Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina; Universidad Tecnológica Nacional, Facultad Regional San Nicolás, San Nicolás, Argentina.
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina; Instituto Multidisciplinario sobre Ecosistemas y Desarrollo Sustentable, Facultad de Cs Exactas, UNICEN, Tandil, Argentina.
Vaccine. 2018 Feb 8;36(7):979-985. doi: 10.1016/j.vaccine.2018.01.007. Epub 2018 Jan 11.
Current recommendations about dengue vaccination by the World Health Organization depend on seroprevalence levels and serological status in populations and individuals. However, seroprevalence estimation may be difficult due to a diversity of factors. Thus, estimation through models using data from epidemiological surveillance systems could be an alternative procedure to achieve this goal.
To estimate the expected dengue seroprevalence in children of selected areas in Argentina, using a simple model based on data from passive epidemiological surveillance systems.
A Markov model using a simulated cohort of individuals from age 0 to 9 years was developed. Parameters regarding the reported annual incidence of dengue, proportion of inapparent cases, and expansion factors for outpatient and hospitalized cases were considered as transition probabilities. The proportion of immune population at 9 years of age was taken as a proxy of the expected seroprevalence, considering this age as targeted for vaccination. The model was used to evaluate the expected seroprevalence in Misiones and Salta provinces and in Buenos Aires city, three settings showing different climatic favorability for dengue.
The estimates of the seroprevalence for the group of 9-year-old children for Misiones was 79% (95%CI:46-100%), and for Salta 22% (95%CI:14-30%), both located in northeastern and northwestern Argentina, respectively. Buenos Aires city, from central Argentina, showed a likely seroprevalence of 7% (95%CI: 3-11%). According to the deterministic sensitivity analyses, the parameter showing the highest influence on these results was the probability of inapparent cases.
This model allowed the estimation of dengue seroprevalence in settings where this information is not available. Particularly for Misiones, the expected seroprevalence was higher than 70% in a wide range of scenarios, thus in this province a vaccination strategy directed to seropositive children of >9 years should be analyzed, including further considerations as safety, cost-effectiveness, and budget impact.
世界卫生组织目前关于登革热疫苗接种的建议取决于人群和个体的血清流行率水平和血清学状态。然而，由于存在多种因素，血清流行率的估计可能会比较困难。因此，使用来自流行病学监测系统的数据通过模型进行估计可能是实现这一目标的替代程序。
使用基于被动流行病学监测系统数据的简单模型，估计阿根廷选定地区儿童的预期登革热血清流行率。
使用从 0 岁到 9 岁个体的模拟队列开发了一个马尔可夫模型。报告的登革热年发病率、隐性病例比例以及门诊和住院病例的扩展因素等参数被视为转移概率。将 9 岁时免疫人群的比例作为预期血清流行率的替代指标，因为该年龄是疫苗接种的目标年龄。该模型用于评估米西奥内斯省和萨尔塔省以及布宜诺斯艾利斯市的预期血清流行率，这三个地区的气候条件对登革热的发生都较为有利。
米西奥内斯组 9 岁儿童的血清流行率估计值为 79%（95%CI：46-100%），萨尔塔为 22%（95%CI：14-30%），这两个地区分别位于阿根廷的东北部和西北部。阿根廷中部的布宜诺斯艾利斯市可能有 7%（95%CI：3-11%）的血清流行率。根据确定性敏感性分析，对这些结果影响最大的参数是隐性病例的概率。
该模型可以在缺乏此类信息的情况下估计登革热血清流行率。特别是在米西奥内斯，在广泛的情景下，预期的血清流行率都高于 70%，因此应该考虑在该省实施针对血清阳性的>9 岁儿童的疫苗接种策略，同时还需要考虑安全性、成本效益和预算影响等因素。
