由于死亡导致的居民登记到期统计数据可以用于近实时的死亡跟踪吗? 一项使用2023年韩国数据的验证研究
1Seoul National University Institute of Health and Environment, Seoul, Korea.
Epidemiology and health
|August 8, 2025
概括
国家行政数据 (NAD) 为韩国实时死亡率监测提供了及时和准确的替代方案,优于延迟的生命统计数据 (VS). 这些公共卫生数据可以提高应急响应能力.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 数据科学数据科学数据科学
背景情况:
- 及时追踪死亡率对于公共卫生监测至关重要,特别是在COVID-19流行病等卫生紧急情况期间.
- 韩国生命统计 (VS) 数据历来面临着延迟,限制了其实时监控的实用性.
- 内政和安全部 (MOIS) 提供国家行政数据 (NAD) 关于因死亡而过期的居民登记.
研究的目的:
- 评估国家行政数据 (NAD) 的可靠性,作为韩国死亡率监测的近实时替代方案.
- 为了在不同地理和人口层面上比较NAD和生命统计 (VS) 数据之间的死亡数量.
主要方法:
- 对2023年VS和NAD之间的死亡人数进行比较分析.
- 在多个地理层面进行数据比较:县,省和国家.
- 评估人口变化 (性别和年龄组) 和每月趋势.
- 使用相关性分析,散射图和密度图的统计等价性测试.
主要成果:
- 在国家一级,NAD与VS表现出强烈的一致性,报告死亡的总体差异为0.4%.
- 在所有地理水平上观察到NAD和VS之间的高度一致性,相关系数≥0.999.9.
- 在特定的年龄组 (新生儿和1-4岁) 和每月变化中发现了差异,需要分析考虑.
结论:
- 国家行政数据 (NAD) 作为韩国重要统计数据 (VS) 的可靠替代品,提供更好的及时性和可比准确性.
- 自2023年以来,NAD最近纳入性别和年龄特定数据,使其成为持续死亡监测的有价值基础设施.
- 虽然存在微小的变化,但NAD的优势使其成为公共卫生监测和紧急响应的关键工具.
相关概念视频
Actuarial Approach
135
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
135
Kaplan-Meier Approach
266
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
266
Life Tables
194
A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
194
Introduction To Survival Analysis
398
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
398
Censoring Survival Data
237
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
237
Statistical Methods for Analyzing Epidemiological Data
536
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:
536


