brazil: a spatio-temporal analysis medrxiv

  17. Coelho, Flávio Codeço et al. (2020) Modeling the Post-Containment Elimination of Transmission of COVID-19 medrxiv

  18. Colón-González, Felipe J. et al. (2020) Probabilistic seasonal dengue forecasting in Vietnam using superensembles medrxiv

  19. Coelho, Flávio Codeço et al. (2020) Assessing the potential impact of COVID-19 in Brazil: Mobility, Morbidity and the burden on the Health Care System medrxiv

  20. Brady, Oliver et al. (2020) The potential cost-effectiveness of controlling dengue in Indonesia using wMel Wolbachia released at scale: a modelling study medrxiv

  21. Bastos, Leonardo S. et al (2018) Fast approaches for Bayesian estimation of size of hard-to-reach populations using Network Scale-up arxiv

  22. Gonçalves, Kelly et al. (2018) Dynamic quantile linear models: a Bayesian approach arxiv

  23. Bastos, Leonardo S. (2017) Modelling reporting delays for disease surveillance data arxiv

  24. Coelho, Flávio Codeço et al. (2016) Sexual transmission causes a marked increase in the incidence of Zika in women in Rio de Janeiro, Brazil. Biorxiv

  25. Codeço, Claudia Torres et al. (2016) InfoDengue: a nowcasting system for the surveillance of dengue fever transmission. Biorxiv

  26. Carvalho, Luiz Max et al. (2015) Combining probability distributions: Extending the logarithmic pooling approach arxiv

  27. Bastos, Leonardo S. et al. (2014) Obtaining adjusted prevalence ratios from logistic regression model in cross-sectional studies arxiv

  28. Bastos et al. (2012) Binary regression analysis with network structure of respondent-driven sampling data. arxiv