Epidemiology dynamic of the common respiratory virus in winter-spring, 2018–2023 in Guangdong province, China
Letter to the Editor

Epidemiology dynamic of the common respiratory virus in winter-spring, 2018–2023 in Guangdong province, China

Jingyi Liang1, Yangqianxi Wang2, Yong Liu3, Qianying Li4, Zhiqi Zeng2,3,4,5, Zifeng Yang2,4,5, Chitin Hon1,2,5

1Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China; 2Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China; 3Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China; 4State 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, China; 5Guangzhou Laboratory, Guangzhou, China

Correspondence to: Dr. Chitin Hon, PhD. Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China; Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China; Guangzhou Laboratory, Guangzhou 510120, China. Email: cthon@must.edu.mo; Dr. Zifeng Yang, MD. Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China; 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, 151 Yanjiang Road, Guangzhou 510120, China; Guangzhou Laboratory, Guangzhou 510120, China. Email: Jeffyah@163.com; Dr. Zhiqi Zeng, PhD. Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China; Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, 195 Dongfengxi Road, Guangzhou, China; 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, 151 Yanjiang Road, Guangzhou 510120, China; Guangzhou Laboratory, Guangzhou, 510120, China. Email: zeng_zhiq@126.com.

Submitted May 29, 2023. Accepted for publication Dec 14, 2023. Published online Dec 26, 2023.

doi: 10.21037/jtd-23-833

Respiratory pathogens are a significant public health issue that can cause severe illnesses and fatalities (1). In recent years, novel respiratory tract infectious pathogens have emerged, with the global pandemic caused by coronavirus disease 2019 (COVID-19) having a tremendous economic and societal impact (2). Therefore, monitoring and analyzing the prevalence of typical respiratory pathogens is crucial for formulating appropriate prevention and treatment strategies. This study focuses on the respiratory pathogen detection data from the winter-spring seasons (high-occurrence season) of 2018 to 2023 in Guangdong province, China. We analyzed the changes in the positive detection rates of respiratory pathogens from January to March over the years, aiming to provide a reference for public health decision-making.

From 2018 to 2023, KingMed Diagnostics collected a total of 37,933 respiratory samples from 331 hospitals, maternal and child health care centers, and community health service centers in Guangdong province, China. The sample types included nasal and pharyngeal swabs, bronchoalveolar lavage fluid, oral secretions, sputum, and pleural or peritoneal fluid. These samples were tested for various respiratory pathogens, including adenovirus (ADV), influenza A virus (IFA), influenza B virus (IFB), human metapneumovirus (HMPV), parainfluenza virus 1/2/3 (PIV1/2/3), rhinovirus (RHV), respiratory syncytial virus (RSV). Participants include newborns, infants, children, youth, adults, and the elderly. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study was approved by the Ethics Committee of KingMed Diagnostics (No: GZKM-2019-24) and individual consent for this retrospective analysis was waived.

During the study period, the detection rate of respiratory pathogens under surveillance in 2018-2019 was relatively high and showed a downward trend (Figure 1A). However, following the outbreak of COVID-19, the positive detection rate of most respiratory pathogens notably declined. This could be attributed to the strict public health and social measures (PHSM) (3) implemented, including social distancing, mask-wearing, and personal hygiene practices. Additionally, this may be due to the medical resources heavily allocated to diagnosing and treating COVID-19 cases. As a result, the testing for other respiratory pathogens may have been limited, leading to a decrease in their positive detection rates.

Figure 1 Detection rate of multiple respiratory pathogens (ADV, IFA, IFB, HMPV, PIV1/2/3, RHV, RSV) in winter-spring seasons (January–March) from 2018 to 2023. (A) The overall detection of respiratory pathogens. (B) The detection of a single viral respiratory pathogen. The height of the bar represents the number of respiratory samples, and the dark line represents the positive rate. ADV, adenovirus; IFA, influenza A virus; IFB, influenza B virus; HMPV, human metapneumovirus; PIV1/2/3, parainfluenza virus 1/2/3; RHV, rhinovirus; RSV, respiratory syncytial virus.

In the winter-spring of 2020, the positive detection rates of IFA, IFB, HMPV, and RHV were close to zero. Compared to the positive detection rates of the respiratory pathogens mentioned above, although the detection rates of ADV and RSV decreased, they remained at relatively low levels of prevalence. After 2021, with adjustments in COVID-19 policies and the immune gap caused by long-term control measures, there were varying degrees of increase in positive detection rates for all pathogens except IFB. Among them, IFA, HMPV, PIV1/2/3, and RHV showed notable peaks in positive detection rates and require particular attention. Notably, towards the end of 2022, the majority of COVID-19 control policies were relaxed in China. Figure 1B shows a significant surge in the positive detection rate of IFA in the spring of 2023, which is consistent with reports of an outbreak of IFA earlier this year in China (4). Additionally, there is a noticeable increase in PIV1/2/3 and RHV, and it is necessary to monitor the trend of their positive detection rates after March to catch the high epidemic risk.

Our research illustrates the detection frequencies of common respiratory viruses in Guangdong province, revealing the epidemic risk of them in the post-COVID-19 era. We also emphasize the importance of ongoing monitoring of respiratory pathogens and highlight the significance of implementing necessary preventive and control measures.

Acknowledgments

Funding: This work was supported by the Science and Technology Development Fund of Macau SAR (No. 005/2022/ALC); National Key Research and Development Program of China (No. 2022YFC2600705); Self-supporting Program of Guangzhou Laboratory (No. SRPG22-007); Science and Technology Program of Guangzhou (No. 2022B01W0003); Science and Technology Program of Guangzhou (Grant No. 202102100003); Science and Technology Development Fund of Macau SAR (No. 0045/2021/A); Macau University of Science and Technology (No. FRG-20-021-MISE).

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Journal of Thoracic Disease for the series “Thoracic Diseases and Big Data”. The article has undergone external peer review.

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-23-833/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-23-833/coif). The series “Thoracic Diseases and Big Data” was commissioned by the editorial office without any funding or sponsorship. Z.Y. served as the unpaid Guest Editor of the series. The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study was approved by the Ethics Committee of KingMed Diagnostics (No: GZKM-2019-24) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

  1. Songwang W, Yewu Z, Zunyou W, et al. Reported Cases of Respiratory Infectious Diseases — China, January−June, 2018−2020. China CDC Weekly 2020;2:747-8. [Crossref] [PubMed]
  2. Miyah Y, Benjelloun M, Lairini S, et al. COVID-19 Impact on Public Health, Environment, Human Psychology, Global Socioeconomy, and Education. ScientificWorldJournal 2022;2022:5578284. [Crossref] [PubMed]
  3. Ali ST, Lau YC, Shan S, et al. Prediction of upcoming global infection burden of influenza seasons after relaxation of public health and social measures during the COVID-19 pandemic: a modelling study. Lancet Glob Health 2022;10:e1612-22. [Crossref] [PubMed]
  4. Zhao J, Hua A, Wang B, et al. Just as China Emerges From Covid, Concerns Grow of a Flu Epidemic. 2023. Available online: https://www.caixinglobal.com/2023-03-21/just-as-china-emerges-from-covid-concerns-grow-of-a-flu-epidemic-102010514.html
Cite this article as: Liang J, Wang Y, Liu Y, Li Q, Zeng Z, Yang Z, Hon C. Epidemiology dynamic of the common respiratory virus in winter-spring, 2018–2023 in Guangdong province, China. J Thorac Dis 2023;15(12):7165-7167. doi: 10.21037/jtd-23-833

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