TY - JOUR
T1 - Modeling epidemics dynamics on heterogenous networks
AU - Ben-Zion, Yossi
AU - Cohen, Yahel
AU - Shnerb, Nadav M.
PY - 2010/5/21
Y1 - 2010/5/21
N2 - The dynamics of the SIS process on heterogenous networks, where different local communities are connected by airlines, is studied. We suggest a new modeling technique for travelers movement, in which the movement does not affect the demographic parameters characterizing the metapopulation. A solution to the deterministic reaction-diffusion equations that emerges from this model on a general network is presented. A typical example of a heterogenous network, the star structure, is studied in detail both analytically and using agent-based simulations. The interplay between demographic stochasticity, spatial heterogeneity and the infection dynamics is shown to produce some counterintuitive effects. In particular it was found that, while movement always increases the chance of an outbreak, it may decrease the steady-state fraction of sick individuals. The importance of the modeling technique in estimating the outcomes of a vaccination campaign is demonstrated.
AB - The dynamics of the SIS process on heterogenous networks, where different local communities are connected by airlines, is studied. We suggest a new modeling technique for travelers movement, in which the movement does not affect the demographic parameters characterizing the metapopulation. A solution to the deterministic reaction-diffusion equations that emerges from this model on a general network is presented. A typical example of a heterogenous network, the star structure, is studied in detail both analytically and using agent-based simulations. The interplay between demographic stochasticity, spatial heterogeneity and the infection dynamics is shown to produce some counterintuitive effects. In particular it was found that, while movement always increases the chance of an outbreak, it may decrease the steady-state fraction of sick individuals. The importance of the modeling technique in estimating the outcomes of a vaccination campaign is demonstrated.
KW - Disease models
KW - Dispersal
KW - Individual-based models
KW - Population dynamics
KW - Star network
KW - Stochasticity
UR - http://www.scopus.com/inward/record.url?scp=77951652611&partnerID=8YFLogxK
U2 - 10.1016/j.jtbi.2010.01.029
DO - 10.1016/j.jtbi.2010.01.029
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C2 - 20117115
AN - SCOPUS:77951652611
SN - 0022-5193
VL - 264
SP - 197
EP - 204
JO - Journal of Theoretical Biology
JF - Journal of Theoretical Biology
IS - 2
ER -