| Full text | |
| Author(s): |
Marcilio-Jr, Wilson E.
;
Eler, Danilo M.
[1]
;
Garcia, Rogerio E.
[1]
;
Correia, Ronaldo C. M.
[1]
;
Rodrigues, Rafael M. B.
[1]
Total Authors: 5
|
| Affiliation: | [1] Marcilio-Jr, Jr., Wilson E., Sao Paulo State Univ UNESP, Dept Math & Comp Sci, Presidente Prudente, SP - Brazil
Total Affiliations: 1
|
| Document type: | Journal article |
| Source: | JOURNAL OF BIOMEDICAL INFORMATICS; v. 117, MAY 2021. |
| Web of Science Citations: | 0 |
| Abstract | |
Visual analytics techniques are useful tools to support decision-making and cope with increasing data, particularly to monitor natural or artificial phenomena. When monitoring disease progression, visual analytics approaches help decision-makers to understand or even prevent dissemination paths. In this paper, we propose a new visual analytics tool for monitoring COVID-19 dissemination. We use k-nearest neighbors of cities to mimic neighboring cities and analyze COVID-19 dissemination based on comparing a city under consideration and its neighborhood. Moreover, such analysis is performed within periods, which facilitates the assessment of isolation policies. We validate our tool by analyzing the progression of COVID-19 in neighboring cities of Sao Paulo state, Brazil. (AU) | |
| FAPESP's process: | 18/17881-3 - Multilevel visual representation to assist the exploration of data sets |
| Grantee: | Danilo Medeiros Eler |
| Support Opportunities: | Regular Research Grants |