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Disease spreading on populations structured by groups

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  • Ramos, A.B.M.
  • Schimit, P.H.T.

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.

Suggested Citation

  • Ramos, A.B.M. & Schimit, P.H.T., 2019. "Disease spreading on populations structured by groups," Applied Mathematics and Computation, Elsevier, vol. 353(C), pages 265-273.
  • Handle: RePEc:eee:apmaco:v:353:y:2019:i:c:p:265-273
    DOI: 10.1016/j.amc.2019.01.055
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    References listed on IDEAS

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    1. Cristopher Moore & M. E. J. Newman, 2000. "Epidemics and Percolation in Small-World Networks," Working Papers 00-01-002, Santa Fe Institute.
    2. Erez Lieberman & Christoph Hauert & Martin A. Nowak, 2005. "Evolutionary dynamics on graphs," Nature, Nature, vol. 433(7023), pages 312-316, January.
    3. Ilnytskyi, Jaroslav & Kozitsky, Yuri & Ilnytskyi, Hryhoriy & Haiduchok, Olena, 2016. "Stationary states and spatial patterning in an SIS epidemiology model with implicit mobility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 36-45.
    4. Schimit, P.H.T. & Monteiro, L.H.A., 2009. "On the basic reproduction number and the topological properties of the contact network: An epidemiological study in mainly locally connected cellular automata," Ecological Modelling, Elsevier, vol. 220(7), pages 1034-1042.
    5. Ahmed, E. & Agiza, H.N., 1998. "On modeling epidemics Including latency, incubation and variable susceptibility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 253(1), pages 347-352.
    6. Schimit, P.H.T. & Monteiro, L.H.A., 2010. "Who should wear mask against airborne infections? Altering the contact network for controlling the spread of contagious diseases," Ecological Modelling, Elsevier, vol. 221(9), pages 1329-1332.
    7. Monteiro, L.H.A. & Sasso, J.B. & Chaui Berlinck, J.G., 2007. "Continuous and discrete approaches to the epidemiology of viral spreading in populations taking into account the delay of incubation time," Ecological Modelling, Elsevier, vol. 201(3), pages 553-557.
    8. Joël Mossong & Niel Hens & Mark Jit & Philippe Beutels & Kari Auranen & Rafael Mikolajczyk & Marco Massari & Stefania Salmaso & Gianpaolo Scalia Tomba & Jacco Wallinga & Janneke Heijne & Malgorzata Sa, 2008. "Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases," PLOS Medicine, Public Library of Science, vol. 5(3), pages 1-1, March.
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