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一种用于追踪已知和新型流感样疾病暴发情况的贝叶斯方法的评估。

An evaluation of a Bayesian method to track outbreaks of known and novel influenza-like illnesses.

作者信息

Aronis John M, Ye Ye, Espino Jessi, Michaels Marian G, Hochheiser Harry, Cooper Gregory F

机构信息

Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China.

出版信息

medRxiv. 2025 Aug 26:2025.08.22.25334257. doi: 10.1101/2025.08.22.25334257.

Abstract

Tracking known influenza-like illnesses, such as influenza, is an important problem in public health and clinical medicine. The problem is complicated by the clinical similarity and co-occurrence of many of these illnesses. Additionally, detecting a new or reemergent disease, such as COVID-19, is of paramount importance as recent history has shown. This paper describes the testing of a system that tracks known influenza-like illnesses and can detect the presence of a novel disease.

摘要

追踪已知的流感样疾病,如流感,是公共卫生和临床医学中的一个重要问题。许多此类疾病在临床上具有相似性且会同时出现,这使得该问题变得复杂。此外,正如近期历史所显示的,检测一种新出现或再度出现的疾病,如新冠病毒病,至关重要。本文描述了一个追踪已知流感样疾病并能检测新型疾病存在的系统的测试情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8fb5/12407607/d3faf7ccede0/nihpp-2025.08.22.25334257v1-f0001.jpg

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