中国石河子市流感病毒感染与 SARS-CoV-2 感染关系的初步探索：一项检测阴性的研究

IF 8.8 3区医学 Q1 Medicine

Infectious Disease Modelling Pub Date : 2024-10-09 DOI:10.1016/j.idm.2024.10.002

Songsong Xie , Yinxia Su , Yanji Zhao , Yaling Du , Zihao Guo , Xiu Gu , Jie Sun , Mohammad Javanbakht , Daihai He , Jiazhen Zhang , Yan Zhang , Kai Wang , Shi Zhao

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引用次数: 0

摘要

COVID-19 和流感等呼吸道疾病的爆发引起了全球关注。然而，感染甲型流感的风险是否会受到 SARS-CoV-2 感染史的影响仍不清楚。在本研究中，我们进行了一项检测阴性的病例对照研究，并利用逻辑回归模型分析了 SARS-CoV-2 与甲型流感感染之间的关系。在 258 个符合条件的流感样病症（ILI）患者样本中，我们没有发现 SARS-CoV-2 感染史与甲型流感感染风险之间存在统计学意义上的显著关联。这些发现可能表明，通过接种疫苗或自然免疫获得的 COVID-19 抗体并不能预防流感。

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A tentative exploration for the association between influenza virus infection and SARS-CoV-2 infection in Shihezi, China: A test-negative study

The outbreak of respiratory diseases, such as COVID-19 and influenza, has drawn global attention. However, it remains unclear whether the risk of influenza A infection may be affected by the history of SARS-CoV-2 infection. In this study, we conducted a test-negative case-control study, and utilized a logistic regression model to analyze the relationship between SARS-CoV-2 and influenza A infections. Among 258 eligible patient samples with influenza-like illness (ILI), we did not detect a statistically significant association between the history of SARS-CoV-2 infection and the risk of influenza A infection. These findings might indicate that antibodies against COVID-19 acquired through vaccination or natural immunity have not protected against influenza.

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来源期刊

Infectious Disease Modelling Mathematics-Applied Mathematics

CiteScore

17.00

自引率

3.40%

发文量

审稿时长

17 weeks

期刊介绍： Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.