Large and medium-sized cities have a concentrated population, obvious seasonal climate, and high incidence of respiratory infectious diseases. This study focused on monitoring multiple respiratory pathogens in feverish populations in Nanjing communities to establish a respiratory pathogen spectrum and fill the gap in acute respiratory infectious disease monitoring after the cessation of NPIs. The study showed that from week 42 (October 2023), there was a rapid increase in positive pathogen samples, maintaining a stable and high positive detection rate, dropping in December, and then showing a growth trend until early February 2024. This study conducted molecular epidemiological research on respiratory pathogens to identify the currently dominant genotypes, which contributes to a deeper understanding of the epidemiological characteristics of different pathogens, including their transmission routes, infectivity, and seasonal distribution. The overall positive detection rate in this study was 53.57%, with high detection rates for Flu A and Flu B (24.00% and 10.95%, respectively). All Flu A subtypes were H3N2, while all Flu B subtypes were B/Victoria lineage. Influenza viruses showed a peak in winter and spring, with Flu A prevalent from October to January and Flu B prevalent from December to February, consistent with research in Beijing[15]. However, the high detection rate of influenza viruses in our study indicates a serious influenza situation in our city.
HRV was prevalent from August to October, consistent with research in Taizhou[16]. This study conducted typing tests on simple infection of rhinoviruses and enteroviruses, detecting a total of 18 strains of rhinovirus A, including 3 of type A21, 2 of type A64, 2 of type A7, 1 of type A71, and 3 of type A98, as well as 3 strains of rhinovirus B, including 1 of type B69, and 17 strains of rhinovirus C, including 2 of type C1. It can be observed that the detection rates of HRV A and C types are relatively high, consistent with domestic and international research results[17–18]. HRV-A and HRV-C are more likely to cause moderate to severe diseases, and type C is associated with childhood asthma attacks. Therefore, strengthening the monitoring of rhinovirus typing is of great significance for the prevention and control of respiratory infectious diseases. In enteroviruses, a total of 3 strains of coxsackievirus A6, 1 strain of coxsackievirus A21, and 1 strain of enterovirus D68 were detected. Coxsackievirus A6 has become one of the main pathogens causing human hand-foot-and-mouth disease in recent years. While coxsackievirus A21 and enterovirus D68 can also enter the body through the respiratory tract, they rarely cause hand-foot-and-mouth disease and herpangina, mainly manifesting as symptoms of upper respiratory tract infections. HPIV, HCoV, HSV, EV, and HADV showed short-term low prevalence. Among them, HPIV is mainly type HPIV-3, and among the four serotypes, the infection rate of HPIV-3 is the highest, often peaking in the winter and spring seasons, consistent with previous research findings [19]. HCoV mainly invaded the upper respiratory tract with HCoV-OC43 and HCoV-229E types. HMPV, H. influenzae, S. pneumoniae, and C. pneumoniae had relatively low annual detection rates, appearing sporadically. However, due to the short duration of our study and the lack of coverage in the spring, it is not sufficient to fully describe the common respiratory pathogen prevalence characteristics in the region, requiring further supplementation in the future.
Mixed infections of pathogens may pose challenges to the diagnosis, treatment, and epidemic prevention and control of respiratory infections. Concurrent or sequential infection of respiratory pathogens may lead to mixed infections, causing positive synergistic or negative antagonistic interactions among pathogens, leading to varying degrees of disease severity changes in patients. In this study, mixed infections accounted for 11.45% of total positive cases, with Flu A mostly co-infected with other pathogens, and the highest positive detection rates in mixed infections were observed for Flu A + HRV, FluA + HCoV, FluA + HSV. Previous studies suggested negative interactions between IAV and RSV, HRV and IAV, while RSV and HRV co-infections indicated increased disease severity[20]. Previous studies have shown that [21],co-infections may lead to an increased hospitalization rate among patients with respiratory viral infections, indicating an escalation in disease severity. This study conducted a comparative analysis of single infections and co-infections based on gender, different age groups, Ct values, and the number of symptoms. The results ultimately revealed statistically significant differences between single infections and co-infections across different age groups. The lack of statistical significance in symptom numbers may be due to the challenge of deriving conclusions about severity solely based on symptom counts. HRV, HSV, M. Pneumoniae, and S. pneumoniae in mixed infections had smaller Ct values compared to single infections, possibly due to synergistic effects between pathogens, resulting in increased disease severity. The Ct value for HSV single infection was 34.57, while for mixed infection, it was 32.55, with significant differences and higher persuasiveness. However, HADV and HMPV single infection had larger Ct values, possibly related to their role as primary infecting viruses activating the host's non-specific innate immune response. Due to the short study period and relatively low number of mixed infection cases, significant results could not be obtained. Viral interference may provide a new model for antiviral treatment research. Some studies have shown that Influenza A virus Defective Interfering Particles (IAV-DIPs) can stimulate the host's innate immune system to inhibit HSV infection and replication[22], suggesting a potential preventive and therapeutic role in respiratory infectious diseases. There is limited research in China in this area, and future monitoring of more data can lead to further research. Subsequent follow-up tracking or research based on hospital cases could further investigate this matter.
Starting from January 2023, China lifted the control measures for COVID-19 from Class A infectious diseases. This study was conducted from June 2023 to the end of February 2024, after comprehensive relaxation of epidemic control measures. The aim was to explore the changes in the respiratory pathogen spectrum after the cessation of NPIs. Since the emergence of COVID-19, China has implemented non-pharmaceutical interventions (NPIs) including encouraging mask-wearing, patient isolation, social distancing, hand hygiene, and disinfection to prevent new SARS-CoV-2 infections. Comparing the spectrum of respiratory pathogens in Jinan City and Beijing City during NPIS period with that in this study, the overall positive detection rate of pathogens in this study (54.15%) was significantly higher than that in Jinan City (40.18%) and Beijing (10.97%), indicating that NPIS measures against COVID-19 greatly reduced the prevalence of respiratory pathogens. Furthermore, the detection rate of influenza in this study was 34.95% ((24.00% + 0.95%), which was significantly higher than 3.44% in Jinan City and 1.5% in Beijing City, and the positive detection rate of all pathogens in this study was higher than that in Beijing city, possibly because NPIS measures during COVID-19 not only prevented the invasion of viruses but also cut off the transmission of other respiratory pathogens. However, the overall positive rate of respiratory pathogens is rising, which may be linked to the public's relaxation of vigilance against respiratory infectious diseases, and may also be related to the immune debt after the novel coronavirus pandemic, resulting in a rebound or high epidemic level of some infectious diseases. However, during NPIS, the positive rate of HRV pathogens in Jinan City was 9.85%, higher than 8.7% in this study, which may be since HRV is transmitted through direct or indirect contact with contaminated items, which requires chlorine-based disinfectants to eradicate, and the use of ethanol is less effective. In addition, the positive rates of Mycobacterium pneumoniae and respiratory syncytial virus in Jinan were significantly higher than in our study, which may be due to the fact that our study focussed on community populations rather than hospital-based studies, and that Jinan has a higher proportion of children under the age of 15, who are more susceptible to these pathogens.
In recent years, there has been extensive research in China utilizing the ARIMA model for infectious disease surveillance and prediction, demonstrating its effectiveness, particularly in short-term forecasting[23–24]. Based on the scientifically predicted results of the model, early detection of respiratory pathogen trends can be achieved, providing timely warnings for control efforts and facilitating the targeted formulation of prevention and control strategies. In this study, fitting models were established using the ARIMA model (0,1,4), (0,0,0) based on influenza surveillance data from June 2023 to February 2024. According to the forecast results of the ARIMA model, influenza peaks are expected to occur in late autumn and winter of 2023, with the number of detected respiratory pathogens projected to decline initially from March to June 2024 before stabilizing. This trend may be attributed to the rising temperatures during the spring and summer seasons. Nanjing, characterized by a subtropical monsoon climate, experiences a noticeable temperature increase by the end of February along with high humidity and rainfall. Studies have indicated that the transmission of respiratory viruses is associated with climate conditions, especially humidity and temperature, with respiratory pathogens being more likely to spread under cold and dry conditions[25]. Additionally, this study has certain limitations as it only considers the quantity of detected pathogens, potentially leading to underreporting or overreporting biases in weekly data.
Overall, our study monitored respiratory infections in the community population of Nanjing City, providing insights into the spectrum and co-infections of respiratory pathogens., A time series forecasting model has been established to serve as a reference for prevention and control efforts. While filling gaps in Nanjing's respiratory pathogen spectrum research, our study has limitations due to a short period and single sample source. Future research could involve hospital samples to further understand the epidemiology of respiratory pathogens, establish a more comprehensive pathogen spectrum, and enhance Nanjing's monitoring and alert system post-COVID-19 pandemic.