Impact of air pollutants on influenza-like illness outpatient visits under COVID-19 pandemic in the subcenter of Beijing, China.

This study aimed to explore the association between air pollutants and outpatient visits for influenza-like illnesses (ILI) under the coronavirus disease 2019 (COVID-19) stage in the subcenter of Beijing. The data on ILI in the subcenter of Beijing from January 1, 2018 to December 31, 2020 were obtained from the Beijing Influenza Surveillance Network. A generalized additive Poisson model was applied to examine the associations between the concentrations of air pollutants and daily outpatient visits for ILI when controlling meteorological factors and temporal trend. A total of 171 943 ILI patients were included. In the pre-coronavirus disease 2019 (COVID-19) stage, an increased risk of ILI outpatient visits was associated to a high air quality index (AQI) and the high concentrations of particulate matter less than 2.5 (PM2.5 ), particulate matter 10 (PM10 ), sulphur dioxide (SO2 ), nitrogen dioxide (NO2 ), and carbon monoxide (CO), and a low concentration of ozone (O3 ) on lag0 day and lag1 day, while a higher increased risk of ILI outpatient visits was observed by the air pollutants in the COVID-19 stage on lag0 day. Except for PM10 , the concentrations of other air pollutants on lag1 day were not significantly associated with an increased risk of ILI outpatient visits during the COVID-19 stage. The findings that air pollutants had enhanced immediate effects and diminished lag-effects on the risk of ILI outpatient visits during the COVID-19 pandemic, which is important for the development of public health and environmental governance strategies.

Molecular Epidemiology of Herpangina Children in Tongzhou District, Beijing, China, During 2019-2020.

Background: The changing pattern of pathogen spectrum causing herpangina in the time of coronavirus disease 2019 (COVID-19) pandemic was unknown. The purpose of this study was to investigate the changes on the molecular epidemiology of herpangina children during 2019-2020 in Tongzhou district, Beijing, China. Method: From January 2019 to December 2020, children diagnosed with herpangina were recruited by the staff from Tongzhou Center for Disease Control and Prevention (CDC) in Beijing. Viral RNA extraction from pharyngeal swabs was used for enterovirus (EV) detection and the complete VP1 gene was sequenced. The phylogenetic analysis was performed based on all VP1 sequences for EV genotypes. Result: A total of 1,331 herpangina children were identified during 2019-2020 with 1,121 in 2019 and 210 in 2020, respectively. The predominant epidemic peak of herpangina children was in summer and autumn of 2019, but not observed in 2020. Compared to the number of herpangina children reported in 2019, it decreased sharply in 2020. Among 129 samples tested in 2019, 61 (47.3%) children were detected with EV, while 22.5% (20/89) were positive in 2020. The positive rate for EV increased since June 2019, peaked at August 2019, and decreased continuously until February 2020. No cases were observed from February to July in 2020, and the positive rate of EV rebounded to previous level since August 2020. Four genotypes, including coxsackievirus A6 (CV-A6, 9.3%), CV-A4 (7.8%), CV-A10 (2.3%) and CV-A16 (10.1%), were identified in 2019, and only three genotypes, including CV-A6 (9.0%), CV-A10 (6.7%) and CV-A16 (1.1%), were identified in 2020. The phylogenetic analysis showed that all CV-A6 strains from Tongzhou located in Group C, and the predominant strains mainly located in C2-C4 subgroups during 2016-2018 and changed into C1 subgroup during 2018-2020. CV-A16 strains mainly located in Group B, which consisting of strains widely distributed around the world. Conclusions: The predominant genotypes gradually shifted from CV-A16, CV-A4 and CV-A6 in 2019 to CV-A6 in 2020 under COVID-19 pandemic. Genotype-based surveillance will provide robust evidence and facilitate the development of public health measures.

Dynamics of influenza-like illness under urbanization procedure and COVID-19 pandemic in the subcenter of Beijing during 2013-2021.

Influenza-like illness (ILI) varies in intensity year by year, generally keeping a stable pattern except for great changes of its epidemic pattern. Of the most impacting factors, urbanization has been suggested as shaping the intensity of influenza epidemics. Besides, growing evidence indicates the nonpharmaceutical interventions (NPIs) to severe acute respiratory syndrome coronavirus 2 offer great advantages in controlling infectious diseases. The present study aimed to evaluate the impact of urbanization and NPIs on the dynamic of ILI in Tongzhou, Beijing, during January 2013 to March 2021. ILI epidemiological surveillance data in Tongzhou district were obtained from Beijing Influenza Surveillance Network and separated into three periods of urbanization and four intervals of coronavirus disease 2019 pandemic. Standardized average incidence rates of ILI in each separate stages were calculated and compared by using Wilson method and time series model of seasonal ARIMA. Influenza seasonal outbreaks showed similar epidemic size and intensity before urbanization during 2013-2016. Increased ILI activity was found during the process of Tongzhou's urbanization during 2017-2019, with the rate difference of 2.48 (95% confidence interva [CI]: 2.44, 2.52) and the rate ratio of 1.75 (95% CI: 1.74, 1.76) of ILI incidence between preurbanization and urbanization periods. ILI activity abruptly decreased from the beginning of 2020 and kept at the bottom level almost in every epidemic interval. The top decrease in ILI activity by NPIs was shown in 5-14 years group in 2020-2021 influenza season, as 92.2% (95% CI: 78.3%, 95.2%). The results indicated that both urbanization and NPIs interrupted the epidemic pattern of ILI. We should pay more attention to public health when facing increasing population density, human contact, population mobility, and migration in the process of urbanization. NPIs and influenza vaccination should be implemented as necessary measures to protect people from common infectious diseases like ILI.

Molecular Epidemiology of Herpangina Children in Tongzhou District, Beijing, China, During 2019-2020

Background The changing pattern of pathogen spectrum causing herpangina in the time of coronavirus disease 2019 (COVID-19) pandemic was unknown. The purpose of this study was to investigate the changes on the molecular epidemiology of herpangina children during 2019-2020 in Tongzhou district, Beijing, China. Method From January 2019 to December 2020, children diagnosed with herpangina were recruited by the staff from Tongzhou Center for Disease Control and Prevention (CDC) in Beijing. Viral RNA extraction from pharyngeal swabs was used for enterovirus (EV) detection and the complete VP1 gene was sequenced. The phylogenetic analysis was performed based on all VP1 sequences for EV genotypes. Result A total of 1,331 herpangina children were identified during 2019-2020 with 1,121 in 2019 and 210 in 2020, respectively. The predominant epidemic peak of herpangina children was in summer and autumn of 2019, but not observed in 2020. Compared to the number of herpangina children reported in 2019, it decreased sharply in 2020. Among 129 samples tested in 2019, 61 (47.3%) children were detected with EV, while 22.5% (20/89) were positive in 2020. The positive rate for EV increased since June 2019, peaked at August 2019, and decreased continuously until February 2020. No cases were observed from February to July in 2020, and the positive rate of EV rebounded to previous level since August 2020. Four genotypes, including coxsackievirus A6 (CV-A6, 9.3%), CV-A4 (7.8%), CV-A10 (2.3%) and CV-A16 (10.1%), were identified in 2019, and only three genotypes, including CV-A6 (9.0%), CV-A10 (6.7%) and CV-A16 (1.1%), were identified in 2020. The phylogenetic analysis showed that all CV-A6 strains from Tongzhou located in Group C, and the predominant strains mainly located in C2-C4 subgroups during 2016-2018 and changed into C1 subgroup during 2018-2020. CV-A16 strains mainly located in Group B, which consisting of strains widely distributed around the world. Conclusions The predominant genotypes gradually shifted from CV-A16, CV-A4 and CV-A6 in 2019 to CV-A6 in 2020 under COVID-19 pandemic. Genotype-based surveillance will provide robust evidence and facilitate the development of public health measures.