Peta Penelitian SEIRS-Vaksin COVID-19: Analisis Tren, Temuan, dan Tantangan Model Matematika - Fauzan, Muhamad Fahri; Ramadhani, Alya; Maywanti, Dara; Fahmi, Aban Subanul; Sukmaangara, Bayu (Perspectives in Mathematics and Applications, 2025)
The control of the COVID-19 pandemic requires mathematical models that are able to accommodate complex immune dynamics, especially waning immunity phenomena and vaccination interventions. This study conducted a Systematic Literature Review using the PRISMA protocol to map trends, findings, and methodological challenges in SEIRS-Vaccination modeling. Of the 80 articles identified in the initial stage, 56 articles met the inclusion criteria and were analyzed. Furthermore, 11 articles were selected through purposive sampling techniques as representative samples for in-depth comparative analysis of five main methodology categories: Deterministic (ODE), Optimal Control, Fractional Order, Data Assimilation/Stochastic, and Spatial. The results of the literature synthesis reveal a significant paradigm shift from classical deterministic models that focused on stability analysis  static towards a more adaptive model. Specifically, this study identifies the use of the Ensemble Kalman Filter for estimation of dynamic parameters and Optimal Control Theory for resource allocation strategies as the dominant methodological trends. The model's findings consistently validate that vaccination rate is the most sensitive intervention parameter, but its long-term effectiveness is highly dependent on the duration of immunity. The study concludes the need to develop a hybrid model that integrates stochastic approaches and optimal control to generate more precise policy recommendations in the future.