Moghadas Seyed M
Department of Mathematics and Statistics, The University of Winnipeg, Winnipeg, Manitoba, Canada.
Proc Biol Sci. 2008 May 22;275(1639):1163-9. doi: 10.1098/rspb.2008.0016.
The rise of drug resistance remains a major impediment to the treatment of some diseases caused by fast-evolving pathogens that undergo genetic mutations. Models describing the within-host infectious dynamics suggest that the resistance is unlikely to emerge if the pathogen-specific immune responses are maintained above a certain threshold during therapy. However, emergence of resistance in the population involves both within-host and between-host infection mechanisms. Here, we employ a mathematical model to identify an effective treatment strategy for the management of drug resistance in the population. We show that, in the absence of pre-existing immunity, the population-wide spread of drug-resistant pathogen strains can be averted if a sizable portion of susceptible hosts is depleted before drugs are used on a large scale. The findings, based on simulations for influenza infection as a case study, suggest that the initial prevalence of the drug-sensitive strain under low pressure of drugs, followed by a timely implementation of intensive treatment, can minimize the total number of infections while preventing outbreaks of drug-resistant infections.
耐药性的出现仍然是治疗某些由经历基因突变的快速进化病原体引起的疾病的主要障碍。描述宿主体内感染动态的模型表明,如果在治疗期间病原体特异性免疫反应维持在一定阈值以上,耐药性不太可能出现。然而,群体中耐药性的出现涉及宿主体内和宿主间的感染机制。在此,我们采用一个数学模型来确定一种有效的治疗策略,以控制群体中的耐药性。我们表明,在没有预先存在的免疫力的情况下,如果在大规模使用药物之前使相当一部分易感宿主减少,耐药病原体菌株在群体中的广泛传播是可以避免的。基于作为案例研究的流感感染模拟结果表明,在低药物压力下药物敏感菌株的初始流行率,随后及时实施强化治疗,可以在防止耐药感染爆发的同时将感染总数降至最低。