收回:一个随机的SEIRS流行病模型与感染力量和干预策略
Journal of healthcare engineering
|November 10, 2023
概括
这篇文章已被撤回. 最初的研究,DOI 10.1155/2022/4538045标识,不再被认为是有效的或科学记录的一部分.
科学领域:
- 科学出版标准的科学出版标准.
- 撤回通知 撤回通知
背景情况:
- 科学文献的完整性至关重要.
- 撤销有助于在必要时纠正科学记录.
研究的目的:
- 为了正式收回DOI 10.1155/2022/4538045.5标识的物品.
- 告知科学界关于本次撤回的信息.
主要方法:
- 开始了正式的撤销程序.
- 撤回通知发布以提醒读者.
主要成果:
- 文章DOI: 10.1155/2022/4538045已经正式撤回.
- 此操作将该文章从同行评审文献中删除.
结论:
- 收回的文章不应该被引用或用作参考.
- 这次撤回支持科学准确性和道德出版实践.
相关概念视频
Steps in Outbreak Investigation
135
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:
135
Infection
8.0K
When a pathogen enters the body and reproduces, it can cause an infection, damage body cells, and cause illness symptoms that eventually lead to disease. Therefore, its prevention requires breaking the chain of infection.
The chain begins with pathogens: bacteria, viruses, fungi, prions, or parasites such as protozoa helminths. These can be present on the skin as transient or resident flora, or they can be acquired from the environment. Identifying and treating the type of infection and...
The chain begins with pathogens: bacteria, viruses, fungi, prions, or parasites such as protozoa helminths. These can be present on the skin as transient or resident flora, or they can be acquired from the environment. Identifying and treating the type of infection and...
8.0K
Statistical Software for Data Analysis and Clinical Trials
582
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
582
Censoring Survival Data
108
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...
108
Viral Recombination
23.5K
Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.
23.5K
Introduction To Survival Analysis
250
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...
250


