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Can treatment increase the epidemic size?

机译:治疗可以增加流行病的规模吗?

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Antiviral treatment is one of the key pharmacological interventions against many infectious diseases. This is particularly important in the absence of preventive measures such as vaccination. However, the evolution of drug-resistance in treated patients and its subsequent spread to the population pose significant impediments to the containment of disease epidemics using treatment. Previous models of population dynamics of influenza infection have shown that in the presence of drug-resistance, the epidemic final size (i.e., the total number of infections throughout the epidemic) is affected by the treatment rate. These models, through simulation experiments, illustrate the existence of an optimal treatment rate, not necessarily the highest possible rate, for minimizing the epidemic final size. However, the conditions for the existence of such an optimal treatment rate have never been found. Here, we provide these conditions for a class of models covered in the literature previously, and investigate the combination effect of treatment and transmissibility of the drug-resistant pathogen strain on the epidemic final size. For the first time, we obtain the final size relations for an epidemic model with two strains of a pathogen (i.e., drug-sensitive and drug-resistant). We also discuss this model with specific functional forms of de novo resistance emergence, and illustrate the theoretical findings with numerical simulations.
机译:抗病毒治疗是针对许多传染病的关键药物干预措施之一。在没有预防措施如疫苗接种的情况下,这一点尤其重要。然而,在治疗的患者中耐药性的演变及其随后向人群的传播严重阻碍了使用治疗来控制疾病的流行。以前流行性感冒感染的人口动态模型表明,在存在耐药性的情况下,流行的最终规模(即整个流行中的感染总数)受治疗率的影响。这些模型通过模拟实验说明了最佳的治疗率(不一定是最高的治疗率)的存在,以使流行病的最终规模最小化。然而,从未发现存在这种最佳治疗率的条件。在这里,我们为先前文献中涵盖的一类模型提供了这些条件,并研究了耐药性病原体菌株的治疗和传播性对流行最终规模的综合影响。我们首次获得了具有两种病原体菌株(即药物敏感性和抗药性)的流行模型的最终尺寸关系。我们还讨论了从头出现抗药性的特定功能形式的该模型,并通过数值模拟说明了理论发现。

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