Two observational methods are currently being used to monitor post-deployment vaccine effectiveness: the obvious crude method comparing rate testing positive per head of vaccinated population with that rate per head of unvaccinated population; and the test-negative case control (TNCC) method. The two methods give very different results. We want to know whether either method is reliable. We assume either a homogeneous population or one partitioned into two homogeneous subsets which differ only in their not-directly-observable healthcare-seeking behaviour including probability of getting vaccinated. We first consider uniform independent priors on the probabilities of being hospitalised conditional on subset, vaccination status, and infection status. We simulate from the resulting model and observe the TNCC estimate, the crude estimate, and the Bayesian central 95% confidence interval on vaccine effectiveness represented as log ratio of odds ratios for infection with and without vaccination. With these wide open priors, even when the population is homogeneous, the Bayesian 95% confidence interval typically has a width of nearly 4 nats (55-fold), implying too much uncertainty for the data collected to be of any use in monitoring effectiveness. There do exist some tight priors under which the data is useful: some lead to TNCC being more accurate while with others the crude estimate is more accurate. Thus using only data from those spontaneously choosing to be tested, we find that neither method is reliably better than the other, and indeed that the desired information is not present in this data. We conclude that effective monitoring of vaccine effectiveness and side-effects requires either strong information on the population's behaviour, or ongoing randomised controlled trials (RCTs), rather than just choosing whichever of TNCC and crude estimate gives the result we prefer to find.
翻译:目前,正在使用两种观察方法来监测部署后疫苗的效用:一种是明显的粗略方法,将每头接种疫苗的人口的检测率与每头未接种人口的比例进行比较;另一种是测试负控制病例的方法。两种方法的结果大不相同。我们想知道这两种方法是否可靠。我们假设的是同质人口,一种是分成两个单一的子集,这两类方法只在非直接可观察的寻求保健行为(包括接种疫苗的可能性)上存在差异。我们首先考虑的是,将每头接种疫苗的概率与每头未接种的人群的接种率进行比较的明显粗略方法比较粗略;另一种是,我们模拟的模型,并观察TC的估计数;两种方法,我们模拟的测试结果是:疫苗有效性的模型、粗略的估计以及Bayesian中央95%的95%的置信度间隔,作为传染和没有接种疫苗的概率比率之比率之高。由于这些前两个方法,即使人口是同质的,Bayesian 95%的置信度间隔期一般为近4 nats(55倍),这意味着收集的数据的不确定性太大,有些用于监测是否有效。我们无法进行这种监测。这样选择之前的数据是比较精确的数据,而没有精确地评估。我们使用这种数据,而选择了另一种方法之下的数据是比较精确的数据是比较精确的数据,而没有根据。我们使用。我们使用的方法是更精确地选择了其他数据,而没有比较精确的数据。我们使用。 。在比较精确的数据是比较精确性的数据。在比较精确地选择了。我们选择了。在比较精确的数据,在比较精确的数据,在比较精确的方法是比较精确地选择了。在比较精确地选择了。 。在比较精确地选择了一种方法之下,在比较精确地选择了一种是比较精确性的数据,在比较精确的方法是比较精确地选择了。 。