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J. Verdasca

Publications and source records attributed to J. Verdasca.

2 recordsLinked to original sources

Short and Long-Term Dynamics of Childhood Diseases on Dynamic Small-World Networks

We have performed individual-based lattice simulations of SIR and SEIR dynamics to investigate both the short and long-term dynamics of childhood epidemics. In our model, infection takes place through a combination of local and long-range contacts, in practice generating a dynamic small-world network. Sustained oscillations emerge with a period much larger than the duration of infection. We found that the network topology has a strong impact on the amplitude of oscillations and in the level of persistence. Diseases do not spread very effectively through local contacts. This can be seen by measuring an {\em effective} transmission rate $β_{\mbox {\scriptsize eff}}$ as well as the basic reproductive rate $R_0$. These quantities are lower in the small-world network than in an homogeneously mixed population, whereas the average age at infection is higher.

q-bio.PE

Recurrent epidemics in small world networks

The effect of spatial correlations on the spread of infectious diseases was investigated using a stochastic SIR (Susceptible-Infective-Recovered) model on complex networks. It was found that in addition to the reduction of the effective transmission rate, through the screening of infectives, spatial correlations may have another major effect through the enhancement of stochastic fluctuations. As a consequence large populations will have to become even larger to 'average out' significant differences from the solution of deterministic models. Furthermore, time series of the (unforced) model provide patterns of recurrent epidemics with slightly irregular periods and realistic amplitudes, suggesting that stochastic models together with complex networks of contacts may be sufficient to describe the long term dynamics of some diseases. The spatial effects were analysed quantitatively by modelling measles and pertussis, using a SEIR (Susceptible-Exposed-Infective-Recovered) model. Both the period and the spatial coherence of the epidemic peaks of pertussis are well described by the unforced model for realistic values of the parameters.

q-bio.PE