1
|
Wei M, Li S, Lu X, Hu K, Li Z, Li M. Changing respiratory pathogens infection patterns after COVID-19 pandemic in Shanghai, China. J Med Virol 2024; 96:e29616. [PMID: 38634514 DOI: 10.1002/jmv.29616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 03/21/2024] [Accepted: 04/08/2024] [Indexed: 04/19/2024]
Abstract
To assess the positive rate of 11 respiratory pathogens in 2023, providing a comprehensive summary and analysis of the respiratory infection patterns after COVID-19 pandemic. The study comprised 7544 inpatients suspected of respiratory infections who underwent respiratory pathogen multiplex polymerase chain reaction tests from July 2022 to December 31, 2023. We analyzed the positive rate of 11 pathogens over 18 months and the characterization of infection patterns among different age groups and immune states. Among 7544 patients (age range 4 months to 104 years, 44.99% female), the incidence of infected by at least one of the 11 pathogens was 26.07%. Children (55.18%, p < 0.05) experienced a significantly higher infection probability than adults (20.88%) and old (20.66%). Influenza A virus (8.63%), Mycoplasma pneumoniae (5.47%), and human rhinovirus (5.12%) were the most common pathogens. In children, M. pneumoniae (35.96%) replaced the predominant role of human respiratory syncytial virus (HRSV) (5.91%) in the pathogen spectrum. Age, immunosuppressed state, and respiratory chronic conditions were associated with a significantly higher risk of mixed infection. Immunosuppressed patients were more vulnerable to human coronavirus (4.64% vs. 1.65%, p < 0.05), human parainfluenza virus (3.46% vs. 1.69%, p < 0.05), and HRSV (2.27% vs. 0.55%, p < 0.05). Patterns in respiratory infections changed following regional epidemic control measures and the COVID-19 pandemic.
Collapse
Affiliation(s)
- Muyun Wei
- Department of Laboratory Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuangshuang Li
- Department of Laboratory Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xinhua Lu
- Department of Laboratory Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Kaiming Hu
- Department of Laboratory Medicine, Chaohu Hospital, Anhui Medical University, Hefei, China
| | - Zhilan Li
- Department of Laboratory Medicine, Seventh People's Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Min Li
- Department of Laboratory Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| |
Collapse
|
2
|
Zhang L, Zhang Y, Duan W, Wu S, Sun Y, Ma C, Wang Q, Zhang D, Yang P. Using an influenza surveillance system to estimate the number of SARS-CoV-2 infections in Beijing, China, weeks 2 to 6 2023. Euro Surveill 2023; 28:2300128. [PMID: 36927716 PMCID: PMC10021470 DOI: 10.2807/1560-7917.es.2023.28.11.2300128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023] Open
Abstract
With COVID-19 public health control measures downgraded in China in January 2023, reported COVID-19 case numbers may underestimate the true numbers after the SARS-CoV-2 Omicron wave. Using a multiplier model based on our influenza surveillance system, we estimated that the overall incidence of SARS-CoV-2 infections was 392/100,000 population in Beijing during the 5 weeks following policy adjustment. No notable change occurred after the Spring Festival in early February. The multiplier model provides an opportunity for assessing the actual COVID-19 situation.
Collapse
Affiliation(s)
- Li Zhang
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Yi Zhang
- General Administration of Customs (Beijing) International Travel Health Care Center, Dongcheng District, Beijing, China
| | - Wei Duan
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Shuangsheng Wu
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Ying Sun
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Chunna Ma
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Quanyi Wang
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Daitao Zhang
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Peng Yang
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| |
Collapse
|
3
|
Liang J, Wang Z, Liu Y, Zeng L, Li Z, Liang J, Liang H, Jiang M, Yang Z. Epidemiology and co-infection patterns in patients with respiratory tract infections in southern China between 2018 and 2020. J Infect 2021; 83:e6-e8. [PMID: 34302865 DOI: 10.1016/j.jinf.2021.07.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 07/15/2021] [Indexed: 11/18/2022]
Affiliation(s)
- Jingyi Liang
- National center for respiratory medicine, state 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, 510120, P.R. China; Guangzhou KingMed Diagnostics Group Co., Ltd., Guangzhou 510120, China
| | - Zhufeng Wang
- National center for respiratory medicine, state 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, 510120, P.R. China
| | - Yong Liu
- National center for respiratory medicine, state 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, 510120, P.R. China
| | - Linxiu Zeng
- Guangzhou KingMed Diagnostics Group Co., Ltd., Guangzhou 510120, China
| | - Zhengtu Li
- National center for respiratory medicine, state 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, 510120, P.R. China
| | - Jiamin Liang
- Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Hanwen Liang
- National center for respiratory medicine, state 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, 510120, P.R. China
| | - Mei Jiang
- National center for respiratory medicine, state 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, 510120, P.R. China.
| | - Zifeng Yang
- National center for respiratory medicine, state 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, 510120, P.R. China.
| |
Collapse
|