Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China

Ozone (O₃) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level. Large-scale and long-term studies of O₃ pollution in China are few due to highly limited direct ground and satellite measurements. This study offers a new perspective to estimate ground-level O₃ from solar radiation intensity and surface temperature by employing an extended ensemble learning of the space-time extremely randomized trees (STET) model, together with ground-based observations, remote sensing products, atmospheric reanalysis, and an emission inventory. A full-coverage (100%), high-resolution (10 km) and high-quality daily maximum 8-h average (MDA8) ground-level O₃ dataset covering China (called ChinaHighO₃) from 2013 to 2020 was generated. Our MDA8 O₃ estimates (predictions) are reliable, with an average out-of-sample (out-of-station) coefficient of determination of 0.87 (0.80) and root-mean-square error of 17.10 (21.10) μg/m³ in China. The unique advantage of the full coverage of our dataset allowed us to accurately capture a short-term severe O₃ pollution exposure event that took place from 23 April to 8 May in 2020. Also, a rapid increase and recovery of O₃ concentrations associated with variations in anthropogenic emissions were seen during and after the COVID-19 lockdown, respectively. Trends in O₃ concentration showed an average growth rate of 2.49 μg/m³/yr (p < 0.001) from 2013 to 2020, along with the continuous expansion of polluted areas exceeding the daily O₃ standard (i.e., MDA8 O₃ = 160 μg/m³). Summertime O₃ concentrations and the probability of occurrence of daily O₃ pollution have significantly increased since 2015, especially in the North China Plain and the main air pollution transmission belt (i.e., the "2 + 26” cities). However, a decline in both was seen in 2020, mainly due to the coordinated control of air pollution and ongoing COVID-19 effects. This carefully vetted and smoothed dataset is valuable for studies on air pollution and environmental health in China.

Separating Daily 1 km PM2.5 Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data.

Fine particulate matter (PM2.5) chemical composition has strong and diverse impacts on the planetary environment, climate, and health. These effects are still not well understood due to limited surface observations and uncertainties in chemical model simulations. We developed a four-dimensional spatiotemporal deep forest (4D-STDF) model to estimate daily PM2.5 chemical composition at a spatial resolution of 1 km in China since 2000 by integrating measurements of PM2.5 species from a high-density observation network, satellite PM2.5 retrievals, atmospheric reanalyses, and model simulations. Cross-validation results illustrate the reliability of sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and chloride (Cl-) estimates, with high coefficients of determination (CV-R2) with ground-based observations of 0.74, 0.75, 0.71, and 0.66, and average root-mean-square errors (RMSE) of 6.0, 6.6, 4.3, and 2.3 µg/m3, respectively. The three components of secondary inorganic aerosols (SIAs) account for 21% (SO42-), 20% (NO3-), and 14% (NH4+) of the total PM2.5 mass in eastern China; we observed significant reductions in the mass of inorganic components by 40-43% between 2013 and 2020, slowing down since 2018. Comparatively, the ratio of SIA to PM2.5 increased by 7% across eastern China except in Beijing and nearby areas, accelerating in recent years. SO42- has been the dominant SIA component in eastern China, although it was surpassed by NO3- in some areas, e.g., Beijing-Tianjin-Hebei region since 2016. SIA, accounting for nearly half (∼46%) of the PM2.5 mass, drove the explosive formation of winter haze episodes in the North China Plain. A sharp decline in SIA concentrations and an increase in SIA-to-PM2.5 ratios during the COVID-19 lockdown were also revealed, reflecting the enhanced atmospheric oxidation capacity and formation of secondary particles.

Emotional distress and burnout at a fever clinic in China: Comparison between different periods of COVID-19.

Background: Frontline healthcare workers (FHWs) experienced psychological stress and heavy workload during COVID-19 pandemic. This study examined the psychological symptoms and occupational burnout of FHWs in a fever clinic during different periods of the pandemic. Methods: A cross-sectional survey of FHWs in the fever clinic of a tertiary hospital was carried out during both the outbreak period and regular period of COVID-19. Psychological measurement instruments including Generalized Anxiety Disorder 7-item, the 9-Question Patient Health Questionnaire, the Maslach Burnout Inventory-Human Service Survey, and the General Self-Efficacy Scale were used to evaluate anxiety, depression, burnout, and self-efficacy, respectively. The correlation between clinical variables was explored. Results: A total of 162 participants were involved in this study, including 118 FHWs during the outbreak period (Group 1) and 44 FHWs during the regular period (Group 2). Anxiety symptoms were more prevalent in Group 2 (x 2 = 27.477) while depressive symptoms were significantly more prevalent in Group 1 (x 2 = 69.538). Burnout rate was higher in Group 2 (x 2 = 29.526). Self-efficacy was higher in Group 1 (t = 3.194). Burnout was positively correlated with anxiety symptoms (r 2 = 0.424) and negatively correlated with self-efficacy (r 2 = -0.312). Conclusion: Anxiety, depressive symptoms and burnout were prevalent in FHWs during different periods of the COVID-19 pandemic. There is a tendency to be less depressed, but more anxious and burned out over time, although the severity of the pandemic is decreasing. Self-efficacy may be an important factor in protecting FHWs from occupational burnout. Support and intervention plans for FHWs should be made at the institutional level.

Clinical Implications of Targeting the JAK-STAT Pathway in Psoriatic Disease: Emphasis on the TYK2 Pathway.

Cytokines in the interleukin (IL)-23/IL-17 axis are central to psoriasis pathogenesis. Janus kinase (JAK) signal transducer and activator of transcription (STAT) regulates intracellular signalling of several cytokines (including IL-12, 23, 22, 6, 17, and interferon (IFN)-γ) in the IL-23/IL-17 axis, and, as a result, has become a therapeutic target for psoriasis treatment. Although several JAK1-3 inhibitors, with varying degrees of selectivity, have been developed for immune-mediated inflammatory diseases, use in psoriasis is limited by a low therapeutic index as anticipated by signals from other disease indications. More selective inhibition of the JAK family is an area of interest. Specifically, selective tyrosine kinase (TYK)2 inhibition suppresses IL-23/IL-17 axis signalling, and at therapeutic doses, has a favorable safety profile compared to therapeutic doses of JAK1-3 inhibitors. Phase III efficacy and safety data for the selective allosteric TYK2-inhibitor, deucravacitinib, in adult patients with moderate-to-severe plaque psoriasis is promising. Furthermore, phase II clinical trials for ropsacitinib (PF-06826647), a selective TYK2 inhibitor, and brepocitinib (PF-06700841), a JAK1/TYK2 inhibitor, have also demonstrated efficacy and an acceptable safety profile in adult patients with moderate-to-severe plaque psoriasis. Other novel TYK2 allosteric inhibitors, NDI-034858 and ESK-001, are currently being investigated in adult patients with plaque psoriasis. This article reviews the details of the JAK-STAT pathway in psoriasis pathophysiology, the rationale for selective targeting of JAKs in the treatment of psoriasis, and provides clinical perspective on clinical trial data for JAK and TYK2 inhibitors.

Ground-level gaseous pollutants (NO2, SO2, and CO) in China: daily seamless mapping and spatiotemporal variations

Gaseous pollutants at the ground level seriously threaten the urban air quality environment and public health. There are few estimates of gaseous pollutants that are spatially and temporally resolved and continuous across China. This study takes advantage of big data and artificial-intelligence technologies to generate seamless daily maps of three major ambient pollutant gases, i.e., NO2, SO2, and CO, across China from 2013 to 2020 at a uniform spatial resolution of 10 km. Cross-validation between our estimates and ground observations illustrated a high data quality on a daily basis for surface NO2, SO2, and CO concentrations, with mean coefficients of determination (root-mean-square errors) of 0.84 (7.99 µg m-3), 0.84 (10.7 µg m-3), and 0.80 (0.29 mg m-3), respectively. We found that the COVID-19 lockdown had sustained impacts on gaseous pollutants, where surface CO recovered to its normal level in China on around the 34th day after the Lunar New Year, while surface SO2 and NO2 rebounded more than 2 times slower due to more CO emissions from residents' increased indoor cooking and atmospheric oxidation capacity. Surface NO2, SO2, and CO reached their peak annual concentrations of 21.3 ± 8.8 µg m-3, 23.1 ± 13.3 µg m-3, and 1.01 ± 0.29 mg m-3 in 2013, then continuously declined over time by 12 %, 55 %, and 17 %, respectively, until 2020. The declining rates were more prominent from 2013 to 2017 due to the sharper reductions in anthropogenic emissions but have slowed down in recent years. Nevertheless, people still suffer from high-frequency risk exposure to surface NO2 in eastern China, while surface SO2 and CO have almost reached the World Health Organization (WHO) recommended short-term air quality guidelines (AQG) level since 2018, benefiting from the implemented stricter "ultra-low” emission standards. This reconstructed dataset of surface gaseous pollutants will benefit future (especially short-term) air pollution and environmental health-related studies.

Broadly neutralizing and protective nanobodies against SARS-CoV-2 Omicron subvariants BA.1, BA.2, and BA.4/5 and diverse sarbecoviruses.

As SARS-CoV-2 Omicron and other variants of concern (VOCs) continue spreading worldwide, development of antibodies and vaccines to confer broad and protective activity is a global priority. Here, we report on the identification of a special group of nanobodies from immunized alpaca with potency against diverse VOCs including Omicron subvariants BA.1, BA.2 and BA.4/5, SARS-CoV-1, and major sarbecoviruses. Crystal structure analysis of one representative nanobody, 3-2A2-4, discovers a highly conserved epitope located between the cryptic and the outer face of the receptor binding domain (RBD), distinctive from the receptor ACE2 binding site. Cryo-EM and biochemical evaluation reveal that 3-2A2-4 interferes structural alteration of RBD required for ACE2 binding. Passive delivery of 3-2A2-4 protects K18-hACE2 mice from infection of authentic SARS-CoV-2 Delta and Omicron. Identification of these unique nanobodies will inform the development of next generation antibody therapies and design of pan-sarbecovirus vaccines.

Short-term effects of ambient particulate matter (PM1, PM2.5 and PM10) on influenza-like illness in Guangzhou, China.

BACKGROUND: Particulate matter (PM) has been linked to respiratory infections in a growing body of evidence. Studies on the relationship between ILI (influenza-like illness) and PM1 (particulate matter with aerodynamic diameter ≤1 µm) are, however, scarce. The purpose of this study was to investigate the effects of PM on ILI in Guangzhou, China. METHODS: Daily ILI cases, air pollution records (PM1, PM2.5, PM10 and gaseous pollutants), and metrological data between 2014 and 2019 were gathered from Guangzhou, China. To estimate the risk of ILI linked with exposure to PM pollutants, a quasi-Poisson regression was used. Additionally, subgroup analyses stratified by gender, age and season were carried out. RESULTS: For each 10 µg/m3 increase of PM1 and PM2.5 over the past two days (lag01), and PM10 over the past three days (lag02), the relative risks (RR) of ILI were 1.079 (95% confidence interval [CI]: 1.050, 1.109), 1.044 (95% CI: 1.027, 1.062) and 1.046 (95% CI: 1.032, 1.059), respectively. The estimated risks for men and women were substantially similar. The effects of PM pollutants between male and female were basically equivalent. People aged 15-24 years old were more susceptive to PM pollutants. CONCLUSIONS: It implies that PM1, PM2.5 and PM10 are all risk factors for ILI, the health impacts of PM pollutants vary by particle size. Reducing the concentration of PM1 needs to be considered when generating a strategy to prevent ILI.

Recent advances in double-lumen tube malposition in thoracic surgery: A bibliometric analysis and narrative literature review.

Thoracic surgery has increased drastically in recent years, especially in light of the severe outbreak of the 2019 novel coronavirus disease (COVID-19). Routine "passive" chest computed tomography (CT) screening of inpatients detects some pulmonary diseases requiring thoracic surgeries timely. As an essential device for thoracic anesthesia, the double-lumen tube (DLT) is particularly important for anesthesia and surgery. With the continuous upgrading of the DLTs and the widespread use of fiberoptic bronchoscopy (FOB), the position of DLT in thoracic surgery is gradually becoming more stable and easier to observe or adjust. However, DLT malposition still occurs during transferring patients from a supine to the lateral position in thoracic surgery, which leads to lung isolation failure and hypoxemia during one-lung ventilation (OLV). Recently, some innovative DLTs or improved intervention methods have shown good results in reducing the incidence of DLT malposition. This review aims to summarize the recent studies of the incidence of left-sided DLT malposition, the reasons and effects of malposition, and summarize current methods for reducing DLT malposition and prospects for possible approaches. Meanwhile, we use bibliometric analysis to summarize the research trends and hot spots of the DLT research.

Association between ambient sulfur dioxide pollution and asthma mortality: Evidence from a nationwide analysis in China

There is a lack of research on the effects of acute exposure to ambient sulfur dioxide (SO2) on mortality caused by asthma, especially nationwide research in China. To explore the acute effect of exposure to ambient SO2 on asthma mortality using nationwide dataset in China from 2015 to 2020 and further evaluate the associations in subgroups with different geographical and demographic characteristics. We used data from China's Disease Surveillance Points system with 29,553 asthma deaths in China during 2015–2020. The exposure variable was the daily mean concentrations of SO2 from the ChinaHighSO2 10 km × 10 km daily grid dataset. Bilinear interpolation was used to estimate each individual's exposure to air pollutants and meteorological variables. We used a time-stratified case crossover design at the individual level to analyze the exposure response relationship between short-term exposure to SO2 and asthma mortality. Stratified analyses were carried out by sex, age group, marital status, warm season and cold season, urbanicity and region. Significant associations between short-term exposure to ambient SO2 and increased asthma mortality were found in this nationwide study. The excess risk (ER) for each 10 μg/m3 increase in SO2 concentrations at lag07 was 7.78 % (95 % CI, 4.16–11.52 %). Season appeared to significantly modify the association. The associations were stronger in cold season (ER 9.78 %, 95 % CI:5.82 −13.89 %). The association remained consistent using different lag periods, adjusting for other pollutants, and in the analysis during pre-Corona Virus Disease 2019 (COVID-19) period. Our study indicates increased risk of asthma mortality with acute exposures to SO2 in Chinese population. The current study lends support for greater awareness of the harmful effect of SO2 in China and other countries with high SO2 pollution.

Travel intention during the COVID-19 epidemic: The influence of institutional and interpersonal trust.

The global pandemic, COVID-19, has dealt a heavy blow to the tourism industry. Therefore, exploring the mechanisms influencing travel intention in the post-epidemic era can help provide management insights for the recovery of the travel market. Relying on the logic of social cognition theory, we conducted an empirical analysis from the perspective of trust and found that institutional trust and interpersonal trust can positively predict travel intention in the context of the epidemic, while travelers' health risk perception and safety self-efficacy mediate the relationship between trust and travel intention. Moreover, we verified the moderating role of tourists' psychological resilience. Further, the study confirms that China's active prevention policy not only reduces the physical health harm caused by the epidemic, but also effectively increases individuals' institutional trust in a proactive government. Through China's active anti-epidemic policy, individuals were able to counteract the negative impact of the COVID 19 epidemic on their travel intention. Further, theoretical and practical implications are discussed.

Travel intention during the COVID-19 epidemic: The influence of institutional and interpersonal trust

The global pandemic, COVID-19, has dealt a heavy blow to the tourism industry. Therefore, exploring the mechanisms influencing travel intention in the post-epidemic era can help provide management insights for the recovery of the travel market. Relying on the logic of social cognition theory, we conducted an empirical analysis from the perspective of trust and found that institutional trust and interpersonal trust can positively predict travel intention in the context of the epidemic, while travelers’ health risk perception and safety self-efficacy mediate the relationship between trust and travel intention. Moreover, we verified the moderating role of tourists’ psychological resilience. Further, the study confirms that China’s active prevention policy not only reduces the physical health harm caused by the epidemic, but also effectively increases individuals’ institutional trust in a proactive government. Through China’s active anti-epidemic policy, individuals were able to counteract the negative impact of the COVID 19 epidemic on their travel intention. Further, theoretical and practical implications are discussed.

Ground-Level NO2 Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence.

Nitrogen dioxide (NO2) at the ground level poses a serious threat to environmental quality and public health. This study developed a novel, artificial intelligence approach by integrating spatiotemporally weighted information into the missing extra-trees and deep forest models to first fill the satellite data gaps and increase data availability by 49% and then derive daily 1 km surface NO2 concentrations over mainland China with full spatial coverage (100%) for the period 2019-2020 by combining surface NO2 measurements, satellite tropospheric NO2 columns derived from TROPOMI and OMI, atmospheric reanalysis, and model simulations. Our daily surface NO2 estimates have an average out-of-sample (out-of-city) cross-validation coefficient of determination of 0.93 (0.71) and root-mean-square error of 4.89 (9.95) µg/m3. The daily seamless high-resolution and high-quality dataset "ChinaHighNO2" allows us to examine spatial patterns at fine scales such as the urban-rural contrast. We observed systematic large differences between urban and rural areas (28% on average) in surface NO2, especially in provincial capitals. Strong holiday effects were found, with average declines of 22 and 14% during the Spring Festival and the National Day in China, respectively. Unlike North America and Europe, there is little difference between weekdays and weekends (within ±1 µg/m3). During the COVID-19 pandemic, surface NO2 concentrations decreased considerably and then gradually returned to normal levels around the 72nd day after the Lunar New Year in China, which is about 3 weeks longer than the tropospheric NO2 column, implying that the former can better represent the changes in NOx emissions.

One-year follow-up study after patients with severe COVID-19 received human umbilical cord mesenchymal stem cells treatment.

BACKGROUND: The novel coronavirus is still mutating, and the pandemic continues. Meanwhile, many COVID-19 survivors have residual postinfection clinical manifestations. Human umbilical cord mesenchymal stem cells (hUC-MSCs) have been shown to be effective in the early stages of COVID-19. OBJECTIVES: The aim of this study was to investigate long-term safety and efficacy of treatment in patients with severe COVID-19 patients who had received hUC-MSCs therapy. METHODS: Twenty-five discharged patients who had severe COVID-19 (including the standard treatment group and the standard treatment plus hUC-MSCs group) were enrolled in a 1-year follow-up. The assessment considered adverse effects (including effects on liver and kidney function, coagulation, ECG, tumor marker, and so on), pulmonary function, St George's Respiratory Questionnaire (SGRQ), postinfection sequelae and serum concentration of Krebs von den Lungen-6 (KL-6), malondialdehyde (MDA), H2S, carnitine, and N-6 long-chain polyunsaturated fatty acids (N-6 LC-PUFAs). MEASUREMENTS AND MAIN RESULTS: Pulmonary ventilation function had significantly improved at the 1-year follow-up in both the hUC-MSCs group and the control group compared with the 3-month follow-up (P < 0.01). Fatigue (60% [15/25]) remained the most common symptom at the 1-year follow-up. The rate of fatigue relief was significantly reduced in the hUC-MSCs group (25% [2/8]) compared to the control group (76.5% [13/17]) (P = 0.028). The level of KL-6 was significantly lower in the hUC-MSCs group (2585.5 ± 186.5 U/ml) than in the control group (3120.7 ± 158.3 U/ml) (P < 0.001). Compared with the control group, the hUC-MSCs group had a lower level of MDA (9.27 ± 0.54 vs. 9.91 ± 0.72 nmol/ml, P = 0.036). No obvious adverse effects were observed in the hUC-MSCs treatment group at 1 year after discharge. CONCLUSIONS: Intravenous transplantation of hUC-MSCs was a safe approach in the long term in the treatment of patients with severe COVID-19. In addition, hUC-MSCs had a positive effect on postinfection sequelae in COVID-19 survivors. TRIAL REGISTRATION: Chinese Clinical Trial Registration; ChiCTR2000031494; Registered 02 April 2020-Retrospectively registered, http://www.medresman.org.

The willingness of parents to vaccinate their children younger than 12 years against COVID-19: a cross-sectional study in Malaysia.

BACKGROUND: The initiation of a new drug, for instance, the coronavirus disease 2019 (COVID-19) vaccine in children could be a source of major concern for parents. This study aims to determine the willingness of parents in Malaysia to vaccinate their children younger than 12 years against COVID-19. METHODS: An online cross-sectional survey was conducted nationwide in Malaysia from August 29, 2021, to October 17, 2021. Parents with children younger than 12 years were enrolled via the snowball sampling method. RESULTS: The analysis included data from 3,528 parents (79.5%) of the 4,438 survey responses received. Of these parents, 2,598 (73.6%) were willing, 486 (13.8%) were not willing, and 444 (12.6%) were still hesitant to vaccinate their children against COVID-19. Single parents (odds ratio [OR], 2.0; 95% confidence interval [CI], 1.32-3.04; P = 0.001), parents with secondary or lower education (OR, 1.5; 95% CI, 1.21-1.96; P < 0.001), healthcare workers (OR, 1.7; 95% CI, 1.34-2.26; P < 0.001), parents who had significant contact with COVID-19 (OR, 1.3; 95% CI, 1.09-1.63; P = 0.006), and parents who had been vaccinated against COVID-19 (OR, 15.4; 95% CI, 9.76-24.33; P < 0.001) were found more willing to immunize their children. The common reasons for vaccination given by parents who were willing to immunize their children include protection of children (99.4%), protection of other family members (99.3%), and effectiveness (98.2%). The common reasons against vaccination given by parents who were not willing to immunize their children were uncertainty about the new vaccine (96.1%), concerns about vaccine contents (93.2%), limited vaccine information from physicians (82.3%), and the belief of vaccine was unsafe (79.8%). CONCLUSIONS: In this study, nearly three-quarters of parents were willing to vaccinate their children younger than 12 years against COVID-19. The parents' history of COVID-19 vaccination was the strongest independent predictor of their willingness to vaccinate their children. Therefore, future health education for the COVID-19 vaccine should focus on parents who are prone to vaccine refusal or hesitation, address the common reasons for vaccine refusal, and highlight the vaccine's benefits.

Effects of the COVID-19 Lockdown on Air Pollutant Levels and Associated Reductions in Ischemic Stroke Incidence in Shandong Province, China.

Background: Local governments in China took restrictive measures after the outbreak of COVID-19 to control its spread, which unintentionally resulted in reduced anthropogenic emission sources of air pollutants. In this study, we intended to examine the effects of the COVID-19 lockdown policy on the concentration levels of particulate matter with aerodynamic diameters of ≤1 µm (PM1), ≤2.5 µm (PM2.5), and ≤10 µm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO) and the potential subsequent reductions in the incidence of ischemic and hemorrhagic stroke in Shandong Province, China. Methods: A difference-in-difference model combining the daily incidence data for ischemic and hemorrhagic stroke and air pollutant data in 126 counties was used to estimate the effect of the COVID-19 lockdown on the air pollutant levels and ischemic and hemorrhagic stroke incident counts. The avoided ischemic stroke cases related to the changes in air pollutant exposure levels were further estimated using concentration-response functions from previous studies. Results: The PM1, PM2.5, PM10, NO2, and CO levels significantly decreased by -30.2, -20.9, -13.5, -46.3, and -13.1%, respectively. The O3 level increased by 11.5% during the lockdown compared with that in the counterfactual lockdown phase of the past 2 years. There was a significant reduction in population-weighted ischemic stroke cases (-15,315, 95% confidence interval [CI]: -27,689, -2,942), representing a reduction of 27.6% (95% CI: -49.9%, -5.3%). The change in the number of hemorrhagic stroke cases was not statistically significant. The total avoided PM1-, PM2.5-, PM10-, NO2-, and CO-related ischemic stroke cases were 739 (95% CI: 641, 833), 509 (95% CI: 440, 575), 355 (95% CI: 304, 405), 1,132 (95% CI: 1,024, 1,240), and 289 (95% CI: 236, 340), respectively. Conclusion: The COVID-19 lockdown indirectly reduced the concentration levels of PM1, PM2.5, PM10, NO2, and CO and subsequently reduced the associated ischemic stroke incidence. The health benefits due to the lockdown are temporary, and long-term measures should be implemented to increase air quality and related health benefits in the post-COVID-19 period.

Evolution analysis of online topics based on ‘word-topic’ coupling network

Analyzing topic evolution is an effective way to monitor the overview of topic spreading. Existing methods have focused either on the intensity evolution of topics along a timeline or the topic evolution path of technical literature. In this paper, we aim to study topic evolution from a micro perspective, which not only captures the topic timeline but also reveals the topic status and the directed evolutionary path among topics. Firstly, we construct a word network by co-occurrence relationship between feature words. Secondly, Latent Dirichlet allocation (LDA) model is used to automatically extract topics and capture the mapping relationship between words and topics, and then a ‘word-topic’ coupling network is built. Thirdly, based on the ‘word-topic’ coupling network, we describe the topic intensity evolution over time and measure topic status considering the contribution of feature words to a topic. The concept of topic drifting probability is proposed to identify the evolutionary path. Experimental results conducted on two real-world data sets of “COVID-19” demonstrate the effectiveness of our proposed method.

Application of genetic algorithm combined with improved SEIR model in predicting the epidemic trend of COVID-19, China.

Since the outbreak of the 2019 Coronavirus disease (COVID-19) at the end of 2019, it has caused great adverse effects on the whole world, and it has been hindering the global economy. It is ergent to establish an infectious disease model for the current COVID-19 epidemic to predict the trend of the epidemic. Based on the SEIR model, the improved SEIR models were established with considering the incubation period, the isolated population, and genetic algorithm (GA) parameter optimization method. The improved SEIR models can predict the trend of the epidemic situation better and obtain the more accurate epidemic-related parameters. Comparing some key parameters, it is capable to evaluate the impact of different epidemic prevention measures and the implementation of different epidemic prevention levels on the COVID-19, which has significant guidance for further epidemic prevention measures.

Trends in secondary inorganic aerosol pollution in China and its responses to emission controls of precursors in wintertime

The Chinese government recently proposed ammonia (NH3) emission reductions (but without a specific national target) as a strategic option to mitigate fine particulate matter (PM2.5) pollution. We combined a meta-analysis of nationwide measurements and air quality modeling to identify efficiency gains by striking a balance between controlling NH3 and acid gas (SO2 and NOx) emissions. We found that PM2.5 concentrations decreased from 2000 to 2019, but annual mean PM2.5 concentrations still exceeded 35 µg m-3 at 74 % of 1498 monitoring sites during 2015–2019. The concentration of PM2.5 and its components were significantly higher (16 %–195 %) on hazy days than on non-hazy days. Compared with mean values of other components, this difference was more significant for the secondary inorganic ions SO42-, NO3-, and NH4+ (average increase 98 %). While sulfate concentrations significantly decreased over this period, no significant change was observed for nitrate and ammonium concentrations. Model simulations indicate that the effectiveness of a 50 % NH3 emission reduction for controlling secondary inorganic aerosol (SIA) concentrations decreased from 2010 to 2017 in four megacity clusters of eastern China, simulated for the month of January under fixed meteorological conditions (2010). Although the effectiveness further declined in 2020 for simulations including the natural experiment of substantial reductions in acid gas emissions during the COVID-19 pandemic, the resulting reductions in SIA concentrations were on average 20.8 % lower than those in 2017. In addition, the reduction in SIA concentrations in 2017 was greater for 50 % acid gas reductions than for the 50 % NH3 emission reductions. Our findings indicate that persistent secondary inorganic aerosol pollution in China is limited by emissions of acid gases, while an additional control of NH3 emissions would become more important as reductions of SO2 and NOx emissions progress.

Knowledge, Attitude, and Practices Among the General Population During the Later Stage of the COVID-19 Pandemic in Malaysia: A Cross-Sectional Study

Purpose A different pattern of mental health issues was reported during the later stage of the COVID-19 pandemic;however, few studies have examined Malaysians’ knowledge, attitudes, and practices (KAP) prevalent during this time. Patients and Methods A nationwide online cross-sectional study was conducted in Malaysia from June 1, 2021 to June 14, 2021, ie, 18-months from the first reported COVID-19 case in the country. Citizens aged 18 years and above were recruited by means of the snowball sampling method. ANOVA, Pearson correlation, and linear regression tests were used. Results Of the 2168 respondents, most were young adults (62.7%), females (62.4%), tertiary educated individuals (84%), non-health care workers (85.9%), and individuals who knew someone diagnosed with COVID-19 (75.2%). The mean score for knowledge was 10.0 ± 1.52 (maximum score = 12);correct response rate for each question ranged from 54.2% to 99%. The mean score in terms of attitude was 1.3 ± 0.85 (maximum score = 2);68.7% respondents agreed that control over COVID-19 would finally be achieved;and 62.3% believed that Malaysia could conquer COVID-19. The mean score for practices was 5.1 ± 1.10 (maximum score = 6);81.5%, 88.1%, and 74.1% respondents avoided crowded places, confined spaces, and conversations in close physical proximity, respectively. Furthermore, 94.2% wore masks when leaving home;89.0% practiced hand hygiene;and 83.8% adhering to COVID-19 warnings. Small but significant correlations were found between knowledge and attitude (r = 0.078, p < 0.001) as well as between knowledge and practices (r = 0.070, p = 0.001). Conclusion Malaysians exhibited sound knowledge but negative attitudes and inadequate practices pertaining to COVID-19 during the pandemic’s later stage. At this phase, unlike at the early stage, the public’s sound knowledge ensured little improvement in their attitudes and practices. Therefore, health education at the later pandemic stage should focus on promoting positive attitudes and developing better practices.

The association between daily-diagnosed COVID-19 morbidity and short-term exposure to PM1 is larger than associations with PM2.5 and PM10.

Exposure to particulate matter (PM) could increase both susceptibility to SARS-CoV-2 infection and severity of COVID-19 disease. Prior studies investigating associations between PM and COVID-19 morbidity have only considered PM2.5 or PM10, rather than PM1. We investigated the associations between daily-diagnosed COVID-19 morbidity and average exposures to ambient PM1 starting at 0 through 21 days before the day of diagnosis in 12 cities in China using a two-step analysis: a time-series quasi-Poisson analysis to analyze the associations in each city; and then a meta-analysis to estimate the overall association. Diagnosed morbidities and PM1 data were obtained from National Health Commission in China and China Meteorological Administration, respectively. We found association between short-term exposures to ambient PM1 with COVID-19 morbidity was significantly positive, and larger than the associations with PM2.5 and PM10. Percent increases in daily-diagnosed COVID-19 morbidity per IQR/10 PM1 for different moving averages ranged from 1.50% (-1.20%, 4.30%) to 241% (95%CI: 80.7%, 545%), with largest values for exposure windows starting at 17 days before diagnosis. Our results indicate that smaller particles are more highly associated with COVID-19 morbidity, and most of the effects from PM2.5 and PM10 on COVID-19 may be primarily due to the PM1. This study will be helpful for implementing measures and policies to control the spread of COVID-19.