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9th World Conference on Information Systems and Technologies

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Data Science Procedures To Aggregate Unstructured Disease Data In Georeferenced Spreading Analysis

The importance of analyzing data on public health, especially on notifications of disease cases, can play an important role in the overall improvement of the framework for combating epidemics. This type of study proved to be extremely impactful during the COVID-19 pandemic, which demanded rapid and specific actions for the management of different geographic regions. This work presents the design and results of a system that has made possible analyzes of this nature even in contexts of scarcity of structured and even georeferenced data. It is hoped that the work will be an inspiration for new, more comprehensive initiatives, without implying that health professionals have an advanced command of the techniques and technologies that form the basis of the platform, easily integrating with existing processes and adding value. The result was the generation of a structured and aggregated database on COVID-19 in the city of Brasilia, Federal District, capital of Brazil. If these data previously provided only information about the disease situation, with the platform, they now provide a basis for complex epidemiological analyzes and even spreading animations.

Lucas Coelho de Almeida
University of Brasília - UnB
Brazil

Daniel Silva do Prado
University of Brasília - UnB
Brazil

Natália Andrade Marques
University of Brasília - UnB
Brazil

Francisco Lopes de Caldas Filho
University of Brasília - UnB
Brazil

Lucas Mauricio Castro e Martins
University of Brasília - UnB
Brazil

Rafael Timóteo de Sousa Júnior
University of Brasília - UnB
Brazil

 


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