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Predicting the Geographic Spread of the COVID-19 Pandemic: A Case Study from Brazil
Marques,Joao Alexandre Lobo1; Gois,Francisco Nauber Bernardo2; Xavier-Neto,José3; Fong,Simon James4
2021
Source PublicationSpringerBriefs in Applied Sciences and Technology
Pages89-98
AbstractThe support provided by geographic data and the corresponding processing tools can play an essential role to support decision-making process, especially for public healthcare during the current pandemic outbreak of the COVID-19. Geographic data collection may be challenging when is necessary to obtain precise latitude and longitude, for example. The current chapter presents a new tool for the geographic location prediction of new cases of COVID-19, considering the confirmed cases in the city of Fortaleza, capital of the State of Ceara, Brazil. The methodology is based on a sequential approach of four clustering algorithms: Agglomerative Clustering, DBSCAN, Mean Shift, and K-Means followed by a two-dimensional predictor based on the Kalman filter. The results are presented following a case study approach with different examples of implementation and the corresponding analysis of the results. The proposed technique could generally predict the trend of the infection geographically in Fortaleza and effectively supported the decision-making process of public healthcare analysts and managers from the Secretariat of Health of the State of Ceara.
DOI10.1007/978-3-030-61913-8_6
URLView the original
Language英语
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Document TypeBook chapter
CollectionUniversity of Macau
Corresponding AuthorMarques,Joao Alexandre Lobo
Affiliation1.Laboratory of Neuroapplications,University of Saint Joseph,Macao
2.Machine Learning Department,Secretary of Health of the Government of the State of Ceara,Fortaleza,Brazil
3.Government Intelligence Cell,Secretary of Health of the Government of the State of Ceara,Fortaleza,Brazil
4.Department of Computer and Information Science,University of Macau,Macao
Recommended Citation
GB/T 7714
Marques,Joao Alexandre Lobo,Gois,Francisco Nauber Bernardo,Xavier-Neto,José,et al. Predicting the Geographic Spread of the COVID-19 Pandemic: A Case Study from Brazil,2021:89-98.
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