Comparative analysis of control interventions: survival analysis and individual-level SIR model approach

Bidah Sara, Chayoukh Oussama, Kadi Marouane, Boutayeb Hamza, Zakary Omar

Abstract


This study introduces a novel approach to assess the effectiveness of two distinct control strategies, utilizing non-pharmaceutical interventions and treatment measures as exemplars. Focused on understanding infectious disease dynamics within closely-interacting communities such as the Hajj pilgrimage or summer camps, meticulous surveillance is employed to monitor infection, recovery, and vulnerability rates. Leveraging this data, a mathematical model is calibrated to precisely estimate parameters. Through numerical simulations, the impact of the two control strategies is evaluated. Results demonstrate significant reductions in infection rates with both approaches, with treatment measures exhibiting a more pronounced effect. Survival analysis underscores expedited recovery times associated with treatment, indicating its superior efficacy in containing infection spread. Statistical comparisons substantiate the practical significance of treatment interventions in enhancing survival outcomes within the studied groups. Despite inherent assumptions, this study provides valuable insights into the comparative effectiveness of diverse control measures in managing infectious diseases within communal living environments. The proposed approach offers a framework for systematic evaluation and comparison of control strategies, contributing to the development of more effective disease management protocols.

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Published: 2024-04-19

How to Cite this Article:

Bidah Sara, Chayoukh Oussama, Kadi Marouane, Boutayeb Hamza, Zakary Omar, Comparative analysis of control interventions: survival analysis and individual-level SIR model approach, Commun. Math. Biol. Neurosci., 2024 (2024), Article ID 51

Copyright © 2024 Bidah Sara, Chayoukh Oussama, Kadi Marouane, Boutayeb Hamza, Zakary Omar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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