| Full text | |
| Author(s): |
Total Authors: 2
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| Affiliation: | [1] Univ Nove Julho, Informat & Knowledge Management Grad Program, Rua Vergueiro 235-249, BR-01504000 Sao Paulo, SP - Brazil
Total Affiliations: 1
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| Document type: | Journal article |
| Source: | Applied Mathematics and Computation; v. 353, p. 265-273, JUL 15 2019. |
| Web of Science Citations: | 4 |
| Abstract | |
Epidemiological modeling usually relies on contact between two individuals as the method for a contagious infection spread over the population. Although for some diseases the contact is indeed between only two individuals (HIV), many contagious diseases are favored to spread inside a group of individuals. For instance, consider flu: usually infected persons spread the disease on public transport, inside a room in their jobs or their homes. All these situations are related to groups of individuals that may get a disease due to the presence of an infected individual in the group. Here we use a population model structured by groups, where individuals move inside a neighborhood forming groups, where the disease may be transmitted. The population model is based on evolutionary graph theory and modeled by probabilistic cellular automata, and the disease is modeled by the classical SIR-model. A mean-field approach is presented in terms of ordinary differential equations, and population parameters are used to analyze the disease dynamic. The major results of this paper are: (1) the number of groups that an individual belongs and the lattice temperature can estimate the disease spread strength inside the population and; (2) when infected individuals do not move, this is not enough to control the disease spreading. (C) 2019 Elsevier Inc. All rights reserved. (AU) | |
| FAPESP's process: | 17/12671-8 - Laboratory of populational dynamics |
| Grantee: | Pedro Henrique Triguis Schimit |
| Support Opportunities: | Regular Research Grants |