非传统数据,前所未有的见解:在流行病期间利用非传统数据
Kaylin Bolt1, Diana Gil-González2,3, Nuria Oliver4
1Health Sciences Division (Assessment, Policy Development, and Evaluation Unit), Public Health - Seattle & King County, Seattle, WA, United States.
Frontiers in public health
|April 3, 2024
概括
非传统的数据来源,如移动和社交媒体数据,在COVID-19大流行期间提供了快速的见解. 建议加强数据治理和基础设施,以充分整合这些有价值的公共卫生工具.
科学领域:
- 公共卫生监督 公共卫生监督
- 数据科学应用数据科学应用
- 流行病学 流行病学
背景情况:
- 随着COVID-19的流行,人们越来越需要多样化的数据来源,而不仅仅是传统的方法.
- 非传统数据,包括移动性,社交媒体和参与式监控,提供了潜在的可能性,但也带来了挑战.
- 担忧包括数据偏差,代表性,知情同意和与非传统数据相关的安全漏洞.
研究的目的:
- 探索在西班牙和意大利COVID-19大流行期间使用非传统数据的成功,挑战和建议.
- 确定改善非传统数据在公共卫生中的实用性和采用的机会.
- 为优化公共卫生系统中非传统数据的使用提供指导.
主要方法:
- 与人工智能,数据科学,流行病学和政策专家进行了定性半结构面试.
- 采访的重点是利用非传统数据的障碍,促进者和机会.
- 数据被转录,编码并使用框架分析方法进行分析.
主要成果:
- 非传统数据对于快速洞察和填补传统数据延迟的空白来说非常有价值.
- 挑战包括不可靠的访问,数据质量问题以及缺乏人口/地理信息.
- 建议包括优先考虑数据治理,建立数据经纪人,并维持多机构合作.
结论:
- 非传统数据在疫情期间显示出实用性,但需要改进才能产生更大的影响.
- 强大的数据治理框架对于指导在公共卫生中使用非传统数据至关重要.
- 持续的合作和对数据基础设施的投资对于将非传统数据纳入公共卫生系统至关重要.
相关概念视频
01:18Steps in Outbreak Investigation
126
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:
126
01:29Issues And Trends In Healthcare Delivery System
5.6K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.6K
01:25Statistical Methods for Analyzing Epidemiological Data
364
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:
364
01:09Types of Skewness
11.6K
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,...
11.6K
01:16Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
128
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
128
01:40Archival Research
16.0K
Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
16.0K