Optimal control modelling of XEC SARS-CoV-2 variant with combined ELIXIR-COVID and ADSAK-COVID therapies

The XEC variant of SARS-CoV-2, first identified in December 2024, exhibits heightened transmissibility and partial vaccine resistance, posing significant public health challenges. We present a nonlinear SEIHRD compartmental model integrating antiviral therapeutics ELIXIR-COVID and ADSAK-COVID, with an optimal control framework to determine dynamic vaccination and treatment strategies that minimize infections, hospitalizations, and deaths under resource constraints. Numerical simulations were calibrated using early outbreak data and epidemiological reports, with parameters drawn from the literature and estimated from analogous variants and regional demographics. Model fitting employed least-squares optimization, ensuring accurate reproduction of epidemic trajectories. Sensitivity analyses assessed robustness to parameter uncertainties. Results demonstrate that combined administration of ELIXIR-COVID and ADSAK-COVID substantially reduces epidemic peaks and mortality, outperforming static or single-intervention strategies. This approach provides a quantitative, contextually adapted decision-support tool for policymakers, facilitating efficient antiviral allocation and vaccination planning, and exemplifies the novel integration of dual-therapy modeling for emerging SARS-CoV-2 variants in resource-limited settings.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-12-11
DOI
https://doi.org/10.1051/smdo/2025030/pdf
Primary Topic
SARS-CoV-2 and COVID-19 Research
Type
article
Field-Weighted Citation Impact
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article

Optimal control modelling of XEC SARS-CoV-2 variant with combined ELIXIR-COVID and ADSAK-COVID therapies

Springer Link (Chiba Institute of Technology)
SARS-CoV-2 and COVID-19 Research
article

Optimal control modelling of XEC SARS-CoV-2 variant with combined ELIXIR-COVID and ADSAK-COVID therapies

article en

Abstract

The XEC variant of SARS-CoV-2, first identified in December 2024, exhibits heightened transmissibility and partial vaccine resistance, posing significant public health challenges. We present a nonlinear SEIHRD compartmental model integrating antiviral therapeutics ELIXIR-COVID and ADSAK-COVID, with an optimal control framework to determine dynamic vaccination and treatment strategies that minimize infections, hospitalizations, and deaths under resource constraints. Numerical simulations were calibrated using early outbreak data and epidemiological reports, with parameters drawn from the literature and estimated from analogous variants and regional demographics. Model fitting employed least-squares optimization, ensuring accurate reproduction of epidemic trajectories. Sensitivity analyses assessed robustness to parameter uncertainties. Results demonstrate that combined administration of ELIXIR-COVID and ADSAK-COVID substantially reduces epidemic peaks and mortality, outperforming static or single-intervention strategies. This approach provides a quantitative, contextually adapted decision-support tool for policymakers, facilitating efficient antiviral allocation and vaccination planning, and exemplifies the novel integration of dual-therapy modeling for emerging SARS-CoV-2 variants in resource-limited settings.

Springer Link (Chiba Institute of Technology)
Good health and well-being
Openalex Percentile: Top 32%
SARS-CoV-2 and COVID-19 Research
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Optimal control modelling of XEC SARS-CoV-2 variant with combined ELIXIR-COVID and ADSAK-COVID therapies · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS