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http://hdl.handle.net/10397/113761
| Title: | A tentative exploration for the association between influenza virus infection and SARS-CoV-2 infection in Shihezi, China : a test-negative study | Authors: | Xie, S Su, Y Zhao, Y Du, Y Guo, Z Gu, X Sun, J Javanbakht, M He, D Zhang, J Zhang, Y Wang, K Zhao, S |
Issue Date: | Mar-2025 | Source: | Infectious disease modelling, Mar. 2025, v. 10, no. 1, p. 201-206 | Abstract: | 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. | Keywords: | China COVID-19 Influenza A Test-negative study |
Publisher: | Elsevier | Journal: | Infectious disease modelling | ISSN: | 2468-0427 | DOI: | 10.1016/j.idm.2024.10.002 | Rights: | © 2024 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). The following publication Xie, S., Su, Y., Zhao, Y., Du, Y., Guo, Z., Gu, X., Sun, J., Javanbakht, M., He, D., Zhang, J., Zhang, Y., Wang, K., & Zhao, S. (2025). A tentative exploration for the association between influenza virus infection and SARS-CoV-2 infection in Shihezi, China: A test-negative study. Infectious Disease Modelling, 10(1), 201-206 is available at https://doi.org/10.1016/j.idm.2024.10.002. |
| Appears in Collections: | Conference Paper |
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