纽约市的COVID-19测试公平性在流行病的前两年:免费测试数据的人口统计分析
Daniel Rosenfeld1,2, Sean Brennan1,3, Andrew Wallach1,4
1NYC Test & Treat Corps, The New York City Health + Hospitals Corporation, 50 Water St., New York, NY, 10004, United States, 1 212-788-3339, 1 212-788-3673.
JMIR public health and surveillance
|March 13, 2025
概括
纽约市的COVID-19测试计划成功改善了测试公平. 免费测试针对服务不足的地区,增加测试数量和较低收入社区的积极结果,使资源分配成为可能.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 健康 公平 卫生 公平
背景情况:
- 纽约市经历了超过46,000例COVID-19死亡,不成比例地影响了某些社区.
- 超过600万个COVID-19测试免费进行,测试集中在资源有限的地区.
- 测试患病率在历史上有利于富裕地区,需要有针对性的干预.
研究的目的:
- 评估纽约市COVID-19测试计划对测试公平的影响.
- 评估该计划在不同经济,地理和人口群体中的有效性.
- 分析移动测试单位在解决测试不平等方面的作用.
主要方法:
- 利用了来自48家医院的6,347,533个COVID-19测试和449,721个阳性结果的数据库.
- 在Python中使用负二项式回归来分析按邮政编码表格区 (ZCTA) 的人均测试和阳性率.
- 独立变量包括中等收入,年龄,英语人口和种族/种族来评估测试模式.
主要成果:
- 人均测试率与收入中位数相反相关;随着收入下降,测试显著增加 (P<.001).
- 阳性测试结果也随着收入中位数较低 (P<.001) 和只说英语的比例较高 (P=.03) 显著增加.
- 测试数量与有色人种中位数年龄或百分比之间没有发现显著的相关性.
结论:
- 纽约市的无成本测试计划通过专注于资源贫困,高影响地区,明显改善了公平.
- 在服务不足的社区中发现阳性病例的增加,有助于及时部署公共卫生资源.
- 公平的测试策略是可行的,对于在未来的流行病响应中早期实施至关重要.
相关概念视频
Steps in Outbreak Investigation
102
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
102
Statistical Methods for Analyzing Epidemiological Data
275
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
275
Types of Skewness
11.3K
If the frequency distribution of a data set is more inclined towards smaller or larger values, the distribution is said to be skewed. If data values are skewed to the right, then the distribution is called positively skewed. Conversely, if the plot is skewed to the left, the distribution is called negatively skewed.
For instance, in the middle of a pandemic, the geographical distribution of vaccine coverage may be positively skewed towards populations in the global north countries. However,...
For instance, in the middle of a pandemic, the geographical distribution of vaccine coverage may be positively skewed towards populations in the global north countries. However,...
11.3K
Comparing the Survival Analysis of Two or More Groups
113
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
113
Contingency Table
2.4K
A contingency table provides a way of portraying data that can facilitate calculating probabilities. It is a method of displaying a frequency distribution as a table with rows and columns to show how two variables may be dependent (contingent) upon each other; The table helps determine conditional probabilities quite quickly and can help systematically organize, analyze and quantify data. The table displays sample values concerning two variables that may be dependent or contingent on one...
2.4K


