SEIR model on Watts-Strogatz networks exhibits exponential infected growth if latency time is less than infection time and oscillatory dynamics otherwise.
Dynamics of disease spread. Effect of the characteristic times
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abstract
Dynamic properties of spreading infection through a heterogeneous population are studied numerically and analytically using a dynamic variant of Watts and Strogatz Small World Network-based stochastic Susceptible-Exposed-Infectious-Removed (SEIR) epidemic model. This model includes the main realistic parameters usually characterizing transmissible diseases, such as the force of infection, latency and infection times. As far as the latency time remains smaller than that of infection, the proportion of infected individuals increases exponentially with time, otherwise an oscillatory behavior appears. This may explain the periodic behaviors in time observed by the health prevention services. It is also shown that periodic epidemiological surveys overestimate or underestimate the dynamics of infection if the survey periods do not exactly correspond to the characteristic times of the infection. Further discussion is provided on the diffusion and relaxation processes involved in this model, and their relation to the infection characteristic time.
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q-bio.PE 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
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Dynamics of disease spread. Effect of the characteristic times
SEIR model on Watts-Strogatz networks exhibits exponential infected growth if latency time is less than infection time and oscillatory dynamics otherwise.