基于空间和非空间方法的中部城市COVID-19病毒传播相对风险分析

Yurid Audina, Rina Filia Sari, Rina Widyasari
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引用次数: 0

摘要

<span lang="EN">棉兰市是北苏门答腊省城市中COVID-19病毒病例最多的城市。本研究旨在分析COVID-19病毒传播的相对风险水平。相对危险度估计是疾病制图中的一项统计数据,用于确定疾病的分布。相对风险估计可以使用直接估计模型或标准化迁移率和小面积估计模型,使用贝叶斯条件自回归(CAR)与泊松-伽马模型。泊松-伽玛模型是一种以计数数据形式估计小区域的模型,适合用于疾病制图案例。本研究旨在利用标准化迁移率和贝叶斯条件自回归模型寻找相对风险值作为绘制棉兰市COVID-19病毒传播图的基础。并寻找中心误差平方(KTG) /均方误差(MSE)的值作为比较,哪种模型在估计本研究中更有效。条件自回归模型。并寻找中心误差平方(KTG) /均方误差(MSE)的值作为比较,哪种模型在估计本研究中更有效。</span>
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RELATIVE RISK ANALYSIS OF THE SPREAD OF COVID-19 VIRUS IN MEDAN CITY BY SPATIAL AND NON-SPATIAL APPROACHES
The city of Medan is the city with the highest cases of COVID-19 virus among cities in North Sumatra. This study was conducted to analyze the relative risk level for the spread of the COVID-19 virus. Estimation of relative risk is a statistic in disease mapping that is used to determine the distribution of disease. Relative risk estimation can be estimated using a direct estimator model or Standardized Morbility ratio and a small area estimation model using Bayesian Conditional Autoregressive (CAR) with the Poisson-Gamma model. The Poisson-Gamma model is one of the models in estimating small areas in the form of count data which is suitable for use in disease mapping cases. This study aims to find the relative risk value as the basis for mapping the spread of the COVID-19 virus in the city of Medan using the Standardized Morbility Ratio and Bayesian Condition Autoregressive models. And look for the value of the Central Error Squared (KTG) / Mean Squared Error (MSE) as a comparison which model is more efficient in estimating this research. Condition Autoregressive models. And look for the value of the Central Error Squared (KTG) / Mean Squared Error (MSE) as a comparison which model is more efficient in estimating this research.
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