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相关概念视频

Statistical Methods for Analyzing Epidemiological Data01:25

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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:
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An Incident or Occurrence Report in a healthcare setting is a crucial document used to record any unexpected occurrence that may or may not have affected a patient, employee, or visitor. Such reports are critical to improving patient safety and include all details leading up to and including the event.
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Hazard Rate01:11

Hazard Rate

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The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
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It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
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Essential infection prevention measures are based on the knowledge of the infection chain, the modes of transmission in healthcare settings, and the use of the best practices in all healthcare settings. Compulsory public reporting of healthcare-associated infection rates is needed to allow individuals and the community to make informed choices regarding selecting a healthcare facility.
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非致命枪支伤害住院病人的州级估计,2000-2021年

Rosanna Smart1, James Murphy1, Terry L Schell1

  • 1Rosanna Smart, James Murphy, and Terry L. Schell are with the RAND Corporation, Santa Monica, CA. Andrew R. Morral is with the RAND Corporation, Arlington, VA. Nancy Nicosia is with the RAND Corporation, Boston, MA.

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非致命的枪支伤害住院病例在全国范围内激增,特别是在2019-2020年. 这些新数据揭示了州一级的显著差异,并强调了一些地区枪支死亡人数如何低于严重伤害人数.

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科学领域:

  • 公共卫生 公共卫生
  • 流行病学 流行病学
  • 伤害科学 伤害科学

背景情况:

  • 要了解与枪支有关的伤害的全部范围,不仅需要死亡率统计数据,还需要数据.
  • 非致命性枪支伤害住院住院 (NFIIHs) 是枪支暴力影响的关键,但往往被低估的衡量标准.
  • 现有的数据限制阻碍了对国家级NFIIH趋势和差异的全面分析.

研究的目的:

  • 开发一个全面的,公开可访问的数据集,从2000年到2021年的美国州级NFIIHs.
  • 分析NFIIH与枪支谋杀率的趋势,地理变化和相关性.
  • 提供关键数据,以告知与枪支伤害有关的公共卫生政策和干预措施.

主要方法:

  • 采用贝叶斯模型,为334个国家年度观测计算出缺失的NFIIH利率.
  • 在766个观察中,针对不完整的损伤机制编码应用了统计纠正.
  • 分析了国家和州级NFIIH趋势,并计算了与枪支谋杀率的相关性.

主要成果:

  • 国家NFIIH利率在2019年至2020年之间增加了三分之一,达到每10,000人1.31%.
  • 观察到州一级的显著差异,比率从夏威夷的0.18到路易斯安那的2.18不等.
  • NFIIH率与枪支杀人率 (0.86) 有很强的相关性,但非致命伤害与致命伤害的比例在各州之间有很大差异.

结论:

  • 国际金融机构的利率表现出相当大的地理差异和时间差异.
  • 枪支死亡人数并不能完全捕捉到严重枪支伤害的负担,特别是在某些州.
  • 开发的数据集为评估枪支政策对伤害发生率和严重性的影响提供了至关重要的资源.