Winter-autumn air pollution control plan in North China modified the PM2.5 compositions and sources in Central China

The additional impact of emission-reduction measures in North China (NC) during autumn and winter on the air quality of downwind regions is an interesting but less addressed topic. The mass concentrations of routine air pollutants, the chemical compositions, and sources of fine particles (PM2.5) for January 2018, 2019, and 2020 at a megacity of Central China were identified, and meteorology-isolated by a machine-learning technique. Their variations were classified according to air mass direction. An unexpectedly sharp increase in emission-related PM2.5 by 22.7% (18.0 mug m-3) and 25.7% (19.4 mug m-3) for air masses from local and NC in 2019 was observed compared to those of 2018. Organic materials exhibited the highest increase in PM2.5 compositions by 6.90 mug m-3 and 6.23 mug m-3 for the air masses from local and NC. PM2.5 source contributions related to emission showed an upsurge from 1.39 mug m-3 (biomass burning) to 24.9 mug m-3 (secondary inorganic aerosol) in 2019 except for industrial processes, while all reduced in 2020. From 2018 to 2020, the emission-related contribution of coal combustion to PM2.5 increased from 10.0% to 19.0% for air masses from the local area. To support the priority natural gas quotas in northern China, additional coal in cities of southern China was consumed, raising related emissions from transportation activities and road dust in urban regions, as well as additional biofuel consumption in suburban or rural regions. All these activities could explain the increased primary PM2.5 and related precursor NO2. This study gave substantial evidence of air pollution control measures impacting the downwind regions and promote the necessity of air pollution joint control across the administration.Copyright © 2023 Elsevier Ltd

Imaging Features of Familial Clustering of COVID-19

COVID-19 has obvious family clustering, and clustering refers to the occurrence of 2 or more confirmed es or asymptomatic infection in a small area within 14 days [1]. The clinical manifestations of familial clustering COVID-19 are related to exposure time, exposure degree, virus type, virus virulence, and patient age [2], which are mostly manifested as fever, chills, fatigue, ocional diarrhea, sore throat, or asymptomatic [3]. Symptoms are mild in children, and more severe in elderly or patients with chronic underlying diseases [4]. If there is an infected person in the family, it is easy to cause mutual infection;chest CT is helpful for the screening of suspected family es, early diagnosis, early treatment, and early isolation. The CT findings of the family cluster COVID-19 es are consistent with the typical manifestations of COVID-19. In the same group of family es, the lesion density and degree are similar [5]. The number of lesions and the range of involvement of multi-generation infected persons are reduced compared with earlier generations. The chest CT of children may be negative, and the lung lesions of the elderly or patients with chronic underlying diseases may be more severe. In the follow-up after treatment, the vast majority of the lung lesions were absorbed to different degrees, and the residual shadows were mostly ground-glass opacities or fibrous shadows. The chest CT findings of most patients could finally return to normal. © Henan Science and Technology Press 2020.

Seasonal variation and ecological risk assessment of Pharmaceuticals and Personal Care Products (PPCPs) in a typical semi-enclosed bay — The Bohai Bay in northern China

The Bohai Bay as a typical semi-enclosed bay in northern China with poor water exchange capacity and significant coastal urbanization, is greatly influenced by land-based inputs and human activities. As a class of pseudo-persistent organic pollutants, the spatial and temporal distribution of Pharmaceuticals and Personal Care Products (PPCPs) is particularly important to the ecological environment, and it will be imperfect to assess the ecological risk of PPCPs for the lack of systematic investigation of their distribution in different season. 14 typical PPCPs were selected to analyze the spatial and temporal distribution in the Bohai Bay by combining online solid-phase extraction (SPE) and HPLC-MS/MS techniques in this study, and their ecological risks to aquatic organisms were assessed by risk quotients (RQs) and concentration addition (CA) model. It was found that PPCPs widely presented in the Bohai Bay with significant differences of spatial and seasonal distribution. The concentrations of ∑PPCPs were higher in autumn than in summer. The distribution of individual pollutants also showed significant seasonal differences. The high values were mainly distributed in estuaries and near-shore outfalls. Mariculture activities in the northern part of the Bohai Bay made a greater contribution to the input of PPCPs. Caffeine, florfenicol, enrofloxacin and norfloxacin were the main pollutants in the Bohai Bay, with detection frequencies exceeding 80 %. The ecological risk of PPCPs to algae was significantly higher than that to invertebrates and fish. CA model indicated that the potential mixture risk of total PPCPs was not negligible, with 34 % and 88 % of stations having mixture risk in summer and autumn, respectively. The temporary stagnation of productive life caused by Covid-19 weakened the input of PPCPs to the Bohai Bay, reducing the cumulative effects of the pollutants. This study was the first full-coverage investigation of PPCPs in the Bohai Bay for different seasons, providing an important basis for the ecological risk assessment and pollution prevention of PPCPs in the bay. © 2022 Elsevier B.V.

Fast and direct identification of SARS-CoV-2 variants via 2D InSe field-effect transistors

As the COVID-19 pandemic evolves and new variants emerge, the development of more efficient identification approaches of variants is urgent to prevent continuous outbreaks of SARS-CoV-2. Field-effect transistors (FETs) with two-dimensional (2D) materials are viable platforms for the detection of virus nucleic acids (NAs) but cannot yet provide accurate information on NA variations. Herein, 2D Indium selenide (InSe) FETs were used to identify SARS-CoV-2 variants. The device's mobility and stability were ensured by atomic layer deposition (ALD) of Al2O3. The resulting FETs exhibited sub-fM detection limits ranging from 10(-14) M to 10(-)(8) M. The recognition of single-nucleotide variations was achieved within 15 min to enable the fast and direct identification of two core mutations (L452R, R203M) in Delta genomes (p < .01). Such capability originated from the trap states in oxidized InSe (InSe1-xOx) after ALD, resulting in traps-involved carrier transport responsive to the negative charges of NAs. In sum, the proposed approach might highly provide epidemiological information for timely surveillance of the COVID pandemic.

Simulation-Free Radiation Therapy: An Emerging Form of Treatment Planning to Expedite Plan Generation for Patients Receiving Palliative Radiation Therapy

Purpose: Herein we report the clinical and dosimetric experience for patients with metastases treated with palliative simulation-free radiation therapy (SFRT) at a single institution. Methods and Materials: SFRT was performed at a single institution. Multiple fractionation regimens were used. Diagnostic imaging was used for treatment planning. Patient characteristics as well as planning and treatment time points were collected. A matched cohort of patients with conventional computed tomography simulation radiation therapy (CTRT) was acquired to evaluate for differences in planning and treatment time. SFRT dosimetry was evaluated to determine the fidelity of SFRT. Descriptive statistics were calculated on all variables and statistical significance was evaluated using the Wilcoxon signed rank test and t test methods. Results: Thirty sessions of SFRT were performed and matched with 30 sessions of CTRT. Seventy percent of SFRT and 63% of CTRT treatments were single fraction. The median time to plan generation was 0.88 days (0.19-1.47) for SFRT and 1.90 days (0.39-5.23) for CTRT (P = .02). The total treatment time was 41 minutes (28-64) for SFRT and 30 minutes (21-45) for CTRT (P = .02). In the SFRT courses, the maximum and mean deviations in the actual delivered dose from the approved plans for the maximum dose were 4.1% and 0.07%, respectively. All deliveries were within a 5% threshold and deemed clinically acceptable. Conclusions: Palliative SFRT is an emerging technique that allowed for a statistically significant lower time to plan generation and was dosimetrically acceptable. This benefit must be weighed against increased total treatment time for patients receiving SFRT compared (c) 2022 The Author(s). Published by Elsevier Inc. on behalf of American Society for Radiation Oncology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Incorporating Fuzzy Cognitive Inference for Vaccine Hesitancy Measuring

Vaccine hesitancy plays a key role in vaccine delay and refusal, but its measurement is still a challenge due to multiple intricacies and uncertainties in factors. This paper attempts to tackle this problem through fuzzy cognitive inference techniques. Firstly, we formulate a vaccine hesitancy determinants matrix containing multi-level factors. Relations between factors are formulated through group decision-making of domain experts, which results in a fuzzy cognitive map. The subjective uncertainty of linguistic variables is expressed by fuzzy numbers. A double-weighted method is designed to integrate the distinguished decisions, in which the subjective hesitancy is considered for each decision. Next, three typical scenarios are constructed to identify key and sensitive factors under different experimental conditions. The experimental results are further discussed, which enrich the approaches of vaccine hesitancy estimation for the post-pandemic global recovery.

Impacts of Winter and Summer COVID-19 Lockdowns on Urban Air Quality in Urumqi, Northwest China

After the COVID-19 pandemic began in 2020, Urumqi, a remote area in northwest China, experienced two lockdowns, in January and July 2020. Based on ground and satellite observations, this study assessed the impacts of these lockdowns on the air quality in Urumqi and the seasonal differences between them. The results showed that, during the wintertime lockdown, PM10, PM2.5, NO2, CO, and SO2 levels decreased by 38, 40, 45, 27, 8%, respectively, whereas O-3 concentrations increased by 113%. During the summer lockdown, PM10, PM2.5, NO2, CO, and SO2 levels decreased by 39, 24, 59, 2, and 13%, respectively, and the O-3 concentrations increased by 21%. During the lockdowns, the NO2 concentrations decreased by 53% in winter and 13% in summer in the urban areas, whereas they increased by 23% in winter and 9% in summer in the suburbs. Moreover, large seasonal differences were observed between winter and summer SO2, CO, and O-3. The lockdown played a vital role in the rapid decline of primary air pollutant concentrations, along with fewer meteorological impacts on air pollution changes in this area. The increase in O-3 concentrations during the COVID-19 lockdowns reflects the complexity of air quality changes during reductions in air pollutant emissions.

COUPLING INFECTIOUS DISEASE MODEL AND GIS FOR LIVING MATERIAL SUPPLY ANALYSIS DURING COVID-19 OUTBREAK – TAKING SHENZHEN AS AN EXAMPLE

The COVID-19 epidemic has posed a grave threat to human life. The stay-at-home quarantine is an effective method of minimizing physical contact and the risk of COVID-19 transmission. However, the supply of living materials (such as meat, vegetables, grain, and oil) has become a great challenge as residents' activities have been restricted. In this paper, we present a spatial analysis framework for the supply of living materials during COVID-19 outbreak by coupling an infectious disease model with geographic information system (GIS). First, a virus spreading spatial simulation model is developed by combining cellular automata (CA) and Susceptible-Exposed-Infected-Recovered-Death (SEIRD) to estimate COVID-19's spreading under various scenarios. Second, the demand and supply of living materials in the impacted residents are calculated. Finally, the imbalance of the supply and demand of the living materials is assessed. We conduct experiments in Shenzhen. The experimental results show that localities with supply-demand mismatches are primarily concentrated in the southwest of Bao'an District, the southern of Longhua District, and Longgang District. Additionally, the spatial distribution of the mismatch level between supply and demand for living materials in Shenzhen exhibits a significant agglomeration effect, manifested as "low-low" and "high-high" agglomeration. The spatial agglomeration effect of material mismatch has increased with the spread of the epidemic. These results support the prevention and control of the COVID-19 spreading.

A high-performance humidity sensor based on alkalized MXenes and poly(dopamine) for touchless sensing and respiration monitoring

The typical mode of interaction between humans and machines in current intelligent equipment and personalized health care systems is mainly contact-type. However, there are severe problems associated with direct contact, such as uncomfortable wear and cross-infection of bacteria or viruses, especially under global pandemic conditions (e.g., COVID-19, MERS-CoV). In this study, a flexible humidity sensor is developed based on alkalized MXenes and polydopamine (PDA). The unique accordion-like hierarchical structure of the alkalized MXenes with large specific surface area and the chemical structure of the abundant water-absorbing functional groups of PDA wrapped on the MXene surface contribute synergistically to the outstanding performance of the sensor, which has high sensitivity, rapid response, and large detection range. The device was successfully used to control a noncontact switch system based on the distance of the fingertip and monitor different breathing patterns of a volunteer from a long range, proving its potential application in future noncontact human-machine interaction and human physiology monitoring.

Reactive force field-based molecular dynamics simulation of the interaction between plasma reactive oxygen species and the receptor-binding domain of the spike protein in the capsid protein of SARS-CoV-2

Under the pressures of the current global pandemic, researchers have been working hard to find a reliable way to suppress infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and prevent the spread of COVID-19. Studies have shown that the recognition and binding of human angiotensin-converting enzyme 2 by the receptor-binding domain (RBD) of the spike protein on the surface of SARS-CoV-2 is a crucial step in viral invasion of human receptor cells, and blocking this process could inhibit the virus from invading normal human cells. Plasma treatment can disrupt the structure of the RBD and effectively block the binding process. However, the mechanism by which plasma blocks recognition and binding is not clear. In this study, the reaction between reactive oxygen species (ROS) in plasma and a molecular model of the RBD was simulated using a reactive molecular dynamics method. The results showed that the destruction of the RBD by ROS was triggered by hydrogen ion reactions: O and OH ed H atoms from the RBD, while the H atoms of H2O2 and HO2 were ed by the RBD. This hydrogen ion resulted in the breakage of C-H, N-H, O-H and C=O bonds and the formation of C=C and C=N bonds. The addition reaction of OH increased the number of O-H bonds and caused the formation of C-O, N-O and O-H bonds. The dissociation of N-H bonds led to the destruction of the original peptide bond structure and amino acid residues, changed the type of amino acid residues and caused the conversion of N-C and N=C and C=O and C-O. The simulation partially elucidated the microscopic mechanism of the interaction between ROS in plasma and the capsid protein of SARS-CoV-2, providing theoretical support for the control of SARS-CoV-2 infection by plasma, a contribution to overcoming the global pandemic.

The Clinical Significance of SIRT3 in COVID-19 Patients: A Single Center Retrospective Analysis

OBJECTIVE: To investigate the role of Sirtuin 3 (SIRT3) in COVID-19 patients. METHODS: This retrospective study included 97 patients with COVID-19 who were admitted to the Second People's Hospital of Xiangzhou District in Xiangyang City, Hubei Province, China from January 29, 2020 to March 15, 2020. The blood samples of the patients were obtained within 24 hours of admission. The serum levels of SIRT3 were measured by enzyme linked immunosorbent assay (ELISA). Patients received a routine whole blood test, blood gas assay, electrolyte analysis, and coagulation analysis, and all data were recorded and collected. The clinical characteristics and outcomes of all patients were collected, including age, BMI, sex, medical history, complications, temperature, and imaging results. RESULTS: The severe COVID-19 patients showed significantly higher mean temperature, hospitalization duration, CT score, and ratio of cough, fatigue, dyspnea, and ground glass lesions on CT, as well as significantly higher levels of C reactive protein (CRP), procalcitonin (PCT), activated partial thromboplastin time (APTT), and D-dimer. SIRT3 levels were markedly lower in the severe patients compared with the mild/moderate patients and were negatively correlated with the levels of CRP and PCT. Patients with lower SIRT3 showed significantly higher temperature, duration, ratio of ground glass lesion on CT, and CT score, as well as higher expression of CRP and APTT. The ROC curve showed that SIRT3 had the potential for the prediction of different severities of COVID-19. The binary regression analysis showed that temperature, hospitalization, CT score, CRP, PCT, APTT, and D-dimer were independent risk factors for severe COVID-19. CONCLUSION: Serum SIRT3 levels were associated with the clinical outcome and prognosis of COVID-19 patients. However, SIRT3 is not an independent risk factor for severe COVID-19.

Causes of variation of air pollutant concentration in Shenyang during the COVID-19 epidemic based on WRF-Chem and EMI-index

Using air quality monitoring data, surface meteorological observational data, meteorological environment assessment index (EMI-index) products, National Centers for Environmental Prediction (NCEP) reanalysis data and output of the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) from 2015 to 2020 in Shenyang, we analyzed the variation of criteria air pollutants and meteorological elements in Shenyang during the epidemic of COVID-19 and evaluated the response of air quality to emission reduction and meteorological conditions. The results showed that mass concentrations of PM2.5, PM10, and NO2 in Shenyang during the epidemic of COVID-19 decreased, while O3 concentration slightly increased. PM2.5 and NO2 were more sensitive to anthropogenic emission reduction. PM2.5 concentration decreased by 16.37% due to meteorological conditions and by 22.96% due to the prevention and control measures. Under the background of prevention and control measures, adverse meteorological conditions and sudden enhancement in pollutant emissions caused heavy pollution periods, among which adverse meteorological conditions played a more important role. Meanwhile, the emission reduction measures significantly weakened the peak of pollutant concentration in heavy pollution events. © 2021, Science Press. All right reserved.

[Development and outlook on human challenge trial of vaccine].

Human challenge trial (HCT) is a test in which human volunteers are intentionally infected with pathogens in order to evaluate the efficacy of candidate preventive or therapeutic drugs. During the COVID-19 pandemic, the HCT of vaccines has aroused people's attention due to its significant advantages over clinical trial. This paper introduces the concept, development and application of HCT, the advantages and limitations of HCT for vaccine evaluation, and the consideration of future HCT of COVID-19 vaccine in China.

Conformity Consumer Behavior and External Threats: An Empirical Analysis in China During the COVID-19 Pandemic

Conformity consumer behavior refers to a preference of using the behaviors or expectations of others as a guideline for one's own consumption patterns. Significant characteristics of conformity consumer behavior have been observed during the COVID-19 pandemic, and it has greatly hindered resource allocation and pandemic management. Nonetheless, the reasons why a public health emergency, exemplified by COVID-19, triggers conformity consumer behavior remain unclear. This study proposes and tests a theoretical framework to explore the psychological mechanisms of conformity consumer behavior during the COVID-19 pandemic. Results indicate that pandemic severity positively affect conformity consumer behavior, sense of fear plays a mediating role between pandemic severity and conformity consumer behavior, and sense of control does not play a moderating role. This implies that fear drives conformity consumer behavior and people may tend to consume in this way when they perceive a strong sense of fear no matter how strong their sense of control is. The conclusion will help managers to guide consumer behavior during social crisis and emergencies.

The Impact of Lockdown on Air Quality in Pakistan during the COVID-19 Pandemic Inferred from the Multi-sensor Remote Sensed Data

The present study utilized multi-sensory gridded and reanalysis data in conjunction with the meteorological variables to evaluate the impact of lockdown due to the Coronavirus disease of 2019 (COVID-19) pandemic on the changes of concentration of atmospheric pollutants in Pakistan. We focused on assessing the significant changes of pollutant concentrations during March-May for the years 2019 and 2020 utilizing the satellite datasets observed from the Moderate Resolution Imaging Spectroradiometer (MODIS), Ozone Monitoring Instrument (OMI), Atmospheric Infrared Sounder (AIRS), and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis data. Low pollution levels were observed throughout the COVID-19 (March 25-May 31, 2020) compared to a similar period in 2019. The association of meteorology with air pollutants found that the periods of enhanced temperature and relative humidity likely contributed to a cleaner environment over the Indus Basin Region (IBR) and Balochistan Plateau (BP). The decrease in the mean planetary boundary layer Sulphur dioxide (SO2) during the lockdown period of 2020 (DLP-2020) was evident by -36% in BP, -34% in Khyber Pakhtunkhwa (KPK), and -15.15% in IBR when compared to before the lockdown period of 2019 (BLP-2019). This is attributed to the limited transportation and control action plans of industrial activities including combustion sources taken by the Government of Pakistan for the DLP-2020 phase. During DLP-2020, a variable and least significant decline in surface particulate matter of size 2.5 mu m (PM2.5) concentration was observed in the urban regions of KPK (-19.17%) followed by IBR (-0.82%) and BP (-0.26%). Overall, a considerable reductions in Carbon monoxide (CO) and black carbon (BC) concentrations were smaller in rural and suburban areas of BP (-3.61%, -8.57%) followed by KPK (-0.79%, -11.39%) and IBR (-3.30%, -11.39%), respectively. This is due to the reduction in local emissions related to the lockdown measures taken in the control of pandemic. However, the ozone (O-3) concentrations witnessed an increase to a lower extent as 11.39%, 5.78%, and 4.74% in KPK, BP, and IBR, respectively attributed to rising in solar radiation intensity and temperature in hot summers, and decrease in NOx levels during the study period.

Fee for home delivery and monitoring of art raises viral suppression in south africa

Background: Home delivery and monitoring of antiretroviral therapy (ART) is convenient, overcomes logistic barriers, and could increase ART adherence and viral suppression particularly among men who engage less in clinic-based HIV care than women. If clients pay for this service and the benefits are sufficient, it could be a scalable strategy. Methods: We conducted a randomized trial, the Deliver Health Study, of a fee for home delivery and monitoring of ART compared to clinic ART delivery in Pietermaritzburg, KwaZulu Natal, South Africa. People living with HIV on ART or willing to initiate ART in the community were recruited through communitybased testing or from facilities and randomized to: 1) fee for home delivery and monitoring of ART;or 2) clinic-based ART (standard of care). The one-time fee for home delivery was tiered based on participant income (ZAR 30, 60, and 90;equivalent to $2, 4, 6). The outcomes were payment of the fee for home delivery;acceptability of the delivery service;and viral suppression, assessed using loglinear regression adjusting for gender and age. Results: From October 2019-January 2020, 400 persons were screened;of the 180 persons living with HIV, 162 were enrolled - 82 randomized to the fee for home delivery group and 80 to the standard of care group. Overall, 87 participants (54%) were men, 22% were <30 years, 101 (62%) were on ART, and 98 (60%) were unemployed. Among participants in the fee for home delivery group, 40 (49%), 32 (40%), and 9 (11%) were in the ZAR 30, 60, and 90 fee groups, respectively. Median follow-up was 47 weeks (IQR 43-50 weeks) spanning COVID-19 restrictions. Retention at exit was 96%. In the fee payment group, 98% of participants paid the full user fee and acceptability was high with 100% reporting willingness to continue to pay a fee. Compared to standard clinic care, in the intent-to-treat analysis, fee for home delivery of ART significantly increased viral suppression from 74% to 88% (RR=1.21, 95% CI: 1.02-1.42) with a RR of 1.31 among men;fee group (84%, RR=1.31, 95% CI: 1.01-1.71) compared to standard of care (64%). Conclusion: Among South African adults living with HIV on ART or initiating ART, a fee for home delivery and monitoring of ART significantly increased viral suppression compared to clinic-based ART. Client payment of a fee for home delivery and monitoring of ART was highly acceptable in the context of low income and high unemployment, and improved health outcomes as a result.

DeepTrack: Monitoring and Exploring Spatio-Temporal Data - A Case of Tracking COVID-19

Spatio-temporal data analysis is very important in many time-critical applications. We take Coronavirus disease (COVID-19) as an example, and the key questions that everyone will ask every day are: how does Coronavirus spread? where are the high-risk areas? where have confirmed cases around me? Interactive data analytics, which allows general users to easily monitor and explore such events, plays a key role. However, some emerging cases, such as COVID-19, bring many new challenges: (C1) New information may come with different formats: basic structured data such as confirmed/suspected/serious/death/recovered cases, unstructured data from newspapers for travel history of confirmed cases, and so on. (C2) Discovering new insights: data visualization is widely used for storytelling;however, the challenge here is how to automatically find "interesting stories", which might be different from day to day. We propose DEEPTRACK, a system that monitors spatio-temporal data, using the case of COVID-19. For (C1), we describe (a) how we integrate and clean data from different sources by existing modules. For (C2), we discuss (b) how to build new modules for ad-hoc data sources and requirements, (c) what are the basic (or static) charts used;and (d) how to generate recommended (or dynamic) charts that are based on new incoming data. The attendees can use DeepTrack to interactively explore various COVID-19 cases.

[Investigation and analysis on anxiety and depression of 183 medical staffs during the epidemic period of the COVID-19].

Objective: To evaluate the degree of anxiety and depression of medical staff during the epidemic period of the COVID-19, and to provide theoretical basis for the pertinence psychological intervention timely. Methods: The investigation about the psychological status of 183 medical staffs on duty during the epidemic period was conducted using Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS) from 18th to 20th February, 2020, who came from Tianjin and other provinces. The respondents were divided into first-line and non-first-line groups according to their jobs, and local and non-local groups according to their work places, respectively. The data was collected by "Star Questionnaires" using the mobile terminal, and the statistical analysis was carried out to compare whether there were differences in depression and anxiety among medical staff of different groups. Results: The total SAS score (48.96±9.21) and SDS score (56.69±7.57) of all medical staff were higher than those of the national norm SAS (33.80±5.90) and SDS (41.88±10.57) from 1158 individuals (P<0.01) . Among 183 medical staff, the anxiety was found in 87 individuals and the rate of anxiety was 47.5%. The depression was found in 134 individuals and its rate was 73.2%. The anxiety combined with depression was found in 69 individuals and its rate was 37.7%. The scores of SAS and SDS of first-line group were (49.40±9.77) and (55.76±6.86) , respectively. And those of non-first-line group were (48.69±8.87) and (57.29±7.96) . They were higher than those of the national norm, and the differences were both statistically significant (P<0.01) , but there was no difference between the first-line group and non-first-line group. The scores of SAS and SDS of local group were (48.23±9.04) and (56.76±7.05) , while those of non-local group were (50.63±9.45) and (56.54±8.71) , respectively. The differences were statistically significant (P<0.01) , compared with the national norm respectively. But there was no difference between the local group and non-local group. No matter which classification criteria were used, there was no statistically significant difference in the severity distribution of anxiety and depression among different groups (P>0.05) . Conclusion: The anxiety and depression exist obviously among the medical staff during the epidemic period of the COVID-19, and the psychological intervention should be taken out in time.