Towards Efficient Disinfection in Heterogeneous Bacterial Populations: Model-Based Multi-Objective Optimisation of Dosing Strategies

Abstract

Periodic disinfection is a fundamental practice in clinical, industrial, and environmental hygiene to limit pathogen transmission. These protocols create dynamic selective pressures by alternating phases of disinfectant exposure and bacterial regrowth, potentially promoting resistance and tolerance. The persistence of compounds such as benzalkonium chloride in treated environments, along with suboptimal concentrations, may favour adaptive populations while increasing environmental and economic costs, underscoring the need for more efficient dosing strategies. This work presents a model-based multi-objective optimisation approach to design  disinfectant protocols that minimise bacterial populations while reducing both maximum and total disinfectant use. The approach accounts for competitive dynamics between a wild-type bacterial strain and a mutant with increased disinfection survival at the expense of reduced growth, enabling comparison of optimal dosing strategies depending on the duration of growth periods. By identifying trade-offs and conditions driving bacterial selection or eradication, our approach provides a systematic basis for efficient disinfection strategies that balance efficacy with lower environmental and economic impact.