Uses of pathogen detection data to estimate vaccine direct effects in case-control studies

利用病原体检测数据在病例对照研究中估计疫苗的直接效果

阅读:1

Abstract

The fact that many pathogens can be carried or shed without causing symptoms complicates the interpretation of microbiological data when diagnosing certain infectious disease syndromes. Diagnostic criteria that attribute symptoms to a pathogen which is detectable, whether it is or is not the aetiological agent of disease, may lead to outcome misclassification in epidemiological studies. Case-control studies are commonly undertaken to estimate vaccine effectiveness (VE) and present an opportunity to compare pathogen detection among individuals with and without clinically relevant symptoms. Considering this study context, we present a mathematical framework yielding simple estimators for the direct effects of vaccination on various aspects of host susceptibility. These include protection against acquisition of the pathogen of interest and protection against progression of this pathogen to disease following acquisition. We assess the impact of test sensitivity on these estimators and extend our framework to identify a 'vaccine probe' estimator for pathogen-specific aetiological fractions. We also derive biases affecting VE estimates under the test-negative design, a special case enrolling only symptomatic persons. Our results provide strategies for estimating pathogen-specific VE in the absence of a diagnostic gold standard. These approaches can inform the design and analysis of studies addressing numerous pathogens and vaccines.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。