| Full text | |
| Author(s): |
Rocha, Guilherme Conceicao
[1]
;
Paiva, Henrique Mohallem
[2]
;
Sanches, Davi Goncalves
[2]
;
Fiks, Daniel
[3]
;
Castro, Rafael Martins
[4]
;
Alvarenga e Silva, Lucas Fernando
[2]
Total Authors: 6
|
| Affiliation: | [1] Aeronaut Inst Technol ITA, Dept Mech Engn, Sao Jose Dos Campos - Brazil
[2] Fed Univ Sao Paulo UNIFESP, Inst Sci & Technol ICT, Sao Jose Dos Campos - Brazil
[3] Santa Marcelina Sch Med FASM, Sao Paulo - Brazil
[4] Leonardo da Vinci Univ Uniasselvi, Cuiaba - Brazil
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | LIBRARY HI TECH; v. 39, n. 3, SI, p. 834-854, SEP 13 2021. |
| Web of Science Citations: | 0 |
| Abstract | |
Purpose The SARS-CoV-2 pandemic has caused a major impact on worldwide public health and economics. The lessons learned from the successful attempts to contain the pandemic escalation revealed that the wise usage of contact tracing and information systems can widely help the containment work of any contagious disease. In this context, this paper investigates other researches on this domain, as well as the main issues related to the practical implementation of such systems and specifies a technical solution. Design/methodology/approach The proposed solution is based on the automatic identification of relevant contacts between infected or suspected people with susceptible people; inference of contamination risk based on symptoms history, user navigation records and contact information; real-time georeferenced information of population density of infected or suspect people; and automatic individual social distancing recommendation calculated through the individual contamination risk and the worsening of clinical condition risk. Findings The solution was specified, prototyped and evaluated by potential users and health authorities. The proposed solution has the potential of becoming a reference on how to coordinate the efforts of health authorities and the population on epidemic control. Originality/value This paper proposed an original information system for epidemic control which was applied for the SARS-CoV-2 pandemic and could be easily extended to other epidemics. (AU) | |
| FAPESP's process: | 20/08770-3 - Open set methods based on deep networks for multimedia recognition |
| Grantee: | Lucas Fernando Alvarenga e Silva |
| Support type: | Scholarships in Brazil - Master |
| FAPESP's process: | 19/18294-7 - Interactions of urban resistance, hydrology and public health issues |
| Grantee: | Davi Gonçalves Sanches |
| Support type: | Scholarships in Brazil - Scientific Initiation |