对疫苗有效性的高估和低估
Hilla De-Leon1,2, Dvir Aran3,4
1Faculty of Biology, Technion-Israel Institute of Technology, Technion-Israel Institute of Technology, 21 Sderot Rose, Haifa, 3095230, Israel.
BMC medical research methodology
|July 2, 2025
概括
由于未计入的间接保护,疫苗对SARS-CoV-2感染的有效性有所不同. 考虑到接种疫苗和未接种疫苗的个人之间的相互作用,可以提供更准确的疫苗有效性 (VE) 估计.
科学领域:
- 流行病学 流行病学
- 数学建模的数学建模
- 公共卫生 公共卫生
背景情况:
- 报告的SARS-CoV-2疫苗有效性 (VE) 在不同研究中差异很大 (60-95%).
- 在以色列同时进行的研究报告了相互矛盾的 VE 估计 (90-95% vs ~80%).
- 这种变化可能源于对疫苗间接保护和阻止传播的不充分考虑.
研究的目的:
- 调查间接保护对SARS-CoV-2疫苗有效性估计的影响.
- 为了解释不同研究报告的 VE 的差异.
- 为准确的 VE 估计提出一种新的方法.
主要方法:
- 开发了一种新的分析异质感染模型.
- 扩展了基于代理的模型,以纳入异质相互作用.
- 将模型应用于来自以色列的现实世界区域数据 (2021年初).
- 估计VE使用基于人口和二次感染的研究设计.
主要成果:
- 根据接种疫苗/未接种疫苗的相互作用,对85%有效率的疫苗的估计VE在70-95%之间.
- 不同的研究设计捕捉了不同的相互作用水平,解释了观察到的VE差异.
- 提出了一种独立于相互作用知识的准确 VE 估计方法.
结论:
- 间接保护对VE估计有很大的影响.
- 研究设计可以在VE报告中引入偏差,因为交互捕获的不同.
- 拟议的方法提供了一种更准确的方法来了解疫苗的影响,并为公共卫生政策提供信息.
相关概念视频
01:51Vaccinations
45.3K
Overview
45.3K
01:29Bias in Epidemiological Studies
700
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
700
01:27Confounding in Epidemiological Studies
272
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
272
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
182
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
182
01:13Accuracy and Errors in Hypothesis Testing
318
Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
318
01:13Sensitivity, Specificity, and Predicted Value
678
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
Sensitivity is the...
678