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Selective epidemic vaccination under the performant routing algorithms

Author

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  • Bamaarouf, O.
  • Alweimine, A. Ould Baba
  • Rachadi, A.
  • EZ-Zahraouy, H.

Abstract

Despite the extensive research on traffic dynamics and epidemic spreading, the effect of the routing algorithms strategies on the traffic-driven epidemic spreading has not received an adequate attention. It is well known that more performant routing algorithm strategies are used to overcome the congestion problem. However, our main result shows unexpectedly that these algorithms favor the virus spreading more than the case where the shortest path based algorithm is used. In this work, we studied the virus spreading in a complex network using the efficient path and the global dynamic routing algorithms as compared to shortest path strategy. Some previous studies have tried to modify the routing rules to limit the virus spreading, but at the expense of reducing the traffic transport efficiency. This work proposed a solution to overcome this drawback by using a selective vaccination procedure instead of a random vaccination used often in the literature. We found that the selective vaccination succeeded in eradicating the virus better than a pure random intervention for the performant routing algorithm strategies.

Suggested Citation

  • Bamaarouf, O. & Alweimine, A. Ould Baba & Rachadi, A. & EZ-Zahraouy, H., 2018. "Selective epidemic vaccination under the performant routing algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 209-219.
    • Handle: RePEc:eee:phsmap:v:496:y:2018:i:c:p:209-219
    DOI: 10.1016/j.physa.2017.12.148
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    Cited by:

    1. Chen, Jie & Hu, Mao-Bin & Li, Ming, 2020. "Traffic-driven epidemic spreading dynamics with heterogeneous infection rates," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    2. Chen, Jun-Jie & Hu, Mao-Bin & Wu, Yong-Hong, 2022. "Traffic-driven epidemic spreading with non-uniform origin and destination selection," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    3. Chen, Jie & Tan, Xuegang & Cao, Jinde & Li, Ming, 2022. "Effect of coupling structure on traffic-driven epidemic spreading in interconnected networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).

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