[Cross-sectional study on the use of masks among occupational groups with high-risk positions for overseas import and pollution transmission].

Objective: To investigate the wearing of masks and the knowledge of masks among high-risk positions for overseas import and pollution transmission. Methods: From May 14 to 17, 2022, a convenient sampling method was used to conduct an online survey among 963 workers in high-risk positions for overseas import and pollution transmission in Beijing. The behaviors of individual use and wearing masks, the distribution and supervision of the unit, the knowledge of personal mask protection and the subjective feelings of wearing masks were analyzed. The χ(2) test and logistic regression model were used to analyze the influencing factors of the correct selection of masks. Results: The majority of the workers in high-risk positions for overseas import and pollution transmission were male (86.0%, 828/963), age concentration in 18-44 years old (68.2%, 657/963), and the majority of them had college or bachelor degrees (49.4%, 476/963). 79.4%(765/963) of the workers chose the right type of masks, female, 45-59 years old and high school education or above were the risk factors for correct selection of masks (P <0.05). Workers had good behaviors such as wearing/removing masks, but only 10.5% (101/963) could correctly rank the protective effect of different masks. 98.4% (948/963) of the workers believed that their work units had provided masks to their employees, and 99.1% (954/963) and 98.2%(946/963) of them had organized training and supervision on the use of masks, respectively. 47.4%(456/963) of the workers were uncomfortable while wearing masks. Conclusion: The overall selection and use of masks among occupational groups in high-risk positions for overseas import and pollution transmission in China need to be further standardized. It is necessary to strengthen supervision and inspection on the use of masks among occupational groups, and take improvement measures to improve the comfort of wearing masks.

Visual analysis of the prevention and control measures of COVID-19 in Chinese ports.

In 2022, COVID-19 solutions in China have entered a normal stage, and the solutions imported from ports have been transformed from emergency prevention and control measures to investigative long-term prevention and control measures. Therefore, it is necessary to study solutions for COVID-19 at border ports. In this study, 170 research papers related to the prevention and control measures of COVID-19 at ports from 2020 to September 2022 were retrieved from Wanfang database, HowNet database, Wip database, and WoS core collection. Citespace 6.1.R2 software was used to research institutions visualize and analyze researchers and keywords to explore their research hotspots and trends. After analysis, the overall volume of documents issued in the past 3 years was stable. The major contributors are scientific research teams such as the Chinese Academy of Inspection and Quarantine Sciences (Han Hui et al.) and Beijing Customs (Sun Xiaodong et al.), with less cross-agency cooperation. The top five high-frequency keywords with cumulative frequency are as follows: COVID-19 (29 times), epidemic prevention and control (29 times), ports (28 times), health quarantine (16 times), and risk assessment (16 times). The research hotspots in the field of prevention and control measures for COVID-19 at ports are constantly changing with the progress of epidemic prevention and control. Cooperation between research institutions needs to be strengthened urgently. The research hotspots are the imported epidemic prevention and control, risk assessment, port health quarantine, and the normalized epidemic prevention and control mechanism, which is the trend of research and needs further exploration in the future.

Comparative analysis of prevention and control measures toward COVID-19 epidemic between Shanghai and Beijing.

Purpose: By serving and providing a guide for other regional places, this study aims to advance and guide the epidemic prevention and control methods, and practices and strengthen people's ability to respond to COVID-19 and other future potential public health risks. Design/methodology/approach: A comparative analysis was conducted that the COVID-19 epidemic development trend and prevention and control effects both in Beijing and Shanghai. In fact, regarding the COVID-19 policy and strategic areas, the differences between governmental, social, and professional management were discussed and explored. To prevent and be ready for potential pandemics, experience and knowledge were used and summarized. Findings: The strong attack of the Omicron variant in early 2022 has posed challenges to epidemic prevention and control practices in many Chinese cities. Shanghai, which had achieved relatively good performance in the fight against the epidemic, has exposed limitations in its epidemic prevention and control system in the face of Omicron. In fact, the city of Beijing has undertaken prompt and severe lockdown measures and achieved rather good results in epidemic prevention and control because of learning from Shanghai's experience and lessons; adhering to the overall concept of "dynamic clearing," implementing precise prevention and monitoring, enhancing community control, and making emergency plans and preparations. All these actions and measures are still essential in the shift from pandemic response to pandemic control. Research limitations/implications: Different places have introduced different urgent policies to control the spread of the pandemic. Strategies to control COVID-19 have often been based on preliminary and limited data and have tended to be slow to evolve as new evidence emerges. Hence, the effects of these anti-epidemic policies need to be further tested.

[Analysis on infection sources and transmission chains of three outbreaks caused by 2019-nCoV Omicron variant in Beijing, China].

Objective: To investigate the infection sources and the transmission chains of three outbreaks caused by 2019-nCoV Omicron variant possibly spread through cross-border logistics in Beijing. Methods: Epidemiological investigation and big data were used to identify the exposure points of the cases. Close contacts were traced from the exposure points, and the cases' and environmental samples were collected for nucleic acid tests. Positive samples were analyzed by gene sequencing. Results: The Omicron variant causing 3 outbreaks in Beijing from January to April, 2022 belonged to BA.1, BA.1.1 and BA.2. The outbreaks lasted for 8, 12 and 8 days respectively, and 6, 42 and 32 cases infected with 2019-nCoV were reported respectively. International mail might be the infection source for 1 outbreak, and imported clothes might be the infection sources for another 2 outbreaks. The interval between the shipment start time of the imported goods and the infection time of the index case was 3-4 days. The mean incubation period (Q1, Q3) was 3 (2,4) days and the mean serial interval (Q1, Q3) was 3 (2,4)days. Conclusions: The 3 outbreaks highlighted the risk of infection by Omicron variant from international logistics-related imported goods at normal temperature. Omicron variant has stronger transmissibility, indicating that rapid epidemiological investigation and strict management are needed.

A machine learning-based study on the impact of COVID-19 on three kinds of pollution in Beijing-Tianjin-Hebei region.

Large-scale restrictions on anthropogenic activities in China in 2020 due to the Corona Virus Disease 2019 (COVID-19) indirectly led to improvements in air quality. Previous studies have paid little attention to the changes in nitrogen dioxide (NO2), fine particulate matter (PM2.5) and ozone (O3) concentrations at different levels of anthropogenic activity limitation and their interactions. In this study, machine learning models were used to simulate the concentrations of three pollutants during periods of different levels of lockdown, and compare them with observations during the same period. The results show that the difference between the simulated and observed values of NO2 concentrations varies at different stages of the lockdown. Variation between simulated and observed O3 and PM2.5 concentrations were less distinct at different stages of lockdowns. During the most severe period of the lockdowns, NO2 concentrations decreased significantly with a maximum decrease of 65.28 %, and O3 concentrations increased with a maximum increase of 75.69 %. During the first two weeks of the lockdown, the titration reaction in the atmosphere was disrupted due to the rapid decrease in NO2 concentrations, leading to the redistribution of Ox (NO2 + O3) in the atmosphere and eventually to the production of O3 and secondary PM2.5. The effect of traffic restrictions on the reduction of NO2 concentrations is significant. However, it is also important to consider the increase in O3 due to the constant volatile organic compounds (VOCs) and the decrease in NOx (NO+NO2). Traffic restrictions had a limited effect on improving PM2.5 pollution, so other beneficial measures were needed to sustainably reduce particulate matter pollution. Research on COVID-19 could provide new insights into future clean air action.

Causes of the unexpected slowness in reducing winter PM2.5 for 2014-2018 in Henan Province.

Toughest-ever clean air actions in China have been implemented nationwide to improve air quality. However, it was unexpected that from 2014 to 2018, the observed wintertime PM2.5 (particulate matter with an aerodynamic diameter of less than 2.5 µm) concentrations showed an insignificant decrease in Henan Province (HNP), a region in the west of the North China Plain. Emission controls seem to have failed to improve winter air quality in HNP, which has caused great confusion in formulating the next air improvement strategy. We employed a deweathering technique to decouple the impact of meteorological conditions. The results showed that the deweathered PM2.5 trend was -3.3%/yr in winter from 2014 to 2018, which had a larger decrease than the observed concentrations (-0.9%/yr), demonstrating that emission reduction was effective at improving air quality. However, compared with the other two megacity clusters, Beijing-Tianjin-Hebei (BTH) (-8.4%/yr) and Yangtze River Delta (YRD) (-7.4%/yr), the deweathered decreasing trend of PM2.5 for HNP remained slow. The underlying mechanism driving the changes in PM2.5 and its chemical components was further explored, using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Model simulations indicated that nitrate dominated the increase of PM2.5 components in HNP and the proportions of nitrate to total PM2.5 increased from 22.4% in January 2015 to 39.7% in January 2019. There are two primary reasons for this phenomenon. One is the limited control of nitrogen oxide emissions, which facilitates the conversion of nitric acid to particulate nitrate by ammonia. The other is unfavourable meteorological conditions, particularly increasing humidity, further enhancing nitrate formation through multiphase reactions. This study highly emphasizes the importance of reducing nitrogen oxide emissions owing to their impact on the formation of particulate nitrate in China, especially in the HNP region.

Response of cross-correlations between high PM2.5 and O3 with increasing time scales to the COVID-19: different trends in BTH and PRD.

The air pollution in China currently is characterized by high fine particulate matter (PM2.5) and ozone (O3) concentrations. Compared with single high pollution events, such double high pollution (DHP) events (both PM2.5 and O3 are above the National Ambient Air Quality Standards (NAAQS)) pose a greater threat to public health and environment. In 2020, the outbreak of COVID-19 provided a special time window to further understand the cross-correlation between PM2.5 and O3. Based on this background, a novel detrended cross-correlation analysis (DCCA) based on maximum time series of variable time scales (VM-DCCA) method is established in this paper to compare the cross-correlation between high PM2.5 and O3 in Beijing-Tianjin-Heibei (BTH) and Pearl River Delta (PRD). At first, the results show that PM2.5 decreased while O3 increased in most cities due to the effect of COVID-19, and the increase in O3 is more significant in PRD than in BTH. Secondly, through DCCA, the results show that the PM2.5-O3 DCCA exponents α decrease by an average of 4.40% and 2.35% in BTH and PRD respectively during COVID-19 period compared with non-COVID-19 period. Further, through VM-DCCA, the results show that the PM2.5-O3 VM-DCCA exponents [Formula: see text] in PRD weaken rapidly with the increase of time scales, with decline range of about 23.53% and 22.90% during the non-COVID-19 period and COVID-19 period respectively at 28-h time scale. BTH is completely different. Without significant tendency, its [Formula: see text] is always higher than that in PRD at different time scales. Finally, we explain the above results with the self-organized criticality (SOC) theory. The impact of meteorological conditions and atmospheric oxidation capacity (AOC) variation during the COVID-19 period on SOC state are further discussed. The results show that the characteristics of cross-correlation between high PM2.5 and O3 are the manifestation of the SOC theory of atmospheric system. Relevant conclusions are important for the establishment of regionally targeted PM2.5-O3 DHP coordinated control strategies.

Linking Cultural Tightness, Components of Norm Activation and COVID-19 Preventive Behaviors among University Students: Evidence from Beijing, China.

The ongoing COVID-19 pandemic has imposed greater challenges and more stringent requirements on higher education institutions (HEIs). However, limited empirical research has been devoted to identifying external and internal factors that may promote individual preventive behaviors during the COVID-19 pandemic within the higher education context. This study proposed and examined an extended norm activation model (NAM) concerning the relationships among cultural tightness, original NAM components, and COVID-19 preventive behaviors. An online survey was conducted with a sample of 3693 university students from 18 universities in Beijing, China. The results showed that cultural tightness was positively associated with respondents' COVID-19 preventive behaviors. Three original NAM variables, namely, awareness of consequences, the ascription of responsibility, and personal norms, played a chain mediating role in the relationship between cultural tightness and COVID-19 preventive behaviors. Theoretical and practical implications regarding the findings of this study and suggestions for future research are discussed.

Assessing the impact of COVID-19 interventions on influenza-like illness in Beijing and Hong Kong: an observational and modeling study.

BACKGROUND: The impact of coronavirus diseases 2019 (COVID-19) related non-pharmaceutical interventions (NPIs) on influenza activity in the presence of other known seasonal driving factors is unclear, especially at the municipal scale. This study aimed to assess the impact of NPIs on outpatient influenza-like illness (ILI) consultations in Beijing and the Hong Kong Special Administrative Region (SAR) of China. METHODS: We descriptively analyzed the temporal characteristics of the weekly ILI counts, nine NPI indicators, mean temperature, relative humidity, and absolute humidity from 2011 to 2021. Generalized additive models (GAM) using data in 2011-2019 were established to predict the weekly ILI counts under a counterfactual scenario of no COVID-19 interventions in Beijing and the Hong Kong SAR in 2020-2021, respectively. GAM models were further built to evaluate the potential impact of each individual or combined NPIs on weekly ILI counts in the presence of other seasonal driving factors in the above settings in 2020-2021. RESULTS: The weekly ILI counts in Beijing and the Hong Kong SAR fluctuated across years and months in 2011-2019, with an obvious winter-spring seasonality in Beijing. During the 2020-2021 season, the observed weekly ILI counts in both Beijing and the Hong Kong SAR were much lower than those of the past 9 flu seasons, with a 47.5% [95% confidence interval (CI): 42.3%, 52.2%) and 60.0% (95% CI: 58.6%, 61.1%) reduction, respectively. The observed numbers for these two cities also accounted for only 40.2% (95% CI: 35.4%, 45.3%) and 58.0% (95% CI: 54.1%, 61.5%) of the GAM model estimates in the absence of COVID-19 NPIs, respectively. Our study revealed that, "Cancelling public events" and "Restrictions on internal travel" measures played an important role in the reduction of ILI in Beijing, while the "restrictions on international travel" was statistically most associated with ILI reductions in the Hong Kong SAR. CONCLUSIONS: Our study suggests that COVID-19 NPIs had been reducing outpatient ILI consultations in the presence of other seasonal driving factors in Beijing and the Hong Kong SAR from 2020 to 2021. In cities with varying local circumstances, some NPIs with appropriate stringency may be tailored to reduce the burden of ILI caused by severe influenza strains or other respiratory infections in future.

Using an influenza surveillance system to estimate the number of SARS-CoV-2 infections in Beijing, China, weeks 2 to 6 2023.

With COVID-19 public health control measures downgraded in China in January 2023, reported COVID-19 case numbers may underestimate the true numbers after the SARS-CoV-2 Omicron wave. Using a multiplier model based on our influenza surveillance system, we estimated that the overall incidence of SARS-CoV-2 infections was 392/100,000 population in Beijing during the 5 weeks following policy adjustment. No notable change occurred after the Spring Festival in early February. The multiplier model provides an opportunity for assessing the actual COVID-19 situation.

Quantifying Social Interventions for Combating COVID-19 via a Symmetry-Based Model.

The COVID-19 pandemic has revealed new features in terms of substantial changes in rates of infection, cure, and death as a result of social interventions, which significantly challenges traditional SEIR-type models. In this paper we developed a symmetry-based model for quantifying social interventions for combating COVID-19. We found that three key order parameters, separating degree (S) for susceptible populations, healing degree (H) for mild cases, and rescuing degree (R) for severe cases, all display logistic dynamics, establishing a novel dynamic model named SHR. Furthermore, we discovered two evolutionary patterns of healing degree with a universal power law in 23 areas in the first wave. Remarkably, the model yielded a quantitative evaluation of the dynamic back-to-zero policy in the third wave in Beijing using 12 datasets of different sizes. In conclusion, the SHR model constitutes a rational basis by which we can understand this complex epidemic and policymakers can carry out sustainable anti-epidemic measures to minimize its impact.

Impact of the COVID-19 pandemic on emergent stroke care in Beijing, China.

The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented disruption to health care systems around the globe. Stroke is still an ongoing issue during the pandemic. We investigated the impact of the COVID-19 outbreak on emergent stroke care in Beijing, China. This is a retrospective analysis of two groups of patients with acute ischaemic stroke (AIS) registered in the Beijing Emergency Care Database between January 1, 2019, and December 31, 2020. Based on a database including 77 stroke centres, the quantity and quality of emergency care for stroke were compared. Subgroup analyses based on hospitals in different areas (high-risk and low/medium-risk areas) were carried out. A total of 6440 and 8699 admissions with suspected stroke were recorded in 2020 and 2019, respectively. There were no significant differences in the mean age and sex distribution for the patients between the two observational periods. The number of AIS admissions decreased by approximately 23.9% during the COVID-19 pandemic compared to that during the prepandemic period. The proportions of intravenous thrombolysis and endovascular treatment were 76.4% and 13.1%, respectively, in 2020, which were higher than those in 2019 (71.7% and 9.3%, respectively). There was no statistically significant difference in the time from stroke onset to arrival at the hospital (97.97 ± 23.09 min vs. 99.40 ± 20.76 min, p = 0.832) between the two periods. The door-to-needle time for thrombolysis (44.92 ± 9.20 min vs. 42.37 ± 9.06 min, p < 0.001) and door-to-thrombectomy time (138.56 ± 32.45 min vs. 120.55 ± 32.68 min, p < 0.001) were increased significantly in the pandemic period compared to those in the prepandemic period, especially in hospitals in high-risk areas. The decline in the number of patients with AIS and delay in treatment started after the launch of the level-1 public health emergency response and returned to stability after the release of professional protocols and consensus statements. Disruptions to medical services during the COVID-19 pandemic have substantially impacted AIS patients, with a clear drop in admission and a decline in the quality of emergent AIS care, especially in hospitals in high-risk areas and at the time of the initial outbreak of COVID-19. Health care systems need to maintain rapid adaptation to possible outbreaks of COVID-19 or similar crises in the future.

Case study of the Beijing 2022 Olympic Winter Games: Implications for global mass gathering events amidst the COVID-19 pandemic.

Objective: This study aimed to evaluate the public health countermeasures against coronavirus disease 2019 (COVID-19) that are important for organizing mass gathering events (MGEs) during a pandemic and to identify the practices suitable for application at future MGEs. Methods: This study analyzed data from the Beijing 2022 Olympic Winter Games. The aforementioned analysis was conducted from the viewpoints of overseas stakeholders and Chinese residents. The comprehensive set of countermeasures established to prevent the transmission of the COVID-19 pandemic comprised the bubble strategy, the three-layer testing strategy (pre-departure testing, testing at the airport, and daily screening), the mandatory wearing of N95 masks, and mandatory vaccination. Findings: A total of 437 positive cases within the bubble were reported during the Games, of which 60.6% were detected through screening at the airport and 39.4% were detected through routine screening. Nearly, 92.0% of the positive cases were detected within 7 days of arrival in China, and 80.8% of the cases had already been identified before the Opening Ceremony of the Games. Outside the bubble, no Games stakeholders were infected and no spectator contracted COVID-19. The bubble strategy, the three-layer testing strategy, the mandatory wearing of N95 masks, and mandatory vaccination are promising countermeasures to prevent the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during MGEs. Conclusion: Public health countermeasures introduced during the Beijing 2022 Olympic Winter Games were proven to be useful. The success in delivering and organizing the Games instills confidence and leaves a public health legacy for future MGEs amid the pandemic of COVID-19 or future emerging infectious diseases.

Changes in healthy effects and economic burden of PM2.5 in Beijing after COVID-19.

The COVID-19 lockdown had a positive control effect on urban air quality. However, this effect remains uncertain after the epidemic enters regular management, and furthermore, only limited data are available regarding urban PM2.5 (aerodynamic diameter ≤ 2.5µm) under the impact of the epidemic. We used daily ambient PM2.5 concentration data in Beijing to compare and analyze the changes in urban PM2.5 concentrations before and after the COVID-19 epidemic and to estimate the healthy effects and economic burden associated with PM2.5 before and after the epidemic. The study found that COVID-19 has a significant impact on the urban environmental PM2.5 concentration, which is manifested by the decrease in the PM2.5 concentration in Beijing during the epidemic by 27.8%. Exposure-response models estimated 56.443 (95% CI: 43.084-69.893) thousand people die prematurely in Beijing during the COVID-19 epidemic attributed to long-term PM2.5 exposure, with a 13.3% decrease in the number of premature deaths year-on-year. The total healthy economic losses attributable to PM2.5 in Beijing during the COVID-19 epidemic were 35.76 (95% CI: 28.41-42.44) billion yuan, with a per capita loss of 816.8 yuan. Strict control measures throughout the COVID-19 epidemic had a positive impact on air quality in Beijing, with a decrease in both premature deaths and economic healthy losses attributable to fine particles. This paper helps to enrich and expand the research on the impact of COVID-19 on the urban environment and provides a basis for formulating policies related to air quality improvement in the post-epidemic era.

Anxiety, depression, and sleep disturbances among people on long-term efavirenz-based treatment for HIV: a cross-sectional study in Beijing, China.

BACKGROUND: Efavirenz (EFV)-induced neuropsychiatric toxicity bothers people living with HIV (PLHIV). Neuropsychiatric adverse effects of EFV may differ by length of time on EFV-based antiretroviral treatment (ART). METHODS: A cross-sectional, single-center study was conducted at Beijing Ditan Hospital in China from June-August 2020 among ART-experienced PLHIV who were on long-term EFV-based ART. 424 eligible virological suppressed participants were enrolled and divided into four groups according to time on EFV-based ART: group A (0.5 ≤ ART < 2 year), B (2 ≤ ART < 4 year), C (4 ≤ ART < 6 year), and D (ART ≥ 6 year). The questionnaires about 12-item Short Form Health Survey (SF-12), Hospital Anxiety and Depression Scale (HADS) and Pittsburgh Sleep Quality Index (PSQI) were administered to assess neuropsychiatric adverse events of EFV among different groups. RESULTS: Overall mental component summary scores (MCS) of SF-12 in PLHIV was 50.2, which was lower than general population. Overall prevalence of anxiety, depression and sleep disturbances was 15.6%, 15.3% and 58%, respectively. Prevalence of anxiety, depression and sleep disturbances did not vary significantly between the time-on-ART groups. Anxiety, depression, sleep disturbances had no correlation with time on EFV-based ART or CD4+ T cells counts. CONCLUSIONS: In ART-experienced PLHIV in China, neuropsychiatric adverse events exist persistently and prevalence do not significantly change with prolonged time on EFV-based ART. The prevalence of sleep disturbances was high, suggesting that clinicians should pay more attention to long-standing psychiatric health to perform early and effective interventions.

Epidemiological features, genomic characteristics, and origin tracing of the COVID-19 outbreaks in Beijing from January to September 2022.

Different variants of severe acute respiratory syndrome coronavirus 2 have been discovered globally. At present, the Omicron variant has been extensively circulated worldwide. There have been several outbreaks of the Omicron variant in China. Here, we investigated the epidemiologic, genetic characteristics, and origin-tracing data of the outbreaks of COVID-19 in Beijing from January to September 2022. During this time, 19 outbreaks occurred in Beijing, with the infected cases ranging from 2 to 2230. Two concern variants were detected, with eight genotypes. Based on origin tracing analysis, two outbreaks were from the cold-chain transmission and three from items contaminated by humans. Imported cases have caused other outbreaks. Our study provided a detailed analysis of Beijing's outbreaks and valuable information to control the outbreak's spread.

How has the COVID-19 pandemic affected the utilisation of online consultation and face-to-face medical treatment? An interrupted time-series study in Beijing, China.

OBJECTIVE: The COVID-19 pandemic has had a major impact on healthcare utilisation. This study aimed to quantify how the online and face-to-face utilisation of healthcare services changed during this time and thus gain insights into the planning of future healthcare resources during the outbreak of infectious diseases. DESIGN: This work is an interrupted time-series study. SETTING: Monthly hospital-grade healthcare-service data from 22 tertiary first-class public hospitals managed by the Beijing Hospital Authority and online-consultation data from GoodDoctor were used in this study. METHODS: This is an interrupted time-series study about the change in face-to-face and online healthcare utilisation before and after the COVID-19 outbreak. We compared the impact of COVID-19 on the primary outcomes of both face-to-face healthcare utilisation (outpatient and emergency visits, discharge volume) and online healthcare utilisation (online consultation volume). And we also analysed the impact of COVID-19 on the healthcare utilisation of different types of diseases. RESULTS: The monthly average outpatient visits and discharges decreased by 36.33% and 35.75%, respectively, compared with those in 2019 in 22 public hospitals in Beijing. Moreover, the monthly average online consultations increased by 90.06%. A highly significant reduction occurred in the mean outpatients and inpatients, which dropped by 1 755 930 cases (p<0.01) and 5 920 000 cases (p<0.01), respectively. Online consultations rose by 3650 cases (p<0.05). We identified an immediate and significant drop in healthcare services for four major diseases, that is, acute myocardial infarction (-174, p<0.1), lung cancer (-2502, p<0.01), disk disease (-3756, p<0.01) and Parkinson's disease (-205, p<0.01). Otherwise, online consultations for disk disease (63, p<0.01) and Parkinson's disease (25, p<0.05) significantly increased. More than 1300 unique physicians provided online-consultation services per month in 2020, which was 35.3% higher than in 2019. CONCLUSIONS: Obvious complementary trends in online and face-to-face healthcare services existed during the COVID-19 pandemic. Different changes in healthcare utilisation were shown for different diseases. Non-critically ill patients chose online consultation immediately after the COVID-19 lockdown, but critically ill patients chose hospital healthcare services first. Additionally, the volume of online physician services significantly rose as a result of COVID-19.

[Numerical Response Analysis of PM2.5-O3 Compound Pollution in Beijing].

The multi-scale variation trend of PM2.5-O3 compound pollution events was analyzed based on air quality data, meteorological data, and COVID-19 data in Beijing from 2015 to 2020. For the threshold of compound pollution, a compound pollution index was proposed, and the numerical response trend was evaluated based on the generalized additive model. A distributed lag nonlinear model was introduced to analyze the risk response relationship between compound pollution and influencing factors. The results showed that the events of PM2.5-O3 compound pollution in Beijing decreased annually. At the same time, due to the influence of pollutant emissions and meteorological conditions, there were obvious seasonal effects, week effects, holiday effects, and epidemic effects. The composite pollution index had no correlation with rainfall but had a linear positive correlation with O3 and air temperature and a nonlinear correlation with other explanatory variables. Air pollutants and meteorological conditions had obvious lag effects on the composite pollution index, and the lag effects were mainly concentrated in 1-3 d. PM2.5, PM10, O3, SO2, and air temperature in high-value areas significantly increased the risk of compound pollution. The CO (1-6 mg·m-3), NO2 (38-118 µg·m-3), and relative humidity (54%-87%) in the median section would also increase the risk of compound pollution, as would low wind speed. The compound pollution events showed a trend of multi-day continuous pollution in the numerical response. Compared with PM2.5 and PM10, compound pollution events were more dependent on O3, and the compound pollution rate in high-value areas was 30.7%-47.5%. CO and relative humidity had little effect on compound pollution events. The air temperature had the greatest impact, and 84.7% of the composite pollution incidents occurred at 20-30℃.

Epidemiological analysis of Group A streptococcus infection diseases among children in Beijing, China under COVID-19 pandemic.

BACKGROUND: Group A streptococcus is human-restricted gram-positive pathogen, responsible for various clinical presentations from mild epidermis infections to life threatened invasive diseases. Under COVID-19 pandemic,. the characteristics of the epidemic strains of GAS could be different. PURPOSE: To investigate epidemiological and molecular features of isolates from GAS infections among children in Beijing, China between January 2020 and December 2021. Antimicrobial susceptibility profiling was performed based on Cinical Laboratory Sandards Institute. Distribution of macrolide-resistance genes, emm types, and superantigens was examined by polymerase chain reaction. RESULTS: 114 GAS isolates were collected which were frequent resistance against erythromycin (94.74%), followed by clindamycin (92.98%), tetracycline (87.72%). Emm12 (46.49%), emm1 (25.44%) were dominant emm types. Distribution of ermB, ermA, and mefA gene was 93.85%, 2.63%, and 14.04%, respectively. Frequent superantigenes identified were smeZ (97.39%), speG (95.65%), and speC (92.17%). Emm1 strains possessed smeZ, ssa, and speC, while emm12 possessed smeZ, ssa, speG, and speC. Erythromycin resistance was predominantly mediated by ermB. Scarlet fever strains harbored smeZ (98.81%), speC (94.05%). Impetigo strains harbored smeZ (88.98%), ssa (88.89%), and speC (88.89%). Psoriasis strains harbored smeZ (100%). CONCLUSIONS: Under COVID-19 pandemic, our collections of GAS infection cutaneous diseases decreased dramatically. Epidemiological analysis of GAS infections among children during COVID-19 pandemic was not significantly different from our previous study. There was a correlation among emm, superantigen gene and disease manifestations. Long-term surveillance and investigation of emm types and superantigens of GAS prevalence are imperative.