尼日利亚COVID-19疫苗接种的干预分析:天真的解决方案与中断的时间序列相比
Desmond Chekwube Bartholomew1, Chrysogonus Chinagorom Nwaigwe1, Ukamaka Cynthia Orumie2
1Department of Statistics, Federal University of Technology Owerri, Owerri, Imo State Nigeria.
概括
尼日利亚的COVID-19疫苗接种在2021年3月至2022年3月期间没有显著减少日常病例. 预测预计2023年1月至4月病例将急剧增加,需要继续采取公共卫生措施.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 生物统计学 生物统计学
背景情况:
- 由于COVID-19的流行,全球范围内需要快速部署疫苗.
- 了解尼日利亚等不同环境中的疫苗有效性对于公共卫生政策至关重要.
研究的目的:
- 评估COVID-19疫苗对尼日利亚日常病例的利用和影响.
- 确定最适合用于分析COVID-19疫苗接种后趋势的统计模型.
主要方法:
- 使用中断时间序列模型进行干预分析.
- 与使用AIC,sigma2和日志概率的原始解决方案模型进行比较.
- ARIMA (4,1,4) 与外源变量被确定为最合适的模型.
主要成果:
- 被中断的时间序列模型显著超过了原始模型.
- 疫苗接种干预在减少每日COVID-19病例 (2021年3月至2022年3月) 方面没有统计学意义.
- 阿里马预测预测2023年1月至4月期间COVID-19病例的激增.
结论:
- 目前的疫苗接种水平可能还没有达到对尼日利亚每日病例减少有重大影响的门.
- 建议继续遵守公共卫生协议和加强疫苗接种/敏感化计划,以减轻未来的激增.
相关概念视频
Bias in Epidemiological Studies
254
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
254
Statistical 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
Vaccinations
44.4K
Overview
44.4K
Confounding in Epidemiological Studies
169
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
169
Steps in Outbreak Investigation
125
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:
125
Contingency Table
2.5K
A contingency table provides a way of portraying data that can facilitate calculating probabilities. It is a method of displaying a frequency distribution as a table with rows and columns to show how two variables may be dependent (contingent) upon each other; The table helps determine conditional probabilities quite quickly and can help systematically organize, analyze and quantify data. The table displays sample values concerning two variables that may be dependent or contingent on one...
2.5K


