Examinando por Materia "Basic reproduction number"

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    Ítem
    Disease transmission dynamics according to complexity theory
    (Universidad Nacional de Colombia, 2013-01-01) Hincapie-Palacio, D.; Ospina-Giraldo, J.F.; Hincapie-Palacio, D.; Ospina-Giraldo, J.F.; Universidad EAFIT. Departamento de Ciencias; Lógica y Computación
    Objective: Illustrating disease transmission as a complex system according to complexity theory. Methods: A SIR mathematical model (S=number susceptible, I=number infectious, and R=number recovered or immune) reflecting disease transmission from the connection between states of susceptibility, infection, disease, recovery and non-linearity in the interaction between susceptible and infected was simulated. Infection rate temporal fluctuations were described by logistic mapping. Results: Transmission occurs with the reduction of susceptible states as people become infected and sick, followed by an increase in individuals' recovery following diagnosis and treatment. Small increases in infection rate value led to fluctuations in the number of susceptible and exposed people and randomness in the relationship between being susceptible and infected, until converging towards a regular pattern. Conclusion: The model reflected the connection between states of susceptibility, nonlinearity and chaotic behavior following small increases in infection rate. A historical and trans-disciplinary perspective could help in understanding transmission complexity and coordinating control options.
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    Epidemic thresholds in SIR and SIIR models applying an algorithmic method
    (SPRINGER, 2008-01-01) Hincapié P., D.; Ospina G., J.; Afuwape, A.U.; Gómez A., R.D.; Hincapié P., D.; Ospina G., J.; Afuwape, A.U.; Gómez A., R.D.; Universidad EAFIT. Departamento de Ciencias; Lógica y Computación
    Epidemic thresholds were deduced and simulated from SIR models of Susceptible - Infected - Recovered individuals, through local stability analysis of the disease free and endemic equilibrium, with an algorithmic method. One and two types of infected individuals were modeled, considering the influence of sub clinical, undiagnosed or unrecognized infected cases in disease transmission. © 2008 Springer Berlin Heidelberg.