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A targeted vaccination strategy based on dynamic community detection for epidemic networks

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Abstract

Vaccination is a vital strategy to prevent and control the spread of infectious diseases. In this paper, we propose a vaccination strategy that starts with community detection in a dynamic epidemic network, then uses centrality measures to identify spreaders in these communities, who are then targeted for vaccination. By vaccinating the most influential individuals in each community, we aim to achieve a highly vaccinated network that can effectively contain the spread of the disease. To test the effectiveness of the methods, we evaluate them using different evaluation metrics. Our strategy is also highly scalable and adaptable to different epidemic scenarios, making it a promising approach for future epidemic control.

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Acknowledgements

This research is carried out as a part of the project “Plateforme logicielle d’intégration de stratégies d’immunisation contre la pandémie COVID-19” funded by the grant of the Hassan II Academy of Sciences and Technology of Morocco.

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Authors and Affiliations

  1. LRIT, Faculty of Sciences, Mohammed V University in Rabat, Rabat, Morocco

    Nadia Laasri, Dounia Lotfi & Ahmed Drissi El Maliani

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  1. Nadia Laasri
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  2. Dounia Lotfi
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  3. Ahmed Drissi El Maliani
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All authors participated equally in conducting analyses, drafting sections of the manuscript, editing, and approving the final submitted version.

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Correspondence to Nadia Laasri, Dounia Lotfi or Ahmed Drissi El Maliani.

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Laasri, N., Lotfi, D. & El Maliani, A.D. A targeted vaccination strategy based on dynamic community detection for epidemic networks. Soc. Netw. Anal. Min. 14, 126 (2024). https://doi.org/10.1007/s13278-024-01292-z

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