Robust Evaluation of Vaccination Strategies under Epidemiological and Logistical Uncertainty

Boyuan Zhu

Simen Owen Academic Proceedings Series, 2026, vol. 3, 61-71

Abstract: Infectious disease outbreaks present persistent challenges for public health policy, particularly when key factors such as transmission intensity, vaccine efficacy, and rollout logistics are uncertain. This study develops a stochastic Susceptible-Infectious-Recovered (SIR) framework to conduct a robust evaluation of vaccination strategies under joint epidemiological and logistical uncertainty. Randomness is incorporated into transmission, recovery, and vaccine uptake processes, enabling the model to reflect the variability of real-world epidemic dynamics. Monte Carlo simulations are performed to compare fixed-rate, phased, and threshold-triggered vaccination strategies across a wide range of plausible outbreak scenarios. Sensitivity analysis highlights the dominant influence of transmission rate and vaccine efficacy on epidemic outcomes, while a cost-effectiveness framework balances epidemiological benefits against resource constraints. Results indicate that adaptive, threshold-triggered vaccination strategies consistently reduce worst-case epidemic peaks and improve resilience under uncertainty. These findings provide actionable guidance for policymakers seeking robust, resource-efficient interventions in rapidly evolving epidemic contexts.

Keywords: stochastic SIR model; vaccination strategies; epidemiological uncertainty; logistical uncertainty; cost-effectiveness (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:axf:soapsa:v:3:y:2026:i::p:61-71

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