适应时间位置采样用于COMPASS:美国15个不同社区的SARS-CoV-2流行研究
Sahar Z Zangeneh1,2,3, Timothy Skalland2, Krista Yuhas2
1From the RTI International, Research Triangle, NC.
Epidemiology (Cambridge, Mass.)
|December 11, 2023
概括
这项研究开发了一种可适应的采样设计,以估计不同美国社区的SARS-CoV-2患病率,为未来危机期间的公共卫生监测提供了一个模型.
科学领域:
- 流行病学 流行病学
- 公共卫生监督 公共卫生监督
- 统计学方法论 统计学方法论
背景情况:
- COVID-19不成比例地影响了服务不足的人群,包括种族和民族少数群体和基本工作人员.
- 估计SARS-CoV-2 (严重急性呼吸系统综合征冠状病毒2) 在不同社区的流行率,由于公共卫生准则的变化,提出了重大后勤挑战.
- 对于了解弱势群体疾病负担至关重要的是需要强大的数据收集方法.
研究的目的:
- 估计美国15个不同社区的儿童和成人中SARS-CoV-2感染的横截面流行率.
- 开发和实施灵活的统计抽样设计,能够适应不可预测的公共卫生任务和不断变化的感染动态.
- 为未来在具有挑战性的环境下进行的人口健康研究提供一个方法框架.
主要方法:
- 采用时间位置抽样与复杂的调查设计,包括分层和聚类,从选定的社区招募参与者.
- 实施了知情同意,样本采集和在公共场所户外进行采访的安全协议.
- 根据不断变化的场所可访问性和流行病学数据,动态调整了采样框架和选择概率.
主要成果:
- 成功开发了一种创新的采样策略,以适应现实世界的限制,如场地关闭和转移感染热点.
- 生成特定地点的调查权重,以解释非响应和校准结果,以县级人口数据 (年龄,出生时的性别) 进行校准.
- 证明了在动态公共卫生干预中进行严格的人口级健康评估的可行性.
结论:
- 提出的采样和数据收集策略虽然针对COVID-19而具体,但为未来的公共卫生监测提供了可转移的案例研究.
- 可适应的方法可以为应对新出现的全球健康威胁提供快速有效的响应.
- 这种方法使得即使面临不可预测的后勤和政策相关挑战,也可以在人口层面做出强有力的推断.
相关概念视频
Systematic Sampling Method
10.4K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
Systematic sampling is one of the simplest methods...
10.4K
Convenience Sampling Method
8.9K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
8.9K
Cluster Sampling Method
11.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.9K
Stratified Sampling Method
12.0K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
To choose a stratified sample, divide the population into groups called strata and then take a...
12.0K
Data Collection by Observations
12.0K
Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
12.0K
Sampling Plans
187
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
187


