Sensitivity assessment of optimal control strategies and cost-effectiveness analysis of a novel Candida Auris environmental transmission model in intensive care facilities

Candida Auris is an emerging fungal pathogen flagged by CDC as a serious global health threat among nosocomial infections in the recent times. As an evolving pathogen that often goes misidentified or unidentified under standard laboratory tests, it has the ability to cause fatal infections among the target population involving patients with serious medical conditions admitted to intensive care facilities, due to its capacity to resist anti-fungal treatment and the ability to persist in the hospital environment for long periods. The subject of this paper is to develop a deterministic model to study the transmission nature of Candida Auris wherein measures like apt admission screening methods with weekly screening follow-ups, transmission prevention, proper treatment protocols and environmental disinfection procedures are introduced as constant mitigating controls into the model initially which are later redefined as variable control functions during the optimal control analysis. The theory of optimal control implemented into the model helps us to understand the sensitivity of each control strategy upon the behaviour of each state variable. Further, cost-effectiveness analysis is rigorously conducted using incremental cost-effectiveness ratio (ICER) to identify and rank the control strategies involved based on their economic efficiency. Numerical simulation for the optimal control analysis is performed in MATLAB using the Forward–Backward Sweep Method and the findings are illustrated graphically.