Changes in the Circulation of Multiple Respiratory Pathogens of Severe Acute Respiratory Infections in Shanghai, 2019 to 2023: a retrospective observational study

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Data may be preliminary. 7 January 2025 V1 Latest version Share on Changes in the Circulation of Multiple Respiratory Pathogens of Severe Acute Respiratory Infections in Shanghai, 2019 to 2023: a retrospective observational study Authors : Qi Qiu 0009-0003-2156-7401 , Huilin Shi , Chenyan Jiang , Zheng Teng , Jiajing Liu , Huanyu Wu , Yaxu Zheng , and JIAN CHEN 0000-0002-6685-3503 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.173621934.42073713/v1 318 views 196 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background: Severe acute respiratory infection (SARI) is an important health issue,which was broadly impacted by COVID-19 pandemic. However, changes of epidemic trends and characteristics involving multiple respiratory pathogens are not well defined.This study aimed to characterize the circulation patterns of common respiratory pathogens before, during, and after the pandemic. Methods: The retrospective observational multi-center study was conducted at seven sentinel hospitals in Shanghai,China from 2019 to 2023. Patients with SARI aged 15 years and older were tested for 12 respiratory pathogens (22 subtypes) using real-time polymerase chain reaction. Results: Of the 4738 patients tested,the positive rate of the pathogens decreased from the pre-pandemic year to the pandemic years by 45.47% (from 30.26% to 16.50%), and then increased by 21.64% (from 16.50% to 20.07%) in the post-pandemic year. The change of each pathogen showed four different patterns: (1) decreased first and then increased (IFV, M. pneumoniae , B. pertussis , HBoV); (2) continuing decreased (HPIV, HCoV, HAdV, EV/HRV, L. pneumophila ); (3) increased first and then decreased (HMPV); (4) continuing increased (RSV). Among the three periods, IFV, EV/HRV, and HCoV remained stay on the top five positions of the spectrum, M. pneumoniae was the top pathogen found among 15-44 years of age (33.65%). Varied seasonality was observed among patients with SARI. The co-infection rates of the SARI patients were 1.14% (54/4738), of which mixed infection of IFV and M. pneumoniae was most common (20.37%). Conclusions: Circulation patterns of the common respiratory pathogens changed from 2019 to 2023. It is necessary to be alert to outbreak or epidemic of certain pathogens, as well as strengthening the surveillance for the risk of co-epidemic of multiple respiratory pathogens. Changes in the Circulation of Multiple Respiratory Pathogens of Severe Acute Respiratory Infections in Shanghai, 2019 to 2023: a retrospective observational study Qi Qiu 1,& , Huilin Shi 2,& , Chenyan Jiang 2 , Zheng Teng 3 , Jiajing Liu 3 , Huanyu Wu 4,1 , Yaxu Zheng 1# , Jian Chen 2,# 1 Institute of Infectious Disease Prevention and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China; 2 Shanghai Institute of Preventive Medicine, Shanghai, China； 3 Department of Microbiology, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China； 4 Department of Microbiology, Shanghai Institute of Infectious Disease and Biosecurity, Shanghai, China & Qi Qiu and Huilin Shi contributed equally to the work. # Correspondence: Jian Chen ( [email protected] ),Yaxu Zheng (zhengyaxu @scdc.sh.cn) Funding: Outstanding Youth Training Program (GWVI-11.2-YQ13) of Three-year Action Program of Shanghai Municipality for Strengthening the Construction of Public Health System (2023–2025); Shanghai Municipal Science and Technology Major Project (ZD2021CY001); Health Policy Research Project of Shanghai Municipal Health Commission (2024HP80);Eastern Talent Plan Youth Project (2023);National Natural Science Foundation of China (82404331). Keywords: Severe acute respiratory infection; Co-infection; Pathogen spectrum; Influenza virus; Mycoplasma pneumonia ABSTRCT Background: Severe acute respiratory infection (SARI) is an important health issue,which was broadly impacted by COVID-19 pandemic. However, changes of epidemic trends and characteristics involving multiple respiratory pathogens are not well defined.This study aimed to characterize the circulation patterns of common respiratory pathogens before, during, and after the pandemic. Methods: The retrospective observational multi-center study was conducted at seven sentinel hospitals in Shanghai,China from 2019 to 2023. Patients with SARI aged 15 years and older were tested for 12 respiratory pathogens (22 subtypes) using real-time polymerase chain reaction. Results: Of the 4738 patients tested,the positive rate of the pathogens decreased from the pre-pandemic year to the pandemic years by 45.47% (from 30.26% to 16.50%), and then increased by 21.64% (from 16.50% to 20.07%) in the post-pandemic year. The change of each pathogen showed four different patterns: (1) decreased first and then increased (IFV, M. pneumoniae , B. pertussis , HBoV); (2) continuing decreased (HPIV, HCoV, HAdV, EV/HRV, L. pneumophila ); (3) increased first and then decreased (HMPV); (4) continuing increased (RSV). Among the three periods, IFV, EV/HRV, and HCoV remained stay on the top five positions of the spectrum, M. pneumoniae was the top pathogen found among 15-44 years of age (33.65%). Varied seasonality was observed among patients with SARI. The co-infection rates of the SARI patients were 1.14% (54/4738), of which mixed infection of IFV and M. pneumoniae was most common (20.37%). Conclusions: Circulation patterns of the common respiratory pathogens changed from 2019 to 2023. It is necessary to be alert to outbreak or epidemic of certain pathogens, as well as strengthening the surveillance for the risk of co-epidemic of multiple respiratory pathogens. 1 Introduction Acute respiratory infections (ARIs) have become an important health issue associated with high morbidity and mortality worldwide 1 . Among them, severe acute respiratory infections (SARI) are of several high-frequent factors associating with hospital admissions and in-hospital deaths of all ages. Many kinds of microorganisms have been reported as pathogens of SARI, while viral etiology is the most frequent cause, as well as the involvement of bacteria and fungi. In particular, the novel coronavirus (COVID-19) outbreak, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that was first reported at the end of 2019 in Wuhan, resulted in challenges to the global disease control 2 . Since 2020, China has categorized COVID-19 as a Category B infectious disease but treated it as a Category A disease, until Jan 8, 2023, when it was downgraded to Class B in accordance with the country’s law on prevention and treatment of infectious disease. During the period, the CDC in China implemented a package of nonpharmaceutical interventions (NPIs) (home quarantining, social distancing, mask-wearing, etc.), which has been reported to act on a broad spectrum of respiratory pathogens 3,4 . But most studies did not include the follow-up since the lifting of NPIs. Shanghai Municipal Center for Disease Control and Prevention (Shanghai CDC) implemented a comprehensive surveillance for ARIs program since 2015, testing a spectrum of common contagious pathogens causing ARIs year-round 5 . In this study, making use of these data, we characterized the circulation patterns of common respiratory pathogens among hospitalized SARI patients aged 15 years and older before, during, and after the COVID-19 epidemic. 2 Methods 2.1 Case definition We conducted this retrospective observational multi-center study from 2019 to 2023.This study included patients from seven sentinel hospitals across urban and rural areas in Shanghai. Patients≥15 years of age who met the World Health Organization (WHO) SARI definitions were eligible for inclusion. SARI was defined as ”a case of acute respiratory infection with fever (measured temperature or previous temperature ≥38°C) and cough that required hospitalization within 10 days of onset”. 2.2 Data Collection Specimens (nasopharyngeal swab, sputum, or other lower respiratory specimen) were collected as the clinical diagnostic examinations were being performed after patients were identified as eligible for ARI surveillance, to carry out further pathogen examination. Healthcare workers at the sentinel hospitals recorded the demographic information, clinical characteristics, and medication status of the included cases sampled from Jan 2019 to Dec 2023. Patients without specimens, or with missing personal information and clinical records, were excluded. 2.3 Pathogen examination The collected specimens were stored at 4°C and then examined 12 respiratory pathogens (22 subtypes) using a real-time reverse transcription polymerase chain reaction (RT-PCR) kit (ResipiFinder 2SMART, PathoFinder, Netherlands) within 24 hours, including influenza virus (IFV, including A(H1N1) pdm09, A(H3N2), B/Yamagata, and B/Victoria), human parainfluenza virus (HPIV, including subtypes 1-4), human adenovirus (HAdV), respiratory syncytial virus (RSV, including subtypes A and B), human rhinovirus/enterovirus (EV/HRV), human coronavirus (HCoV, including types HCoV-OC43, HCoV-NL63, HCoV-HKU1, and HCoV-229E), human metapneumovirus (HMPV), human bocavirus (HBoV), Legionella pneumophila ( L. pneumophila ), Bordetella pertussis ( B. pertussis ), Mycoplasma pneumoniae ( M. pneumoniae ), Chlamydia pneumoniae ( C. pneumoniae ). The specimens were stored at −70°C if they were not examined within 48 hours. 2.4 Statistical Analyses To explore the circulation patterns of etiological and epidemiological features, we defined 3 periods based on the differentiating management levels in response to the COVID-19 epidemic in China between 2019 and 2023: pre-pandemic year (year 2019); COVID-19 pandemic years (year 2020-2022); post-pandemic year (year 2023).The patients were divided into four groups: 15-44 years old, 45-59 years old, 60-74 years old, and ≥75 years old. Descriptive statistics included frequency analysis for categorical variables, medians and IQR for continuous variables. Pearson’s Chi-square test or Fisher’s exact test were performed to compare categorical variables between groups. All the statistical analysis was performed using R version 3.6.3. A two-sided, p value of 3 Results 3.1 Study patients We extracted diagnostic results and epidemiological data of 4738 patients hospitalized with SARI who were tested for the 12 respiratory pathogens between Jan 1, 2019 and Dec 31, 2023, including 1484 in pre-pandemic year (2019), 2043 in COVID-19 years (595 in 2020, 922 in 2021, 526 in 2022), and 1211 in post-pandemic year (2023). A total of 2684 (56.65%) cases were male and 2054 (43.35%) were female. The age of the enrolled patients ranged from 15 to 104 years old, with the median (IQR) age was 71 (IQR:60-83) (Table 1). 3.2 Pattern of pathogen positive rate In total, 21.72% (1029/4738) of the SARI patients who received tests on all the 12 pathogens had at least one positive detection. The overall posivite rate decreased from the pre-pandemic year to the pandemic years by 45.47% (from 30.26% to 16.50%), and then increased by 21.64% (from 16.50% to 20.07%) in the post-pandemic year ( P <0.001) (see Table 2). The positive rate suggested similar percentage levels between genders (23.13% in female vs 20.64% in male), and we observed significantly higher rates in the 15-44 (30.17%) and 45-59 (25.15%) age groups than in the 60-74(19.43%) and 75 years and above (19.97%). We detected a total of 20 subtypes of 11 pathogens except for C. pneumoniae and influenza B/ Yamagata lineage viruses, while IFV (6.29%) demonstrated highest rate, followed by EV/HRV (4.07%), HCoV (2.64%), M. pneumoniae (2.26%), HPIV (2.13%), HMPV (2.03%), RSV (1.35%), HAdV (0.89%), B. pertussis (0.57%), L. pneumophila (0.42%), HBoV (0.21%). In general, the changes in the positive rate of these respiratory pathogens before, during, and after the COVID -19 pandemic showed four patterns: (1) decreased first and then increased (IFV, M. pneumoniae , B. pertussis , HBoV); (2) continuing decreased (HPIV, HCoV, HAdV, EV/HRV, L. pneumophila ); (3) increased first and then decreased (HMPV); (4) continuing increased (RSV). 3.3 Pathogen spectrum The ranking of the pathogenic spectrum positive proportion of the pathogens was consistent with that of positive rate. The most frequently detected respiratory pathogen was IFV (accounting for 27.52% of total positive detection), followed by EV/HRV (17.82%), HCoV (11.54%), M. pneumoniae (9.88%), HPIV (9.33%), HMPV (8.86%), RSV (5.91%), HAdV (3.88%), B. pertussis (2.49%), L. pneumophila (1.85%), HBoV (0.92%) (see Figure 1). It was notable that the rankings of these pathogens were distinct in the three periods. IFV, EV/HRV, and HCoV stayed on the top five positions of the list, while the order changed in different periods. In particular, although the IFV proportion decreased during the COVID-19 years, it became a dominant pathogen after the epidemic. M. pneumoniae and RSV followed and listed on the second and third place, respectively. In contrast, the proportion of HMPV increased significantly during the epidemic years. For the pathogens that were less detected, the proportion of HAdV and HBoV has been decreasing while B. pertussis has been increasing during the three periods. In addition, L. pneumophila was not detected in the post-pandemic year. Further age-specific analysis revealed that IFV and EV/HRV were the most frequently infection types in SARI patients aged 45 years or above. HCoV (13.14%) and M. pneumoniae (10.22%) ranked third and fourth among patients aged 45-59 years, HMPV (12.16%) and HCoV (11.85%) among the aged 60-74 years, and HCoV (13.69%) and HPIV (13.69%) in the group of 75-year-old and/or above. While for 15-44 years of age, M. pneumoniae (24.35%),exceeding IFV (20.19%) and EV/HRV(10.58%), worked as a leading pathogen. 3.4 Time trends and seasonality Varied seasonality was observed among patients with SARI, and the infection such as IFV, RSV, and HMPV, were more likely to occur during winter or spring (see figure 2). The adjustment of COVID-19 prevention and control strategies at the end of 2022 led to the postponement of the influenza season to March 2023. In addition, IFV infection had a small summer peak in August-September. EV/HRV also showed semiannual peaks of activity, with a prominent peak in the spring and early summer (April-July), followed by a smaller or even higher peak in the fall (September-November). M. pneumoniae and HCoV had higher detection rates in autumn and winter, while HPIV showed a peak in summer, with the highest detection rate in June. 3.5 Co-infection pattern of pathogens Co-infection rates of the SARI patients were 1.14% (54/4738), accounted for 5.25% of 1029 pathogen-positive cases. The mixed infection of IFV and M. pneumoniae indicated the highest frequency (20.37%), followed by HCoV infected with HPIV (12.96%) and IFV (11.11%) (see Table 3). 4 Discussion In this study, by using surveillance data on 15-year-old or older hospitalized patients with SARI in the years between 2019 and 2023, we characterized the circulation patterns of the 12 common respiratory pathogens before, during, and after the COVID-19 epidemic in Shanghai. While earlier studies have explored the impacts of COVID-19 Pandemic on ARIs, they have not explicitly addressed its influence on post-pandemic circulation pattern involving multiple respiratory pathogens, especially for adults with SARIs. Our analysis results revealed that the overall positive rate of the respiratory pathogens decreased from 30.26% in the pre-pandemic year to 16.50% during the COVID-19 pandemic years, and then back up to 20.07% in the post-pandemic year, but the change of each pathogen showed four different patterns. On the one hand, dynamic changes in these patterns are informative about the impact of the NPIs as the driver on respiratory infections that share similar transmission modes. Several studies focusing on the long-term impact of NPIs have been conducted on the circulation levels of respiratory infections in North America, Europe, tropical Asia, Japan, and South Korea, where a consistent finding was that influenza decreased 6-9 . We also observed a delay in the influenza epidemic during 2022-23 season. On the other hand, there were researches suggesting that other factors such as respiratory droplet and aerosol routes of transmission, pathogen-to-pathogen interactions, and the immune status of the population might also made a difference in this process. For example, a study found that wearing masks could effectively block the transmission of IFV and HCoV but might be less effective in blocking HRV 10 . It is also reported HRV infection could reduce the risk of suffering IFV attack 11,12 . IFV showed the highest detection rate throughout the reporting period, and influenza A(H1N1) pdm09, A(H3N2) and B/Victoria lineage viruses co-circulated in Shanghai. But influenza B virus (subtype Yamagata) was not detected in our study, which was consistent with the results of WHO surveillance. Globally, no confirmed naturally occurring B/Yamagata lineage virus has been detected yet since March 2020, making it the only respiratory virus pushed towards extinction by the emergence of SARS-CoV-2 13,14 . However, since the different regions are unevenly covered by respiratory virus surveillance systems, some caution is warranted in considering the B/Yamagata lineage actually to be extinct, or might reappearance globally at some point like the B/Victoria lineage (which happened in 2001–02) 15 .In this context, this field needs more surveillance and studies on sequencing of influenza viruses for tracking changes in epidemiological characteristics and a timely revision in influenza prevention practices, particularly with respect to the composition of vaccines. In February, 2024, the WHO influenza vaccine composition advisory committee declared “that the B/Yamagata lineage antigen should be excluded from influenza vaccines as it is no longer warranted. National or regional authorities should make decisions regarding the transition to trivalent influenza vaccines in their jurisdictions.” (this decision applies to vaccines for the 2024–25 season in the northern hemisphere) 13 . Currently, although the domestic vaccine manufacturers such as Hualan Vac and Sinovac Biotech Co., Ltd. also have licensed trivalent influenza vaccine, they may still transition steadily with the quadrivalent vaccine. In addition, there are manufacturers that only provided trivalent influenza vaccine, such as Changchun BCHT Biotechnology Co. (nasal injection reduction), Zhongyianke Biotech Co., Ltd.etc 16 . M. pneumoniae was identified as the leading pathogen in 15-44 years of age. There was no vaccine that were designed to against M. pneumoniae, macrolides, ketolactones and tetracyclines in clinical treatment. Macrolides were recommended as the first choice for the treatment of M.pneumoniae pneumonia on children in China 17 . However, since 2000, the macrolide-resistant M. pneumoniae (MRMP) has been applied in multiple regions across Asia, and the report revealed that more than 80% of clinical isolates of M. pneumoniae from Beijing and Shanghai were macrolide resistant 18,19 . China have suffered a concurrent outbreak of paediatric respiratory diseases in 2023, particularly the MRMP outbreak. A study found that EC2 clones showed 100% macrolide resistance because of the acquisition of the A2063G mutation in 23S rRNA, and suggested that without the restrictions enacted during the COVID-19 pandemic, the MRMP clones could have caused outbreaks across the country as early as 2020 20,21 . There is a wide variety of respiratory pathogens, coinfections between different pathogens are common. A study reported that multiple (≥2) respiratory viruses were observed in 1.6% (94/5808) of the participated adults with acute respiratory tract infections in Beijing, among them, HRV was the most frequently found viral agents in co-infections, followed by IFVA and PIV 22 . In our study, IFV- M . pneumoniae and HCoV-HPIV co-infections were common. The coexistence of SARS-CoV-2 and other respiratory pathogens was also found in our previous studies 23,24 .Perhaps due to the damage to patients with ARIs, they are also vulnerable to the invasion of other pathogens, but it is not rule out the amplification of residual genetic material from previous infections or from persistent viruses 25,26 . The clinical significance of such co-detection is unclear. To date, observational studies have reported three distinctive associations between coinfection and clinical outcomes, including improved, deteriorated, and no effect 27 . These contradictory results imply a complicated mechanism on how coinfection affects risk for critical outcomes, and it is exactly where further researches are urgently needed. Our study was subject to several limitations. First, a high proportion of the participants aged 60 years and older; the usage of antibiotics or antiviral drugs prior to treatment might lead to an underestimation of the detection rate, although it seemed to be common to surveillance studies with similar study designs 28,29 . Second, the COVID-19 pandemic might have substantially changed healthcare-seeking behavior of patients with SARIs, there might be sampling bias as the samples in this study were obtained from sentinel hospitals. But given that the inclusion/exclusion criteria for the testing stayed the same during and after the pandemic, also, our analyses were based on test-positive rates, which should be less sensitive to healthcare-seeking behavior. Third, causal relationships cannot be inferred from the surveillance data. Especially for bacterial pathogens, a positive result cannot tell whether it is a colonization or an invasive infection. 5 Conclusion In summary, Circulation of the common respiratory pathogens changed from 2019 to 2023,COVID-19 pandemic has affected the epidemiological characteristics of other respiratory pathogens to a certain extent. It is necessary to be alert to outbreak or epidemic of certain pathogens, as well as the risk of co-epidemic of multiple respiratory pathogens. Unfortunately, infection of all these pathogens, except IFV and B. pertussis, are not yet notifiable infectious diseases in China, and there were no commercially available vaccines provided. Therefore, it is now more important to strengthen the surveillance of multiple pathogens than ever and will remain so for many years to come, which will be helpful in applying differential diagnosis, identifying significant public health risks, and improving prevention control. Author Contributions Qi Qiu: data curation, investigation, formal analysis, writing – original draft. Huilin Shi: data curation, formal analysis, writing – original draft. Chenyan Jiang: investigation, formal analysis. Zheng Teng: investigation, laboratory test. Jiajing Liu: investigation, laboratory test. Huanyu Wu: writing – review and editing .Yaxu Zheng: conceptualization, writing – review and editing, visualization. Jian Chen: conceptualization, writing – review and editing, visualization. Acknowledgments We extend our sincere appreciation to every healthcare professional involved in diagnosing and treating SARIs, as well as those contributing to SARI network reporting. Additionally, we express our gratitude to the laboratory physicians for their invaluable support in diagnosing SARIs. We also thank the staff members at the Bureau of Disease Control and Prevention, the Shanghai Municipal Health Commission, and local health departments for their assistance in coordinating data collection. We appreciate the efforts of staff members at the county and prefecture levels of CDCs for their contributions to data collection. Ethics Statement This study was approved by the ethics review committees of Shanghai Municipal Center for Disease Control and Prevention (KY-2024-21). Conflicts of Interest The authors declare no conflicts of interest. Data availability statement The datasets analyzed during the current study are not publicly available due to the reason that these data came from a long-term surveillance but are available from the corresponding author on reasonable request. References 1. GBD. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 2020; 396 (10258): 1204-22.2. Zhu N, Zhang D, Wang W, et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med 2020; 382 (8): 727-33.3. Liu P, Xu M, Cao L, et al. Impact of COVID-19 pandemic on the prevalence of respiratory viruses in children with lower respiratory tract infections in China. Virol J 2021; 18 (1): 159.4. Li ZJ, Yu LJ, Zhang HY, et al. Broad impacts of COVID-19 pandemic on acute respiratory infections in China: an observational study. Clin Infect Dis 2021.5. Kong D, Zheng Y, Hu L, et al. Epidemiological and co-infection characteristics of common human coronaviruses in Shanghai, 2015-2020: a retrospective observational study. Emerg Microbes Infect 2021; 10 (1): 1660-8.6. Olsen SJ, Azziz-Baumgartner E, Budd AP, et al. Decreased Influenza Activity During the COVID-19 Pandemic - United States, Australia, Chile, and South Africa, 2020. MMWR Morb Mortal Wkly Rep 2020; 69 (37): 1305-9.7. Mott JA, Fry AM, Kondor R, Wentworth DE, Olsen SJ. Re-emergence of influenza virus circulation during 2020 in parts of tropical Asia: Implications for other countries. Influenza Other Respir Viruses 2021; 15 (3): 415-8.8. Yum S, Hong K, Sohn S, Kim J, Chun BC. Trends in Viral Respiratory Infections During COVID-19 Pandemic, South Korea. Emerg Infect Dis 2021; 27 (6): 1685-8.9. Sakamoto H, Ishikane M, Ueda P. Seasonal Influenza Activity During the SARS-CoV-2 Outbreak in Japan. Jama 2020; 323 (19): 1969-71.10. Leung NHL, Chu DKW, Shiu EYC, et al. Respiratory virus shedding in exhaled breath and efficacy of face masks. Nat Med 2020; 26 (5): 676-80.11. Nickbakhsh S, Mair C, Matthews L, et al. Virus-virus interactions impact the population dynamics of influenza and the common cold. Proc Natl Acad Sci U S A 2019; 116 (52): 27142-50.12. Wu A, Mihaylova VT, Landry ML, Foxman EF. Interference between rhinovirus and influenza A virus: a clinical data analysis and experimental infection study. Lancet Microbe 2020; 1 (6): e254-e62.13. Organization WH. Recommended composition of influenza virus vaccines for use in the 2024-2025 northern hemisphere influenza season. 2024.14. Caini S, Meijer A, Nunes MC, et al. Probable extinction of influenza B/Yamagata and its public health implications: a systematic literature review and assessment of global surveillance databases. The Lancet Microbe 2024; 5 (8).15. Ikonen N, PyhÄLÄ R, Axelin T, Kleemola M, Korpela H. Reappearance of influenza B/Victoria/2/87-lineage viruses: epidemic activity, genetic diversity and vaccination efficacy in the Finnish Defence Forces. Epidemiology and Infection 2005; 133 (2): 263-71.16. National Immunization Advisory Committee (NIAC) Technical Working Group (TWG) IVT. Technical guidelines for seasonal influenza vaccination in China (2023-2024). Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44 (10): 1507-30.17. China NHCotPsRo. Guidelines for Diagnosis and Treatment of Mycoplasma Pneumonae Pneumonia in Children (2023 Edition). 2023.18. Xin D, Mi Z, Han X, et al. Molecular Mechanisms of Macrolide Resistance in Clinical Isolates of Mycoplasma pneumoniae from China. Antimicrobial Agents and Chemotherapy 2009; 53 (5): 2158-9.19. Liu Y, Ye X, Zhang H, et al. Antimicrobial Susceptibility of Mycoplasma pneumoniae Isolates and Molecular Analysis of Macrolide-Resistant Strains from Shanghai, China. Antimicrobial Agents and Chemotherapy 2009; 53 (5): 2160-2.20. Li H, Li S, Yang H, Chen Z, Zhou Z. Resurgence of Mycoplasma pneumonia by macrolide-resistant epidemic clones in China. Lancet Microbe 2024.21. Meyer Sauteur PM, Beeton ML. Mycoplasma pneumoniae: delayed re-emergence after COVID-19 pandemic restrictions. Lancet Microbe 2024; 5 (2): e100-e1.22. Ren L, Gonzalez R, Wang Z, et al. Prevalence of human respiratory viruses in adults with acute respiratory tract infections in Beijing, 2005-2007. Clin Microbiol Infect 2009; 15 (12): 1146-53.23. Qiu Q, Wu HY, Shi HL, et al. Analysis of parainfluenza virus infection in acute respiratory tract infection adult cases in Shanghai, 2015-2021. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44 (10): 1628-33.24. Qiu Qi KD, Teng Zheng, Zhou Yanqiu, Chen Hongyou, Zhang Xi, Chen Jian, Zheng Yaxu, Jiang Xianjin, Yuan Shiying, Wu Huanyu, Pan Hao, Sun Xiaodong. Features of severe acute respiratory syndrome coronavirus 2 co-infected with other common respiratory pathogens in Shanghai City, 2020-2021. Chin J Infect Dis 2023; 41 (4): 249-54.25. Larcher C, Jeller V, Fischer H, Huemer HP. Prevalence of respiratory viruses, including newly identified viruses, in hospitalised children in Austria. Eur J Clin Microbiol Infect Dis 2006; 25 (11): 681-6.26. Jartti T, Lehtinen P, Vuorinen T, Koskenvuo M, Ruuskanen O. Persistence of rhinovirus and enterovirus RNA after acute respiratory illness in children. J Med Virol 2004; 72 (4): 695-9.27. Guan Z, Chen C, Li Y, et al. Impact of Coinfection With SARS-CoV-2 and Influenza on Disease Severity: A Systematic Review and Meta-Analysis. Front Public Health 2021; 9 : 773130.28. Jain S, Self WH, Wunderink RG, et al. Community-Acquired Pneumonia Requiring Hospitalization among U.S. Adults. N Engl J Med 2015; 373 (5): 415-27.29. Li ZJ, Zhang HY, Ren LL, et al. Etiological and epidemiological features of acute respiratory infections in China. Nat Commun 2021; 12 (1): 5026. Tables Table 1. Demographic characteristics of the participants before, during, and after the COVID-19 pandemic Characteristics Pre-pandemic year (2019), n=1484 COVID-19 pandemic years (2020-2022), n=2043 Post-pandemic year (2023), n=1211 Total (2019-2023), N=4738 Gender Male 795 (53.57) 1198 (58.64) 691 (57.06) 2684 (56.65) Female 689 (46.43) 845 (41.36) 520 (42.94) 2054 (43.35) Age, yrs (Median, IQR) 71 (59,84) 71 (62,84) 69 (59,78) 71 (60,83) Age group 15-44y 227 (15.3) 251 (12.29) 165 (13.63) 643 (13.57) 45-59y 154 (10.38) 198 (9.69) 149 (12.3) 501 (10.57) 60-74y 433 (29.18) 720 (35.24) 473 (39.06) 1626 (34.32) 75y and above 670 (45.15) 874 (42.78) 424 (35.01) 1968 (41.54) Table 2 . Comparison of patients’ characteristics and pathogen positive rates before, during, and after the COVID-19 pandemic Pre-pandemic year (2019) COVID-19 pandemic years (2020-2022) Post-pandemic year (2023) Total (2019-2023) χ2 P value Positive rates (%) 30.26 (449/1484) 16.5 (337/2043) 20.07 (243/1211) 21.72 (1029/4738) 98.352 <0.001 Gender 4.081 0.043 Male 28.55 (227/795) 14.86 (178/1198) 21.56 (149/691) 20.64 (554/2684) Female 32.22 (222/689) 18.82 (159/845) 18.08 (94/520) 23.13 (475/2054) Age group 15-44y 39.21(89/227) 23.90(60/251) 27.27(45/165) 30.17(194/643) 29.872 <0.001 45-59y 27.92(43/154) 22.73(45/198) 25.5(38/149) 25.15(126/501) 7.257 0.007 60-74y 28.18(122/433) 14.58(105/720) 18.82(89/473) 19.43(316/1626) - - 75y and above 29.1(195/670) 14.53(127/874) 16.75(71/424) 19.97(393/1968) 0.129 0.719 IFV 8.49 (126/1484) 3.28 (67/2043) 8.67 (105/1211) 6.29 (298/4738) 55.251 <0.001 A (H1N1) pdm09 4.92 (73/1484) 0.29 (6/2043) 4.79 (58/1211) 2.89 (137/4738) 86.366 <0.001 A (H3N2) 1.82 (27/1484) 0.88 (18/2043) 3.88 (47/1211) 1.94 (92/4738) 36.109 <0.001 B/Victoria ** 1.75 (26/1484) 2.11 (43/2043) 0.00 (0/1211) 1.46 (69/4738) - <0.001 EV/HRV 5.93 (88/1484) 4.16 (85/2043) 1.65 (20/1211) 4.07 (193/4738) 31.307 <0.001 HCoV 3.37 (50/1484) 2.79 (57/2043) 1.49 (18/1211) 2.64 (125/4738) 9.526 0.009 OC43 1.15 (17/1484) 1.08 (22/2043) 0.74 (9/1211) 1.01 (48/4738) 1.222 0.543 NL63 ** 1.35 (20/1484) 1.03 (21/2043) 0.00 (0/1211) 0.87 (41/4738) - <0.001 229E 0.67 (10/1484) 0.69 (14/2043) 0.74 (9/1211) 0.70 (33/4738) 0.053 0.974 HKU1 ** 0.47 (7/1484) 0.25 (5/2043) 0.00 (0/1211) 0.25 (12/4738) - 0.048 M. pneumoniae 4.31 (64/1484) 0.54 (11/2043) 2.64 (32/1211) 2.26 (107/4738) 56.561 <0.001 HPIV 3.91 (58/1484) 1.32 (27/2043) 1.32 (16/1211) 2.13 (101/4738) 32.693 <0.001 HPIV-3 2.49 (37/1484) 0.83 (17/2043) 1.07 (13/1211) 1.41 (67/4738) 18.368 0.001 HPIV-1 ** 0.61 (9/1484) 0.29 (6/2043) 0.00 (0/1211) 0.32 (15/4738) - 0.012 HPIV-2 * 0.40 (6/1484) 0.20 (4/2043) 0.17 (2/1211) 0.25 (12/4738) 1.980 0.372 HPIV-4 ** 0.40 (6/1484) 0.0 (0/2043) 0.08 (1/1211) 0.15 (7/4738) - 0.003 HMPV 1.69 (25/1484) 2.59 (53/2043) 1.49 (18/1211) 2.03 (96/4738) 5.971 0.051 RSV 1.08 (16/1484) 1.17 (24/2043) 1.98 (24/1211) 1.35 (64/4738) 4.922 0.085 RSV-B 0.61 (9/1484) 1.08 (22/2043) 0.41 (5/1211) 0.76 (36/4738) 5.119 0.077 RSV-A * 0.47 (7/1484) 0.10 (2/2043) 1.57 (19/1211) 0.59 (28/4738) 28.530 <0.001 HAdV 1.62 (24/1484) 0.59 (12/2043) 0.50 (6/1211) 0.89 (42/4738) 13.208 0.001 B. pertussis 0.47 (7/1484) 0.39 (8/2043) 0.99 (12/1211) 0.57 (27/4738) 5.188 0.075 L. pneumophila ** 1.08 (16/1484) 0.20 (4/2043) 0.00 (0/1211) 0.42 (20/4738) - <0.001 HBoV * 0.34 (5/1484) 0.15 (3/2043) 0.17 (2/1211) 0.21 (10/4738) 1.638 0.441 C. pneumoniae and influenza B virus (subtype Yamagata) were not detected. * Adjusted Chi-squared test ** Fisher’s exact test Table 3. Co-infection pattern of pathogens in patients with SARI in Shanghai, 2019-2023. Co-infection No. of cases (%) IFV+ M. pneumoniae 11 (20.37) HCoV +HPIV 7 (12.96) HCoV+IFV 6 (11.11) HAdV+ B. pertussis 3 (5.56) IFV+HPIV 3 (5.56) IFV+EV/HRV 3 (5.56) HCoV+EV/HRV 3 (5.56) HMPV+EV/HRV 3 (5.56) RSV+ L. pneumophila 2 (3.70) IFV+RSV 2 (3.70) HPIV+ L. pneumophila 1 (1.85) HCoV+ L. pneumophila 1 (1.85) IFV+HAdV 1 (1.85) IFV+HMPV 1 (1.85) HCoV+HAdV 1 (1.85) HCoV+RSV 1 (1.85) HCoV+HMPV 1 (1.85) HCoV+HBoV 1 (1.85) HPIV+HBoV 1 (1.85) HPIV+EV/HRV 1 (1.85) HAdV+EV/HRV 1 (1.85) Total 54 (100.00) Figure 1. Pathogen composition of patients with SARI in Shanghai, 2019‒2023. The overall pathogen composition of 1029 SARI patients who had all the 12 pathogens detected. The length of colored bars and the number behind indicate the proportion of each pathogen, calculated by its positive number used as the numerator and the total positive number of all pathogens used as the denominator. Figure 2 . Seasonal patterns of 11 respiratory pathogens before, during, and after the COVID-19 pandemic. Each panel showed the positive rate of a specific pathogen from January to December during 2019-2023. Information & Authors Information Version history V1 Version 1 07 January 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords co-infection influenza virus mycoplasma pneumonia pathogen spectrum severe acute respiratory infection Authors Affiliations Qi Qiu 0009-0003-2156-7401 Shanghai Municipal Center for Disease Control and Prevention View all articles by this author Huilin Shi Shanghai Institute of Preventive Medicine View all articles by this author Chenyan Jiang Shanghai Institute of Preventive Medicine View all articles by this author Zheng Teng Shanghai Municipal Center for Disease Control and Prevention View all articles by this author Jiajing Liu Shanghai Municipal Center for Disease Control and Prevention View all articles by this author Huanyu Wu Shanghai Municipal Center for Disease Control and Prevention View all articles by this author Yaxu Zheng Shanghai Municipal Center for Disease Control and Prevention View all articles by this author JIAN CHEN 0000-0002-6685-3503 [email protected] Shanghai Institute of Preventive Medicine View all articles by this author Metrics & Citations Metrics Article Usage 318 views 196 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Qi Qiu, Huilin Shi, Chenyan Jiang, et al. 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