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Authors
# Name
1 RAMON ADRIAN FRANCO(radrian20@gmail.com)
2 Pedro Moreira(pedrovxm@gmail.com)
3 Janaina Guiginski(,janainaguiginski@gmail.com)
4 Ana Paula da Silva(ana.coutosilva@dcc.ufmg.br)
5 Evandro Cunha(cunhae@ufmg.br )
6 Pedro Alzamora (ploures.alzamora@gmail.com)
7 Wagner Meira Jr.(meira@dcc.ufmg.br)

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Reference
# Reference
1 Aiello, A. E., Renson, A., and Zivich, P. N. (2020). Social media– and internet-based isease surveillance for public health. Annual Review of Public Health, 41(1):101– 118. PMID: 31905322.
2 Bastos, S. B. and Cajueiro, D. O. (2020). Modeling and forecasting the early evolution of the Covid-19 pandemic in Brazil. Scientific Reports, 10(1):1–10.
3 Du, J., Xu, J., Song, H., Liu, X., and Tao, C. (2017). Optimization on machine learning based approaches for sentiment analysis on hpv vaccines related tweets. Journal of biomedical semantics, 8(1):1–7.
4 Gomide, J., Veloso, A., Meira, W., Almeida, V., Benevenuto, F., Ferraz, F., and Teixeira, M. (2011). Dengue surveillance based on a computational model of spatio-temporal locality of twitter. In Proceedings of the 3rd International Web Science Conference, WebSci ’11, New York, NY, USA. Association for Computing Machinery.
5 Kang, G. J., Ewing-Nelson, S. R., Mackey, L., Schlitt, J. T., Marathe, A., Abbas, K. M., and Swarup, S. (2017). Semantic network analysis of vaccine sentiment in online social media. Vaccine, 35(29):3621–3638.
6 Li, C., Chen, L. J., Chen, X., Zhang, M., Pang, C. P., and Chen, H. (2020). Retrospective analysis of the possibility of predicting the covid-19 outbreak from internet searches and social media data, china, 2020. Eurosurveillance, 25(10).
7 Marques-Toledo, C. d. A., Degener, C. M., Vinhal, L., Coelho, G., Meira, W., Codec¸o, C. T., and Teixeira, M. M. (2017). Dengue prediction by the web: Tweets are a useful tool for estimating and forecasting dengue at country and city level. PLoS neglected tropical diseases, 11(7):e0005729.
8 Moreira, P. V. X., Franco, R. A. S., Fonseca, R. M., Prado, A. C. T., Leal, L., Mendes, G. N., and Rezende, T. A. V. (2021). Covid Data Analytics: Repositorio de ´Dados Provenientes de Multiplas Fontes sobre a Pandemia de COVID-19 no Brasil https://doi.org/10.5281/zenodo.5176798. Zenodo.
9 Peixoto, P. S., Marcondes, D., Peixoto, C., and Oliva, S. M. (2020). Modeling future spread of infections via mobile geolocation data and population dynamics. an application to COVID-19 in Brazil. PloS one, 15(7):e0235732.
10 Pereira, I. G., Guerin, J. M., Silva Junior, A. G., Garcia, G. S., Piscitelli, P., Miani, A., ´Distante, C., and Gonc¸alves, L. M. G. (2020). Forecasting Covid-19 dynamics in Brazil: a data driven approach. International Journal of Environmental Research and Public Health, 17(14):5115.
11 Ranzani, O. T., Bastos, L. S., Gelli, J. G. M., Marchesi, J. F., Baiao, F., Hamacher, S., and Bozza, F. A. (2021). Characterisation of the first 250 000 hospital admissions for COVID-19 in Brazil: a retrospective analysis of nationwide data. The Lancet Respiratory Medicine, 9(4):407–418.
12 Rey S. J., Arribas-Bel D., W. L. J. (2020). Geographic data science with pysal and the pydata stack.
13 Sultana, A., Tasnim, S., Hossain, M. M., Bhattacharya, S., and Purohit, N. (2021). Digital screen time during the covid-19 pandemic: a public health concern. F1000Research, 10(81):81.
14 Veiga e Silva, L., de Andrade Abi Harb, M. D. P., Dos Santos, A. M. T. B., de Mattos Teixeira, C. A., Gomes, V. H. M., Cardoso, E. H. S., da Silva, M. S., Vijaykumar, N., Carvalho, S. V., Frances, C. R. L., et al. (2020). COVID-19 mortality underreporting in Brazil: analysis of data from government internet portals. Journal of medical Internet research, 22(8):e21413.