Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling study
BackgroundInfluenza A virus have a distinctive ability to exacerbate SARS-CoV-2 infection proven by in vitro studies. Furthermore, clinical evidence suggests that co-infection with COVID-19 and influenza not only increases mortality but also prolongs the hospitalization of patients. COVID-19 is in a...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-03-01
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| Series: | Frontiers in Cellular and Infection Microbiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fcimb.2024.1347710/full |
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| author | Jingyi Liang Jingyi Liang Yangqianxi Wang Yangqianxi Wang Zhijie Lin Zhijie Lin Wei He Wei He Jiaxi Sun Qianyin Li Mingyi Zhang Zichen Chang Yinqiu Guo Wenting Zeng Tie Liu Zhiqi Zeng Zhiqi Zeng Zifeng Yang Zifeng Yang Zifeng Yang Chitin Hon Chitin Hon Chitin Hon |
| author_facet | Jingyi Liang Jingyi Liang Yangqianxi Wang Yangqianxi Wang Zhijie Lin Zhijie Lin Wei He Wei He Jiaxi Sun Qianyin Li Mingyi Zhang Zichen Chang Yinqiu Guo Wenting Zeng Tie Liu Zhiqi Zeng Zhiqi Zeng Zifeng Yang Zifeng Yang Zifeng Yang Chitin Hon Chitin Hon Chitin Hon |
| author_sort | Jingyi Liang |
| collection | DOAJ |
| description | BackgroundInfluenza A virus have a distinctive ability to exacerbate SARS-CoV-2 infection proven by in vitro studies. Furthermore, clinical evidence suggests that co-infection with COVID-19 and influenza not only increases mortality but also prolongs the hospitalization of patients. COVID-19 is in a small-scale recurrent epidemic, increasing the likelihood of co-epidemic with seasonal influenza. The impact of co-infection with influenza virus and SARS-CoV-2 on the population remains unstudied.MethodHere, we developed an age-specific compartmental model to simulate the co-circulation of COVID-19 and influenza and estimate the number of co-infected patients under different scenarios of prevalent virus type and vaccine coverage. To decrease the risk of the population developing severity, we investigated the minimum coverage required for the COVID-19 vaccine in conjunction with the influenza vaccine, particularly during co-epidemic seasons.ResultCompared to the single epidemic, the transmission of the SARS-CoV-2 exhibits a lower trend and a delayed peak when co-epidemic with influenza. Number of co-infection cases is higher when SARS-CoV-2 co-epidemic with Influenza A virus than that with Influenza B virus. The number of co-infected cases increases as SARS-CoV-2 becomes more transmissible. As the proportion of individuals vaccinated with the COVID-19 vaccine and influenza vaccines increases, the peak number of co-infected severe illnesses and the number of severe illness cases decreases and the peak time is delayed, especially for those >60 years old.ConclusionTo minimize the number of severe illnesses arising from co-infection of influenza and COVID-19, in conjunction vaccinations in the population are important, especially priority for the elderly. |
| first_indexed | 2024-03-07T16:22:00Z |
| format | Article |
| id | doaj.art-b77800be890a455c9d83118abbbf3780 |
| institution | Directory Open Access Journal |
| issn | 2235-2988 |
| language | English |
| last_indexed | 2024-03-07T16:22:00Z |
| publishDate | 2024-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cellular and Infection Microbiology |
| spelling | doaj.art-b77800be890a455c9d83118abbbf37802024-03-04T04:53:28ZengFrontiers Media S.A.Frontiers in Cellular and Infection Microbiology2235-29882024-03-011410.3389/fcimb.2024.13477101347710Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling studyJingyi Liang0Jingyi Liang1Yangqianxi Wang2Yangqianxi Wang3Zhijie Lin4Zhijie Lin5Wei He6Wei He7Jiaxi Sun8Qianyin Li9Mingyi Zhang10Zichen Chang11Yinqiu Guo12Wenting Zeng13Tie Liu14Zhiqi Zeng15Zhiqi Zeng16Zifeng Yang17Zifeng Yang18Zifeng Yang19Chitin Hon20Chitin Hon21Chitin Hon22Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, ChinaRespiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macao, Macao SAR, ChinaDepartment of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, ChinaRespiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macao, Macao SAR, ChinaDepartment of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, ChinaRespiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macao, Macao SAR, ChinaDepartment of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, ChinaRespiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macao, Macao SAR, ChinaGuangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, ChinaState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, ChinaGuangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, ChinaGuangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, ChinaGuangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, ChinaGuangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, ChinaGuangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, ChinaGuangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, ChinaGuangzhou Laboratory, Guangzhou, Guangdong, ChinaRespiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macao, Macao SAR, ChinaState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, ChinaGuangzhou Laboratory, Guangzhou, Guangdong, ChinaDepartment of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, ChinaRespiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macao, Macao SAR, ChinaGuangzhou Laboratory, Guangzhou, Guangdong, ChinaBackgroundInfluenza A virus have a distinctive ability to exacerbate SARS-CoV-2 infection proven by in vitro studies. Furthermore, clinical evidence suggests that co-infection with COVID-19 and influenza not only increases mortality but also prolongs the hospitalization of patients. COVID-19 is in a small-scale recurrent epidemic, increasing the likelihood of co-epidemic with seasonal influenza. The impact of co-infection with influenza virus and SARS-CoV-2 on the population remains unstudied.MethodHere, we developed an age-specific compartmental model to simulate the co-circulation of COVID-19 and influenza and estimate the number of co-infected patients under different scenarios of prevalent virus type and vaccine coverage. To decrease the risk of the population developing severity, we investigated the minimum coverage required for the COVID-19 vaccine in conjunction with the influenza vaccine, particularly during co-epidemic seasons.ResultCompared to the single epidemic, the transmission of the SARS-CoV-2 exhibits a lower trend and a delayed peak when co-epidemic with influenza. Number of co-infection cases is higher when SARS-CoV-2 co-epidemic with Influenza A virus than that with Influenza B virus. The number of co-infected cases increases as SARS-CoV-2 becomes more transmissible. As the proportion of individuals vaccinated with the COVID-19 vaccine and influenza vaccines increases, the peak number of co-infected severe illnesses and the number of severe illness cases decreases and the peak time is delayed, especially for those >60 years old.ConclusionTo minimize the number of severe illnesses arising from co-infection of influenza and COVID-19, in conjunction vaccinations in the population are important, especially priority for the elderly.https://www.frontiersin.org/articles/10.3389/fcimb.2024.1347710/fullSARS-CoV-2influenzaco-infectionvaccinationcompartmental model |
| spellingShingle | Jingyi Liang Jingyi Liang Yangqianxi Wang Yangqianxi Wang Zhijie Lin Zhijie Lin Wei He Wei He Jiaxi Sun Qianyin Li Mingyi Zhang Zichen Chang Yinqiu Guo Wenting Zeng Tie Liu Zhiqi Zeng Zhiqi Zeng Zifeng Yang Zifeng Yang Zifeng Yang Chitin Hon Chitin Hon Chitin Hon Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling study Frontiers in Cellular and Infection Microbiology SARS-CoV-2 influenza co-infection vaccination compartmental model |
| title | Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling study |
| title_full | Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling study |
| title_fullStr | Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling study |
| title_full_unstemmed | Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling study |
| title_short | Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling study |
| title_sort | influenza and covid 19 co infection and vaccine effectiveness against severe cases a mathematical modeling study |
| topic | SARS-CoV-2 influenza co-infection vaccination compartmental model |
| url | https://www.frontiersin.org/articles/10.3389/fcimb.2024.1347710/full |
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