在COVID-19爆发后,对MPH课程的立即但短暂的兴趣:一个中断的时间序列分析
Jemar R Bather1,2, Emily M Burke3, Christine M Plepys3
1Center for Anti-racism, Social Justice & Public Health, New York University School of Global Public Health, New York, NY, USA.
Public health reports (Washington, D.C. : 1974)
|October 22, 2024
概括
由于COVID-19的流行,最初人们对公共卫生士 (MPH) 课程的兴趣增加了,但这种激增并没有长期持续下去. 与疫情前的趋势相比,疫情期间的申请率下降.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 卫生政策 卫生政策
背景情况:
- 随着COVID-19大流行,公众对公共卫生的重要性的认识提高了.
- 对公共卫生士 (MPH) 课程的兴趣可能受到大流行影响.
- 与大流行病发作相对应的MPH应用趋势的数据有限.
研究的目的:
- 检查COVID-19大流行开始前后MPH申请率的趋势.
- 分析31种度的MPH应用率,重点关注流行病学.
- 调查根据种族,种族和公民身份身份的申请率差异.
主要方法:
- 使用了一种准实验性设计,分析了2015-2016年至2022-2023年的MPH应用数据.
- 员工中断时间序列分析,以评估流行病对申请率的直接和持续影响.
- 研究了总体申请人,特定种族/族群和非美国公民的趋势.
主要成果:
- 疫情爆发后,大多数人口群体的MPH申请立即增加.
- 这一最初的激增并没有持续下去,疫情期间的申请率趋势低于疫情前的趋势.
- 非美国公民的MPH流行病学度和整体MPH申请显示,在大流行期间持续上升的趋势.
结论:
- 疫情最初增加了MPH计划的兴趣,但长期趋势需要注意.
- 需要创新策略来保持对MPH学位的持续兴趣.
- 确保公共卫生计划的多元化申请者池仍然至关重要.
相关概念视频
Steps in Outbreak Investigation
107
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:
107
Censoring Survival Data
65
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...
65


