2020/04/15 by Luís Tarrataca, L. Tarrataca, C. M. Dias +5
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · Mathematics · Medicine · #COVID-19 diagnosis using AI #COVID-19 epidemiological studies #Data Analysis with R #Field (mathematics) #Flattening #cs.LG #cs.SY #eess.SY #q-bio.PE #q-bio.QM #stat.ML
paper · pdf · doi:10.1186/s13362-020-00098-w
arxiv created 2020/04/15 · openalex created_date 2020/04/24 · openalex publication_date 2021/01/06 · arxiv updated 2021/01/08 · openalex updated_date 2026/08/06
The current COVID-19 pandemic is affecting different countries in different ways. The assortment of reporting techniques alongside other issues, such as underreporting and budgetary constraints, makes predicting the spread and lethality of the virus a challenging task. This work attempts to gain a better understanding of how COVID-19 will affect one of the least studied countries, namely Brazil. Currently, several Brazilian states are in a state of lock-down. However, there is political pressure for this type of measures to be lifted. This work considers the impact that such a termination would have on how the virus evolves locally. This was done by extending the SEIR model with an on / off strategy. Given the simplicity of SEIR we also attempted to gain more insight by developing a neural regressor. We chose to employ features that current clinical studies have pinpointed has having a connection to the lethality of COVID-19. We discuss how this data can be processed in order to obtain a robust assessment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13362-020-00098-w.