A generalized SEIRW-VN framework for modeling infectious disease dynamics
Abdoulaye Sow1, Cherif Diallo2, Hocine Cherifi3
1Department of Computer Science, Algebra Laboratory for Cryptography, Codes and Applications, Gaston Berger University, Saint-Louis, Senegal. sow.abdoulaye6@ugb.edu.sn.
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Understanding how infectious diseases spread requires models that integrate both human contact structure and environmental factors. We propose SEIRW-VN, a generalized epidemic framework that combines network heterogeneity, indirect transmission via environmental reservoirs, and vaccination. Using COVID-19 data from several European countries, the model outperforms classical homogeneous approaches, capturing more realistic epidemic peaks and timing. Our simulations reveal that highly connected individuals disproportionately sustain outbreaks, while environmental transmission can account for up to one quarter of infections, prolonging epidemic duration. Intervention analysis shows that non-pharmaceutical measures delay peaks and vaccination reduces long-term incidence, but only their combination yields strong synergistic effects, lowering both peak size and overall burden. These findings highlight the importance of integrating contact structure, environmental persistence, and vaccination into epidemic models to design robust and effective public health strategies.
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