预测接种疫苗对尼日尔轮状病毒病影响的一种方法
An Ensemble Approach to Predicting the Impact of Vaccination on Rotavirus Disease in Niger
摘要：
最近开发的疫苗为撒哈拉以南非洲地区控制轮状病毒提供了一种新的方法。轮状病毒的传播动力学模型对于评估不完善的监测造成的当前负担和评估疫苗干预策略的潜在影响都至关重要。我们研究轮状病毒感染的马拉迪地区在南部尼日尔使用医院监测数据提供的Epicentre收集了两年。此外，对该地区家庭的聚类调查使我们能够估计在卫生机构咨询的腹泻儿童的比例。模型拟合和未来预测必然是特定于给定模型的;因此，在潜在流行病学存在竞争模型的情况下，集合方法可以解释这种不确定性。我们比较了几种不同的易感-传染性-潜伏期（SIR）房室模型的结果，以量化建模假设对我们估计的影响。使用马尔可夫链蒙特卡罗通过贝叶斯推断估计模型特定参数。然后，我们使用贝叶斯模型平均生成当前动态的总体估计，包括估计$R_0$，该地区的感染负担，以及疫苗接种对短期动态和不同覆盖水平下轮状病毒发病率长期降低的影响。该模型预测，目前严重轮状病毒疾病的负担为每年人口的2.9%至4.1%，实现70%覆盖率的2剂疫苗计划可以将负担降低37%至43%。
英文摘要：
Recently developed vaccines provide a new way of controlling rotavirus in sub-Saharan Africa. Models for the transmission dynamics of rotavirus are critical both for estimating current burden from imperfect surveillance and for assessing potential effects of vaccine intervention strategies. We examine rotavirus infection in the Maradi area in southern Niger using hospital surveillance data provided by Epicentre collected over two years. Additionally, a cluster survey of households in the region allows us to estimate the proportion of children with diarrhea who consulted at a health structure. Model fit and future projections are necessarily particular to a given model; thus, where there are competing models for the underlying epidemiology an ensemble approach can account for that uncertainty. We compare our results across several variants of Susceptible-Infectious-Recovered (SIR) compartmental models to quantify the impact of modeling assumptions on our estimates. Model-specific parameters are estimated by Bayesian inference using Markov chain Monte Carlo. We then use Bayesian model averaging to generate ensemble estimates of the current dynamics, including estimates of $R_0$, the burden of infection in the region, as well as the impact of vaccination on both the short-term dynamics and the long-term reduction of rotavirus incidence under varying levels of coverage. The ensemble of models predicts that the current burden of severe rotavirus disease is 2.9 to 4.1% of the population each year and that a 2-dose vaccine schedule achieving 70% coverage could reduce burden by 37-43%.
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