Análise Exploratória da Malária na Amazônia Brasileira por Meio da Plataforma de Ciência de Dados aplicada à Saúde
Abstract
Malaria is an infectious disease that mainly affects the Legal Amazon. DATASUS includes the Malaria Epidemiological Surveillance Information System. Monitoring this dataset and integrating it with additional data sources, as well as performing proper data preprocessing is crucial to understand the phenomena behind the occurrences and medical care. Therefore, in this paper we make use of the Data Science Platform Applied to Health (PCDaS) as an enabling tool to analyze the evolution of malaria in the Legal Amazon. From its use, we raised research questions that can help in understanding and controlling this disease in Brazil.
References
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Diallo, A., Sié, A., Sirima, S., Sylla, K., Ndiaye, M., Bountogo, M., Ouedraogo, E., Tine, R., Ndiaye, A., Coulibaly, B., and others (2017). An epidemiological study to assess Plasmodium falciparum parasite prevalence and malaria control measures in Burkina Faso and Senegal. Malaria journal, 16(1):63.
Griffing, S. M., Tauil, P. L., Udhayakumar, V., and Silva-Flannery, L. (2015). A historical perspective on malaria control in Brazil. Memórias do Instituto Oswaldo Cruz, 110(6):701–718.
Guerin, P. J., Olliaro, P., Nosten, F., Druilhe, P., Laxminarayan, R., Binka, F., Kilama,W. L., Ford, N., and White, N. J. (2002). Malaria: current status of control, diagnosis, treatment, and a proposed agenda for research and development. The Lancet infectious diseases, 2(9):564–573.
Han, J., Kamber, M., and Pei, J. (2011). Data Mining: Concepts and Techniques. Morgan Kaufmann, Haryana, India; Burlington, MA, 3 edition.
Johansson, E., Selling, K., Nsona, H., Mappin, B., Gething, P., Petzold, M., Peterson, S., and Hildenwall, H. (2016). Integrated paediatric fever management and antibiotic over-treatment in Malawi health facilities: Data mining a national facility census. Malaria Journal, 15(1).
Labbo, R., Fandeur, T., Jeanne, I., Czeher, C., Williams, E., Arzika, I., Soumana, A., Lazoumar, R., and Duchemin, J.-B. (2016). Ecology of urban malaria vectors in Niamey, Republic of Niger. Malaria journal, 15(1):314.
Loucoubar, C., Paul, R., Bar-Hen, A., Huret, A., Tall, A., Sokhna, C., Trape, J.-F., Ly, A., Faye, J., Badiane, A., Diakhaby, G., Sarr, F., Diop, A., Sakuntabhai, A., and Bureau, J.-F. (2011). An exhaustive, non-euclidean, non-parametric data mining tool for Unraveling the complexity of biological systems - novel insights into malaria. PLoS ONE, 6(9).
Recht, J., Siqueira, A. M., Monteiro, W. M., Herrera, S. M., Herrera, S., and Lacerda, M. V. (2017). Malaria in Brazil, Colombia, Peru and Venezuela: current challenges in malaria control and elimination. Malaria journal, 16(1):273.
Sahle, G. and Meshesha, M. (2014). Uncovering knowledge that supports malaria prevention and control intervention program in ethiopia. Electronic Journal of Health Informatics, 8(1).
Sweeney, A., Beebe, N., and Cooper, R. (2007). Analysis of environmental factors influencing the range of anopheline mosquitoes in northern Australia using a genetic algorithm and data mining methods. Ecological Modelling, 203(3-4):375–386.
WHO (2018). World malaria report 2018. World Health Organization.
Wiefels, A., Wolfarth-Couto, B., Filizola, N., Durieux, L., and Mangeas, M. (2016). Accuracy of the malaria epidemiological surveillance system data in the state of Amazonas. Acta Amazonica, 46(4):383–390.
Published
2019-06-24
How to Cite
BARONI, Lais Ribeiro; PAIXÃO, Balthazar; CHRISPINO, Alvaro; GUEDES, Gustavo; BARCELLOS, Christovam; PEDROSO, Marcel; OGASAWARA, Eduardo.
Análise Exploratória da Malária na Amazônia Brasileira por Meio da Plataforma de Ciência de Dados aplicada à Saúde. In: BRAZILIAN E-SCIENCE WORKSHOP (BRESCI), 13. , 2019, Belém.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
ISSN 2763-8774.
DOI: https://doi.org/10.5753/bresci.2019.10025.
