ABSTRACT

Controlling antibiotic drug resistance requires understanding extinction and emergence mechanisms of emerging bacteria. Selective pressure from prolonged antibiotic misuse may cause high-level antimicrobial resistance. Self-medication and other socioeconomic factors reduce antibiotic use, accelerating the emergence and extinction of resistant pathogens through stochastic fluctuation. This continuous antibiotic self-medication exposes individuals and communities to antibiotic resistance, especially in low- and lower-middle-income countries, according to current literature. We developed a stochastic drug-resistance model that integrates socio-economic growth and antibiotic use to study extinction and strain establishment in this paper. We analytically derived the extinction threshold using the multi-type branching process and obtained pathogen extinction conditions that match numerical experiments. The model's sensitivity analysis identifies extinction dynamics' key parameters. Our results show that higher income, awareness, and lower antibiotic use may increase the chance of extinction by reducing antibiotic misuse, along with strain transmission potential. These analyses may help public health policymakers combat drug resistance.

摘要

控制抗生素耐药性需要了解新兴细菌的灭绝和出现机制。长期滥用抗生素造成的选择性压力可能会导致高度的抗菌药物耐药性。自我药疗和其他社会经济因素减少了抗生素的使用，通过随机波动加速了耐药病原体的出现和灭绝。根据现有文献，这种持续的抗生素自我治疗使个人和社区面临抗生素耐药性，特别是在低收入和中低收入国家。在本文中，我们开发了一个随机耐药模型，将社会经济增长和抗生素使用结合起来，以研究灭绝和菌株建立。我们利用多类型分支过程分析推导了灭绝阈值，并获得了与数值实验相匹配的病原体灭绝条件。该模型的敏感性分析确定了灭绝动力学的关键参数。我们的研究结果表明，更高的收入、意识和更少的抗生素使用可能会通过减少抗生素滥用以及菌株传播的可能性来增加灭绝的机会。这些分析可能有助于公共卫生政策制定者对抗耐药性。