We enrolled 8979 patients with suspected ARTIs who were hospitalised in Shijiazhuang Second Hospital from December 2019 to December 2023. The inclusion criteria were the following: (1) disease duration less than 3 days accompanied by cough or sore throat, nasal congestion, runny nose, sputum and other upper respiratory tract symptoms; (2) complete data. The exclusion criteria were the following: (1) acute respiratory inflammation caused by non-infectious factors; (2) parenchymatous organs or haematopoietic stem cell transplantation, immunodeficiency diseases such as human immunodeficiency virus infection, and cancer chemotherapy; and (3) incomplete data or patients not agreeing to participate in this study. This study was approved by the Ethics Committee of Shijiazhuang Second Hospital, and oral informed consent was obtained from all patients.

Demographic data were collected from the laboratory information system, including sex, age, clinical diagnosis, date of hospitalisation and date of pathogen testing. Nasopharyngeal swab samples were collected by professional clinicians and submitted for examination within 2 h. The collection of clinical data was de-identified and anonymous.

A nucleic acid extraction BD-Micro kit (ZD Biotech, Zhejiang, China) was used to extract nucleic acid according to the manufacturer’s instructions. Multiple detection kits for 13 respiratory pathogens (ZD Biotech, Zhejiang, China) were used for respiratory pathogen detection. The multiple reverse transcription–PCR (mRT–PCR) reaction system and procedure are described in the kit instructions. The mRT–PCR products were separated in the GenomeLab™ GeXP (Beckman Coulter, USA) platform according to fragment size and migration rate and were analysed using the fluorescence signal intensity data. The 13 pathogens included Influenza A viru (InfA), Influenza A virus H1N1 (InfAH1N1), Seasonal Influenza virus H3N2 (H3), Influenza B virus (InfB), Human Adenovirus (HADV), Boca virus (Boca), Human Rhinovirus (HRV), Human Parainfluenza virus (HPIV), Human Coronavirus (HCOV), Human Respiratory Syncytial virus (HRSV), Human Metapneumovirus (HMPV), Mycoplasma Pneumoniae (MP) and Chlamydia (Ch). Quality control was performed during pathogen testing.

The SPSS 21.0 statistical software and GraphPad Prism 5 were used to process and analyses the data. Categorical variables were compared using the chi-square test or Fisher’s exact test. A bilateral P value of <0.05 was considered statistically significant. The base, tseries, forecast and other software packages of R4.0.3 were used to construct the ARIMA prediction model for time series analysis, and the smaller the MAPE value was, the better was the fitting effect. Positive rate or positive detection rate refers to the frequency of positive detections. Positive proportion refers to the positive detection of a pathogen in the positive detection of all 13 pathogens. Positive cases refers to the number of positive patients.

A total of 8979 cases were collected from inpatients with ARTIsadmitted to the hospital, of whom 4801 (53.47%) were males and 4178 (46.53%) were females. The patient age range was from 9 months to 105 y. The socio-demographic variables are summarised in Table 1 . A total of 4169 cases tested positive for respiratory pathogens, and the total positive detection rate was 46.43% (4169/8979). The positive detection rate of the InfAH1N1 virus and total infection rate in males were significantly higher than those in females (1.7% vs. 1.0%, P = 0.004; 24.15% vs. 22.29%, P = 0.020), and the positive detection rate of the H3 virus in females was significantly higher than that in males (9.3% vs. 7.9%, P = 0.042). The total pathogen detection rate was highest in the age group of 0–4 y (102.1%). With the exception of InfAH1N1, HCOV and Ch, there were significant differences in pathogen detection rates among different age groups (P < 0.001).

In December 2019, the first pandemic strain 19A was found in Wuhan, China, and since then, China’s epidemic prevention and control has started. China launched an emergency management mechanism for the first time and began to implement strict epidemic prevention and control measures until December 2022,when the State Council’s epidemic prevention measures to optimise the ‘new 10’ (Rongfeng et al., 2024). Therefore, we collected data for 3 y during the COVID-19 outbreak and for 1 y after the COVID-19 pandemic, as shown in Figure 1 .

The number of pathogens detected in the first 3 y ranged from 1000 to 2000 and rebounded to more than 4,600. The positive detection rates of InfA, InfAH1N1, H3, HRV, HPIV, HMPV and MP were significantly different among the four time periods, which were all higher from December 2022 to December 2023 than from the other three time periods, except for HRV (P < 0.01) ( Figure 1A ). From December 2019 to November 2020, the main pathogenic infections were InfA, H3 and HRV; from December 2020 to November 2021, the pathogenic infection was mainly HRV; from December 2021 to November 2022, the main pathogenic infections were InfB and HRV; and from December 2022 to December 2023, the pathogenic infections were mainly InfA, H3 and MP ( Figure 1B ).

We analysed the monthly distribution of respiratory pathogens by gender and during and after the COVID-19 outbreak in the study period, as shown in Figure 2 . In the four time periods, there was no significant difference in the positive rates of males and females. In the first year of the pandemic, the positive rate of males was highest in December (75.31%) and lowest in July (4.44%), and the positive rate of females was highest in January (78.43%) and lowest in June (1.79%) ( Figure 2A ). In the second year, the positive rate of males was highest in October (30.16%) and lowest in March (4.00%), and the positive rate of females was highest in October (28.00%) and lowest in February (0.00%). The highest positivity rates for males and females were much lower than those in the first year ( Figure 2B ). In the third year, the positive rate of males was highest in January (25.00%) and lowest in July (10.00%), and the positive rate of females was highest in December (40.98%) and lowest in July (6.67%) ( Figure 2C ). In the fourth year, the positive rates were higher in spring and winter than in summer and autumn. The positive rate of males was highest in December (58.54%) and lowest in January (0.93%). The positive rate of females was highest in October (60.53%) and lowest in January (0.00%). The total positive rate of males was significantly higher than that of females (P < 0.001) ( Figure 2D ).

We then statistically analysed the changes in pathogen positive rates (only one count of overlapping infections) and positive detection rates (including overlapping infections) during and after the COVID-19 pandemic. From December 2019 to November 2022, the positive rate of pathogens showed a downwards trend without seasonal dependence, and from December 2022 to December 2023, the positive rate of pathogens showed an upwards trend and the positive rates in spring and winter were higher than those in summer and autumn ( Figure 2E ). The positive detection rate of pathogens showed the same trend ( Figure 2F ). These results suggest that an increase in pathogen positive rates is accompanied by an increase in overlapping infections.

The monthly distribution of each respiratory pathogen during and after the COVID-19 pandemic is shown in Figure 3 . During the COVID-19 pandemic, the peak of InfA and H3 virus infection occurred in winter (January and December) and the lowest activity was in spring and summer (from March to July). There was no clear seasonal distribution for HRV, and infections were high throughout the year ( Figure 3A ). However, as shown in Figure 3C , it can be seen that the higher number of infections in December was mainly contributed by December 2019. After the COVID-19 pandemic, InfA and H3 virus infections peaked in spring (March) and winter (October), with the lowest activity in summer and autumn (from May to September). MP dramatically increased in winter (from October to November). HRV infection increased significantly in autumn and winter (from September to November). HRSV had a small increase in April and May. The number of positive samples for the other pathogens was smaller but significantly higher than that during the COVID-19 pandemic, and the peak of infection was also in autumn and winter ( Figure 3B ). However, as shown in Figure 3D , it can be seen that because of the seasonal advantage of winter, the number of pathogenic infections in December 2023 was still increasing dramatically. Since the first positive case of COVID-19 was found in Shijiazhuang (also Hebei Province) in January 2020, and nucleic acid inspection was lifted from January 2023, and according to the actual monthly change distribution of respiratory viruses, we strictly referred to the 2020.01-2022.12 as 3 y of pandemic, and the 2023.01-2023.12 as 1 y after the pandemic.

During the COVID-19 pandemic, the total number of positive pathogens was 1217 and the dominant pathogens were InfA and HRV, accounting for 24.08% and 21.77% of the total number of positive pathogens, respectively, followed by H3, accounting for 10.35% ( Figure 3E ). After COVID-19 pandemic, the total number of positive pathogens was 2711 and the dominant pathogens were InfA and H3, accounting for 27.92% and 21.17% of the total number of positive pathogens, respectively, followed by MP, accounting for 13.02% ( Figure 3F ). Both during and after the COVID-19 pandemic, InfA/H3 had the highest proportion of co-infection among all tested samples, respectively, accounting for 35.13% (124/353) and 58.81% (574/976), which was not shown in the figure because it was much higher than the other co-infections ( Figure 3G ).

During the COVID-19 pandemic, male and female positive samples accounted for 49.83% and 50.17%, respectively, and the difference was not statistically significant (P = 0.861) ( Figure 4A ). After the COVID-19 outbreak, the proportion of males in positive samples was significantly higher than that of females (53.78% vs. 46.22%, P = 0.001) ( Figure 4B ). During the COVID-19 pandemic, HRV and InfA were the main pathogens in males. InfA and HRV were the main pathogens in females ( Figure 4C ). After the COVID-19 pandemic, the main pathogens in males and females were InfA, H3 and MP. The proportions of InfA, H3 and MP in males were higher than those in females ( Figure 4D ). The number of positive samples in all age groups was higher after the COVID-19 outbreak than during the pandemic ( Figure 4E ). During the COVID-19 pandemic, InfA and HRV frequently occurred in all age groups. HRSV infection also frequently occurred in the age group of 0–4 y, and InfB and MP infections frequently occurred in the age group of 19–49 y and were much higher than those in the other age groups ( Figure 4F ). After the COVID-19 pandemic, InfA and H3 frequently occurred in all age groups. HRSV infection also frequently occurred in the age group of 0–4 y, and MP infection frequently occurred in the age group of 5–18 y and was much higher than that in the other age groups ( Figure 4G ). ARIMA time series prediction modelling was performed on the overall respiratory pathogenic infections, and the total predicted pathogen detection rates for seven quarters from April 2024 to December 2025 in Shijiazhuang City were obtained. The optimal model of acute upper respiratory tract infection in Shijiazhuang was ARIMA (2,2,0), and MAPE was 75.92 ( Figure 4H ).