Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, Connecticut.
Department of Health Policy and Management, Yale School of Public Health, Yale University, New Haven, Connecticut.
Clin Infect Dis. 2019 Mar 7;68(Suppl 2):S96-S104. doi: 10.1093/cid/ciy1108.
Empiric prescribing of antimicrobials in typhoid-endemic settings has increased selective pressure on the development of antimicrobial-resistant Salmonella enterica serovar Typhi. The introduction of typhoid conjugate vaccines (TCVs) in these settings may relieve this selective pressure, thereby reducing resistant infections and improving health outcomes.
A deterministic transmission dynamic model was developed to simulate the impact of TCVs on the number and proportion of antimicrobial-resistant typhoid infections and chronic carriers. One-way sensitivity analyses were performed to ascertain particularly impactful model parameters influencing the proportion of antimicrobial-resistant infections and the proportion of cases averted over 10 years.
The model simulations suggested that increasing vaccination coverage would decrease the total number of antimicrobial-resistant typhoid infections but not affect the proportion of cases that were antimicrobial resistant. In the base-case scenario with 80% vaccination coverage, 35% of all typhoid infections were antimicrobial resistant, and 44% of the total cases were averted over 10 years by vaccination. Vaccination also decreased both the total number and proportion of chronic carriers of antimicrobial-resistant infections. The prevalence of chronic carriers, recovery rates from infection, and relative fitness of resistant strains were identified as crucially important parameters.
Model predictions for the proportion of antimicrobial resistant infections and number of cases averted depended strongly on the relative fitness of the resistant strain(s), prevalence of chronic carriers, and rates of recovery without treatment. Further elucidation of these parameter values in real-world typhoid-endemic settings will improve model predictions and assist in targeting future vaccination campaigns and treatment strategies.
在伤寒流行地区，经验性使用抗生素会对沙门氏菌 Typhi 血清型的抗生素耐药性产生选择压力。在这些地区引入伤寒结合疫苗（TCV）可能会减轻这种选择压力，从而减少耐药感染并改善健康结果。
开发了一种确定性传播动力学模型，以模拟 TCV 对耐抗生素伤寒感染和慢性携带者数量和比例的影响。进行了单因素敏感性分析，以确定对耐药感染比例和 10 年内可预防病例比例有重大影响的模型参数。
模型模拟表明，增加疫苗接种覆盖率将减少耐抗生素伤寒感染的总数，但不会影响耐药病例的比例。在 80%疫苗接种覆盖率的基本情况下，所有伤寒感染中有 35%是耐抗生素的，接种疫苗可在 10 年内预防 44%的病例。疫苗接种还减少了耐抗生素感染的慢性携带者的总数和比例。慢性携带者的流行率、从感染中恢复的速度以及耐药菌株的相对适应性被确定为至关重要的参数。
对耐药感染比例和可预防病例数的模型预测强烈依赖于耐药菌株的相对适应性、慢性携带者的流行率以及未经治疗的恢复速度。在真实的伤寒流行地区进一步阐明这些参数值将提高模型预测能力，并有助于确定未来的疫苗接种运动和治疗策略。
