Silent spreaders: optimal control of asymptomatic cholera transmission through adaptive stochastic modeling

Cholera transmission dynamics are complicated by asymptomatic carriers and environmental stochasticity often overlooked in standard models. We develop a novel Susceptible-Asymptomatic-Infected-Treated-Recovered-Bacterial (SAITR-B) model integrating dual adaptive controls—vaccination and symptom-targeted isolation—within a stochastic framework. Numerical simulations of 10,000 outbreak scenarios show environmental noise amplifies outbreak variability by 28–34% and shifts optimal intervention timing by 1.5–3 days compared to deterministic predictions. Combined control strategies reduce peak symptomatic incidence by 66%, outperforming single interventions (41% vaccination-only; 51% isolation-only). Global sensitivity analysis identifies bacterial growth rate ($$\omega$$) as the dominant outbreak driver, while coverage below 60% triggers dangerous resurgence. Environmental interventions yield 30% greater real-world benefit than deterministic models predict. This work provides a validated framework for designing resilient cholera response strategies under uncertainty.