考虑到COVID-19的否认:巴西的全球应对模式是巴西的典范
1Department of Science and Education, University Center of Formiga and State University of Minas Gerais, Minas Gerais 35570000, Brazil. heslley@uniformg.edu.br.
World journal of methodology
|September 23, 2024
概括
在COVID-19后的巴西,对那些传播错误信息和处方无效治疗的人来说,问责至关重要. 必须对否认领导人和政府官员进行正义追究,因为他们错误地处理了大流行病和高死亡人数.
科学领域:
- 公共卫生 公共卫生
- 医学伦理 医学伦理
- 法律研究 法律研究
背景情况:
- 巴西的2019年冠状病毒病 (COVID-19) 流行突出了重大的公共卫生挑战.
- 广泛的错误信息和推广未经证实的治疗方法使疫情应对工作复杂化.
- 在疫情期间对某些行动缺乏问责制已被确定为一个关键问题.
研究的目的:
- 为了强调在巴西COVID-19大流行后的问责制的关键需求.
- 确定需要审查的关键群体和行动,包括错误信息传播者,处方无效治疗的医疗专业人员和政府的错误处理.
- 倡导正义和实施对那些为大流行病的严重性和死亡人数做出贡献的人采取示范措施.
主要方法:
- 这项研究是对巴西COVID-19大流行期间的事件和反应的批判性分析.
- 它涉及审查针对个人因与流行病相关的行为发起的法律诉讼.
- 该分析基于公共卫生数据,伦理考虑和政府政策审查.
主要成果:
- 对一些个人的法律行动已经开始,揭示了错误信息背后的经济动机.
- 医生处方无效的治疗方法已经使人口处于危险之中,需要问责.
- 联邦政府和否认运动的领导人与因处理不当而导致的高死亡人数有关.
结论:
- 让所有负责任的各方承担责任对于公众的信任和未来的流行病准备至关重要.
- 必须通过立法和行政部门寻求正义,并采取强有力的措施打击错误信息.
- 确保在COVID-19大流行期间对行动的问责制对于巴西的伦理和公共卫生恢复至关重要.
相关概念视频
01:16Response Surface Methodology
95
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
The process of RSM involves several key steps:
95
01:18Steps in Outbreak Investigation
108
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:
108
01:26Principles of Disease Surveillance
74
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
74
01:21Causality in Epidemiology
338
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
338
01:25Statistical Methods for Analyzing Epidemiological Data
316
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:
316
00:52Pareto Chart
6.7K
A Pareto chart is a bar graph or a combination of both line and bar graphs. The bar lengths represent the individual values or the frequency, while the lines represent the cumulative total values. In this chart, the longest bars are arranged on the left and the shortest bars on the right, which makes it easier to read and interpret the data. It can also be called a Pareto diagram or Pareto analysis.
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...
6.7K