Spatiotemporal evolution of urban theft crimes and mechanism in the context of regular COVID-19 pandemic prevention and control: A case study of Haining, Zhejiang

Existing studies show that the outbreak of the COVID-19 pandemic has a significant impact on crime occurrences. However, it remains to be empirically examined whether the regular pandemic prevention and control measures in China can significantly affect the spatial patterns of crimes. To fill this gap, this study chosed the central urban area of Haining City in Zhejiang Province, which had taken the regular pandemic prevention and control measures, as the research area. Using standard deviation ellipse and kernel density estimation methods, this study examined the spatiotemporal patterns of theft crimes between February 2018 and July 2021 in the study area. The results show that: 1) While there were no significant changes in the hourly patterns of theft crimes within a day, the monthly number of thefts in the study area decreased by an average of 53% after the outbreak of the COVID-19 pandemic and fluctuated between 100 to 200 thefts per month. The regular COVID-19 pandemic prevention and control measures had a long-term and stable inhibitory effect on the number of theft crimes in Haining City. 2) The intensity and amount of hotspots for theft crimes in the study area decreased significantly during February 2020 and July 2021 when compared with the pre-pandemic period, and the spatial distribution patterns of theft crimes were relatively stable. 3) For the 12 crime hotspots identified for the pre-pandemic period, the monthly number of crimes decreased between 52% and 78% on average after the outbreak while trajectories of their quarterly temporal changes differed significantly. The average crime drop for the 12 hotspot areas were 63%, which was higher than that for the whole study area. 4) Seven crime-control measures were identified among the regular pandemic prevention and control measures based on the routine activity theory and the crime triangle theory. Functional type of place, geographic location, and pre-pandemic local governance ability all played an important role in affecting the actual crime-control effects of the seven regular COVID-19 pandemic prevention and control measures. The results of this study are important for understanding the spatial evolution of crimes under the influence of major public health emergencies and for formulating scientific strategies for crime prevention and control. © 2023, Editorial office of PROGRESS IN GEOGRAPHY. All rights reserved.

Epidemiological investigation of an outbreak of human rhinovirus in a primary school in northern shaanxi

Objective To analyze the epidemiological characteristics of a Human rhinovirus outbreak in a primary school in northern Shaanxi, and to provide scientific evidence for the prevention and control. Methods On - site epidemiological investigation of an unexplained febrile aggregated outbreak reported in a primary school in northern Shaanxi on May 22, 2020. Nasopharyngeal swabs were collected from typical cases, and nucleic acid testing was performed to test for SARS COV 2, and 16 respiratory pathogens. Results A total of 37 cases were reported, including 1 adult teacher and 36 students, with the overall incidence rate of 1.75%, a male and female ratio of 3:1, and the incidence age mainly concentrated in 6 to 12 years old. The cases were mainly concentrated in 3 first-grade classes and 7 second-grade classes on the same floor, and the first grade cases accounted for 75.68% of the total number of cases. There was a statistically significant difference in the incidence rate of the cases in the classes (χ2 = 49.29, P<0.01). The clinical features of the cases were mainly fever (body temperature between 37.3 and 38.8°C), sore throat, runny nose, nasal congestion and cough, and some of which were accompanied by diarrhea and vomiting, and other gastrointestinal symptoms. Of the 33 nasopharyngeal swabs detected by laboratory, 14 were positive for Rhinovirus, and the positive rate was 42.42%. Conclusion This aggregated outbreak is caused by Rhinovirus infection. Primary and secondary schools in northern Shaanxi should be alert for aggregated unexplained fever due to Rhinovirus outbreaks during the epidemic season of respiratory infectious diseases. © 2023, Editorial Department of Medical Pest Control. All rights reserved.

Spatiotemporal Distribution and Influencing Factors of Theft during the Pre-COVID-19 and COVID-19 Periods: A Case Study of Haining City, Zhejiang, China

Theft is an inevitable problem in the context of urbanization and poses a challenge to people's lives and social stability. The study of theft and criminal behavior using spatiotemporal, big, demographic, and neighborhood data is important for guiding security prevention and control. In this study, we analyzed the theft frequency and location characteristics of the study area through mathematical statistics and hot spot analysis methods to discover the spatiotemporal divergence characteristics of theft in the study area during the pre-COVID-19 and COVID-19 periods. We detected the spatial variation pattern of the regression coefficients of the local areas of thefts in Haining City by modeling the influencing factors using the geographically weighted regression (GWR) analysis method. The results explained the relationship between theft and the influencing factors and showed that the regression coefficients had both positive and negative values in the pre-COVID-19 and COVID-19 periods, indicating that the spatial distribution of theft in urban areas of Haining City was not smooth. Factors related to life and work indicated densely populated areas had increased theft, and theft was negatively correlated with factors related to COVID-19. The other influencing factors were different in terms of their spatial distributions. Therefore, in terms of police prevention and control, video surveillance and police patrols need to be deployed in a focused manner to increase their inhibiting effect on theft according to the different effects of influencing factors during the pre-COVID-19 and COVID-19 periods.

Doing good right: building resilience through donations during the pandemic

PurposeWhile researchers recognize the significance of philanthropic donations in disaster relief and recovery, the benefits that firms derive from such donations remain unclear, particularly when firms are adversely impacted by the disaster. To address this gap, this study seeks to elucidate the impact of various donation strategies on firm resilience in the context of the COVID-19 pandemic.Design/methodology/approachBased on the hand-collected data on donations, the authors employ ordinary least squares regressions to investigate the effectiveness of various donation strategies - including type, timing and location - in enhancing firm resilience in terms of the severity of stock price losses during the pandemic. To address potential endogeneity concerns, the authors use a two-stage least squares regression with instrumental variables.FindingsThis study finds robust evidence that certain donation strategies are more effective at mitigating stock price losses during the pandemic. Specifically, the authors find that in-kind donations (compared to monetary ones), earlier donations (compared to later ones) and donations targeting severely impacted areas (Hubei province vs. other places) are more effective methods to reduce the severity of stock price losses.Originality/valueThis study points out an alternative mechanism through which donations influence firm resilience during a crisis context and provides important managerial implications for firms to better engage in disaster donations.

Impact of Telehealth and Process Virtualization on Healthcare Utilization

Technological advancements and the COVID-19 pandemic have catapulted process virtualization across many industries, including healthcare, where telehealth has enabled significant digital transformation of care delivery. Although telehealth has been proposed as a potential solution to improve access to care and restrain runaway healthcare costs, it can increase spending if telehealth use leads to new types of resource utilization. Drawing on the lens of process virtualization theory, we study the impact of telehealth on healthcare utilization by examining visit-level patient data of telehealth use in facilitating e-visits with healthcare providers. On average, a telehealth visit reduces the number of future outpatient visits by 13.6% (or 0.15 visits), equal to a reduction of $239 in total cost within 30 days after the visit. Our results suggest that the benefits of telehealth use are observed primarily among diseases with high virtualization potential. Specifically, patients with mental health, skin, metabolic, and musculoskeletal diseases exhibit a significant reduction of 0.21 outpatient visits per quarter (an equivalent cost reduction of $179) when they are treated via telehealth, suggesting a substitution effect with respect to traditional clinic visits. Our research identifies the boundary conditions that determine the nuanced impact of telehealth on care utilization and shows that its effectiveness depends on the process virtualization potential of different diseases. Our findings have several practical and theoretical implications for fostering telehealth use in a value-based healthcare environment, especially for diseases with high virtualization potential where telehealth use should be promoted to bend the cost curve.

Development of an Indirect ELISA Antibodies Detection Method on Tandem-epitope Peptide of African Swine Fever Virus p30 and p54 Proteins.

Here, we report the development of an indirect ELISA antibodies detection method for African swine fever virus (ASFV). Two purified monoclonal antibodies (mAbs) against ASFV p30 and p54 protein were used as targets and a phage-displayed 12-mer peptide library was used to conduct four rounds of biopanning to screen peptide epitopes, then amino acids GGG was used as a linker to synthesize tandem-epitope peptide of ASFV p30 and p54 protein which was used as coating antigen. The optimum reaction conditions of indirect ELISA were determined by chessboard titration, and clinical serum samples were used to evaluate the specificity, sensitivity, stability and conformity of this method. The biopanning experiment indicated that 146PAEPYTT152 was a core domain of the B cell linear epitope of p54 protein. The optimization results of ELISA reaction conditions showed that the tandem-epitope peptide coupled with ovalbumin (OVA) at N-terminal had low background of non-specific serum reaction. And the optimum reaction effect was obtained when the polypeptide antigen was coated with carbonate buffer in 2 mug.mL-1, the serum was diluted 100-fold with blocking solution (1% gelatin solution), and the HRP-antibody was diluted 5 000 times with 0.05% PBST solution. The cut-off value was determined to be 0.339. Furthermore, the results of specificity, sensitivity and stability tests showed that there is no cross-reaction in positive serum samples of classical swine fever virus (CSFV), porcine reproductive and respiratory syndrome virus (PRRSV), porcine circovirus type 2 (PCV2), porcine parvovirus (PPV) and porcine pseudorabies virus (PRV), the detection limit of ASFV positive sera is 1:1 600, and the method had high repeatability. Finally, Total 320 swine serum samples were detected simultaneously by the present established method and commercial ASFV antibody detection kit. The results showed that the relative specificity and sensitivity of the two methods were 97.6% and 97.3%, respectively. And the coincidence rate was 97.5%. In conclusion, this method showed good specificity, sensitivity, repeatability and coincidence rate, that had the potential value of developing clinical diagnostic kit.Copyright © 2022 Editorial Board, Institute of Animal Science of the Chinese Academy of Agricultural Sciences. All rights reserved.

Comparison of adaptive thermal comfort with face masks in library building in Guangzhou, China

During the COVID-19 pandemic, wearing masks in public spaces has become a protective strategy. Field tests and questionnaire surveys were carried out at a university library in Guangzhou, China, during June 2021 and January 2022. The indoor environmental parameters were observed, thermal sensation votes of students on various environmental parameters were collected, symptoms of students wearing masks were quantified, and the appropriate amount of time to wear masks was established. To identify acceptable and comfortable temperature ranges, the relationship between thermal sensation and thermal index was investigated. During summer and winter, people wearing masks are symptomatic for a certain duration. The most frequently voted symptom was facial heat (62.7 % and 54.6 % during summer and winter, respectively), followed by dyspnea. During summer, more than 80 % of the participants subjects were uncomfortable and showed some symptoms after wearing masks for more than 2 h (3 h during winter). In the summer air conditioning environment in Guangzhou, the neutral Top was 26.4 °C, and the comfortable Top range was 25.1–27.7 °C. Under the natural ventilation environment in winter, the neutral Top was 20.5 °C, and the comfortable Top range was 18.5–22.5 °C. This study may provide guidance for indoor office work and learning to wear masks in Guangzhou. © 2022 Elsevier Ltd

Breast Cancer Screening, Diagnosis, and Surgery during the Pre- and Peri-pandemic: Experience of Patients in a Statewide Health Information Exchange.

BACKGROUND: Measures taken to address the COVID-19 pandemic interrupted routine diagnosis and care for breast cancer. The aim of this study was to characterize the effects of the pandemic on breast cancer care in a statewide cohort. PATIENTS AND METHODS: Using data from a large health information exchange, we retrospectively analyzed the timing of breast cancer screening, and identified a cohort of newly diagnosed patients with any stage of breast cancer to further access the information available about their surgical treatments. We compared data for four subgroups: pre-lockdown (preLD) 25 March to 16 June 2019; lockdown (LD) 23 March to 3 May 2020; reopening (RO) 4 May to 14 June 2020; and post-lockdown (postLD) 22 March to 13 June 2021. RESULTS: During LD and RO, screening mammograms in the cohort decreased by 96.3% and 36.2%, respectively. The overall breast cancer diagnosis and surgery volumes decreased up to 38.7%, and the median time to surgery was prolonged from 1.5 months to 2.4 for LD and 1.8 months for RO. Interestingly, higher mean DCIS diagnosis (5.0 per week vs. 3.1 per week, p < 0.05) and surgery volume (14.8 vs. 10.5, p < 0.05) were found for postLD compared with preLD, while median time to surgery was shorter (1.2 months vs. 1.5 months, p < 0.0001). However, the postLD average weekly screening and diagnostic mammogram did not fully recover to preLD levels (2055.3 vs. 2326.2, p < 0.05; 574.2 vs. 624.1, p < 0.05). CONCLUSIONS: Breast cancer diagnosis and treatment patterns were interrupted during the lockdown and still altered 1 year after. Screening in primary care should be expanded to mitigate possible longer-term effects of these interruptions.

Multi-MedVit: a deep learning approach for the diagnosis of COVID-19 with the CT images

The grim situation of novel coronavirus pneumonia 2019 (COVID-19) and its terrible spreading speed have already constituted a severe risk to human life, so it is ultimately essential to rapidly and accurately diagnose for COVID-19 pneumonia. Based on this study's 746 lung CT images, we propose Multi-MedVit, a novel auxiliary COVID-19 diagnosis framework based on the multi-input Transformer. We compare Multi-MedVit with state-of-the-art deep learning methods, such as CNN, VGG16, and ResNet50. Multi-MedVit outperformed the other methods on the benchmark dataset and proved that multiscale data input for data augmentation helped enhance model stability. Based on an interpretable analysis of the input and output of Multi-MedVit, we found that with the support of the training set data, the model has been possible to accurately focus on the lesion area for diagnosis of COVID-19 without expert annotations, which can provide initial references containing more potential information to doctors more precisely and fleetly. © 2022 IEEE.

Navigating Robots in Dynamic Environment With Deep Reinforcement Learning

In the fight against COVID-19, many robots replace human employees in various tasks that involve a risk of infection. Among these tasks, the fundamental problem of navigating robots among crowds, named robot crowd navigation, remains open and challenging. Therefore, we propose HGAT-DRL, a heterogeneous GAT-based deep reinforcement learning algorithm. This algorithm encodes the constrained human-robot-coexisting environment in a heterogeneous graph consisting of four types of nodes. It also constructs an interactive agent-level representation for objects surrounding the robot, and incorporates the kinodynamic constraints from the non-holonomic motion model into the deep reinforcement learning (DRL) framework. Simulation results show that our proposed algorithm achieves a success rate of 92%, at least 6% higher than four baseline algorithms. Furthermore, the hardware experiment on a Fetch robot demonstrates our algorithm’s successful and convenient migration to real robots. IEEE

[Epidemiological characteristics of two local COVID-19 outbreaks caused by 2019-nCoV Omicron variant in Guangzhou, China].

Objective: To understand the epidemiological characteristics of two local COVID-19 outbreaks caused by 2019-nCoV Omicron variant in Guangzhou, such as incubation period, serial interval, basic reproductive number (R0) and the influence of gathering places on R0, and provide evidence for the prevention and control of Omicron variant infection. Methods: The data of daily confirmed cases of Omicron variant infection from April 8 to May 8, 2022 in two COVID-19 outbreaks in Guangzhou were collected for model fitting. Weibull, Gamma and lognormal distribution were used to estimate incubation period and serial interval. Exponential growth method and the maximum likelihood estimation were used to estimate R0. Results: The median of incubation period was 2.94 (95%CI: 2.52-3.38) days and median of serial interval was 3.32 (95%CI: 2.89-3.81) days. The estimated R0 in small-size place was 4.40 (95%CI: 3.95-4.85), while the estimated R0 at airport was 11.35 (95%CI: 11.02-11.67). Conclusion: The incubation period of Omicron variant in two local COVID-19 outbreaks in Guangzhou is significantly shorter than that of delta variant. The higher the gathering degree in a place, the larger the R0. Due to its rapid transmission, COVID-19 epidemic is prone to occur. Therefore, the COVID-19 prevention and control strategy should be dynamically adjusted in time.

Association of Ventilator Settings and Lung Mechanics During VV-ECMO Treatment with Short Term Pulmonary Function and Lung Imaging Outcomes in COVID-19 Survivors, a Retrospective Cohort Study

Background: Lung protective ventilation plays a crucial role in the management of patients with COVID-19 ARDS treated with VV-ECMO. We hypothesized that increasingly protective ventilator settings may be associated with improved lung recovery by reducing ventilator induced lung injury. Method(s): We performed a retrospective cohort study of all patients treated with VV-ECMO for COVID-19 at NYU Langone Medical Center from March 2020 to June 2020. Ventilator data including tidal volume (cc/ kg predicted body weight), peak airway pressure, PEEP, Driving pressure (DP), Respiratory Rate, FiO2, lung compliance, and mechanical power were obtained. Pulmonary function test (PFT) results, 6-minute walk test results, and quantitative chest CT scores were obtained from the first outpatient follow up assessment. Bivariate and multivariate analysis correlating ventilator data with lung function and CT outcomes was performed. Result(s): 30 COVID-19 patients were treated with VV-ECMO during the study period, of which 26 survived without lung transplantation and 12 completed follow up assessment at a median of 106 days post ECMO decannulation. Multivariate LASSO regression model results;FEV1: DP (beta=-5.535), Respiratory Rate (beta=-0.370), compliance (beta=0.467), FVC: DP (beta=-4.08), compliance (beta=0.875), preECMO tidal volume (beta=-0.0008), TLC: DP (beta=-4.518), ECMO sweep (beta=-0.598), DLCO: peak airway presure (beta=-1.836), 6MWT distance: compliance (beta=1.436), Chest CT total opacity score: DP(beta=-0.60), preECMO tidal volume(beta=-0.0033). Conclusion(s): Driving pressure and peak airway pressure during VV-ECMO had the strongest associations with improved short-term follow up lung volumes, DLCO, and chest CT outcomes in VV-ECMO treated COVID-19 survivors.

Changes in cancer-related mortality during the COVID-19 pandemic in the United States

Background: The coronavirus disease 2019 (COVID-19) pandemic resulted in delayed medical care that may have led to increased death rates in 2020 among people with medical conditions such as cancer. This study examined changes in cancer-related mortality between 2019 and 2020. Methods: We used the US 2019-2020 Multiple Cause of Death database from the CDC WONDER to identify cancer-related deaths, defined as decedents with invasive or noninvasive cancer as a contributing cause of death (ICD-10 codes: C00-C97 and D00-D09). We compared age-standardized cancer-related annual and monthly mortality rates (per 100,000 person-years and person-months, respectively) in January-December 2020 (pandemic) versus January-December 2019 (pre-pandemic) overall and stratified by rurality and place of death. We calculated the 2020 excess death by comparing the numbers of observed death with the projected death based on age-specific cancer-related death rate from 2015 to 2019. Results: The number of cancer-related deaths was 686 054 in 2020, up from 664 888 in 2019, with an annual increase of 3.2%. Compared to the number of projected deaths for 2020 (666 286), the number of cancer-related excess deaths was 19 768 in 2020. Annual age-standardized cancer-related mortality rate (per 100,000 person-years) continuously decreased from 173.7 in 2015 to 162.1 in 2019, while it increased to 164.1 in 2020 (2020 vs 2019 rate ratio (RR): 1.013, 95% confidence interval (CI): 1.009 - 1.016). The cancer-related monthly mortality rate was higher in April 2020 (RR: 1.032, 95% CI: 1.020 - 1.044) when healthcare capacity was most challenged by the pandemic, subsequently declined in May and June 2020, and higher mortality rates were again observed each month from July to December 2020 compared to 2019. In large metropolitan areas, the largest increase in cancer-related mortality was observed in April 2020, while in non-metropolitan areas, the largest increases occurred from July to December 2020, coinciding with the time-spatial pattern of COVID-19 incidence in the country. Compared to 2019, cancer-related mortality rates were lower from March to December 2020 in medical facilities, hospice facilities, and nursing homes or long-term care settings but higher in decedent's homes. Conclusions: The COVID-19 pandemic led to significant increases in cancer-related deaths in 2020 versus 2019. Ongoing evaluation of the spatialtemporal effects of the pandemic on cancer care and outcomes is warranted, especially in relation to patterns in vaccine uptake and COVID-19 hospitalization rates.

Antiviral effect of Fufang yinhua jiedu (FFYH) granules against coronavirus and its potential mechanism

To investigate the effect of Fufang yinhua jiedu (FFYH) granules against coronavirus and its potential mechanism, we used Huh7, Huh7.5, H460, and C3A cell lines as in vitro models to evaluate the cytotoxicity and antiviral activity of FFYH by observation of cell pathogenic effect (CPE);and then the inhibitory effect of FFYH on the transcription expression of coronavirus RNA and inflammatory factor mRNA were evaluated by quantitive reverse transcription PCR (qRT-PCR);finally, the inhibitory effect of FFYH on the expression of coronavirus protein and its underlying mechanism against coronavirus were investigated by Western blot and immunofluorescence. Our results indicated that 50% toxic concentration (TC50) FFYH on Huh7, Huh7.5, H460, and C3A cells were 2 035.21, 5 245.69, 2 935.28 and 520 µg·mL-1, respectively;50% inhibitory concentration (IC50) of FFYH on HCoV-229E in Huh7 and Huh7.5 cells were 438.16 and 238.54 µg·mL-1 with safety index (SI) of 4.64 and 21.99, respectively;IC50 of FFYH on HCoV-OC43 in H460 cells was 165.13 µg·mL-1 with SI of 17.78. Moreover, FFYH not only could inhibit the replication of coronaviruses (HCoV-OC43 and HCoV-229E) through inhibiting the transcription of viral RNA and the expression of viral protein, but also effectively suppress the expression of inflammatory factors interleukin-6 (IL-6), tumor necrosis factor α (TNF-α) and interleukin-8 (IL-8) at mRNA level caused by coronaviruses, which might be associated with the inhibitory effect of FFYH on mitogen-activated protein kinase (MAPK) pathway and the nuclear translocation of nuclear transcription factor-κB (NF-κB). In summary, our results demonstrated that FFYH exhibited a good in vitro anti-coronavirus effect, which provides a theoretical basis for its clinical use in the treatment of anti-coronavirus pneumonia.

Development and Application of Global Health Events-Mental Stress Scale for Assessment of Medical Staff?s Acute Mental Stress Responses

Background: Medical workers have been increasingly involved in emergent public health events, which can lead to severe stress. However, no standardized, officially recognized, unified tool exists for mental distress measurement in medical workers who experienced the public health events. Purpose: In the present study, we propose the Global Health Events-Mental Stress Scale (GHE-MSS), as a revised version of the Impact of Event Scale-Revision (IES-R), for assessment of medical workers' acute mental stress responses within one month and their chronic mental stress responses within six months after major health events. Patients and methods: The IES-R was slightly modified, developed, and its reliability and validity were tested using the Delphi survey, primary survey with 115 participants, formal survey with 300 participants, and clinical evaluation with 566 participants. Results: Exploratory factor analysis and confirmatory factor analysis confirmed a promising validity of the scale. The values of Cronbach's alpha coefficient, the Spearman-Brown coefficient, and the retested Cronbach's alpha coefficient of the scale applied for the clinical evaluation were 0.88, 0.87, and 0.98, respectively, which confirmed a good internal consistency and stability. The results of the goodness-of-fit test indicated a good adaptation of the model. A correlation analysis was conducted to assess the correlation between the GHE-MSS and the PCL-C, which had a correlation coefficient of 0.68 (P < 0.01). Conclusion: GHE-MSS can be applied with a promising reliability and validity for the assessment of the acute mental stress response of medical workers experiencing public health events. This method can also be used for the screening of mental stress-associated disorders.

On the Test Accuracy and Effective Control of the COVID-19 Pandemic: A Case Study in Singapore

This study examines the impact of coronavirus disease 2019 (COVTD-19) test accuracy (i.e., sensitivity and specificity) on the progression of the pandemic under two scenarios of limited and unlimited test capacity. We extend the classic susceptible-exposed-infectious-recovered model to incorporate test accuracy and compare the progression of the pandemic under various sensitivities and specificities. We find that high-sensitivity tests effectively reduce the total number of infections only with sufficient testing capacity. Nevertheless, with limited test capacity and a relatively high cross-infection rate, the total number of infected cases may increase when sensitivity is above a certain threshold. Despite the potential for higher sensitivity tests to identify more infected individuals, more false positive cases occur, which wastes limited testing capacity, slowing down the detection of infected cases. Our findings reveal that improving test sensitivity alone does not always lead to effective pandemic control, indicating that policymakers should balance the trade-off between high sensitivity and high false positive rates when designing containment measures for infectious diseases, such as COVID-19, particularly when navigating limited test capacity.

A prospective cohort study of the presence of SARS-CoV-2 in clinical samples from multiple bodily sites: implications for transmission routes of COVID-19

Objective: The coronavirus disease 2019 (COVID-19) epidemic resulting from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has still spread globally. The occurrence of the Delta variant, which is more infectious and spreads faster than earlier forms of the virus that causes COVID-19, makes infection prevention more challenging. Therefore, this study aimed to gain a comprehensive insight into the transmission routes of SARS-CoV-2 for curbing the propagation of SARS-CoV-2 in human populations. Methods: We studied a prospective cohort of 576 patients admitted consecutively to the First Affiliated Hospital of Guangzhou Medical University from January 21 to June 8, 2020. These patients were chosen based on their similar clinical phenotypes or imaging findings. There were 21 (3.6%) laboratory-confirmed COVID-19 patients (16 severe and 5 mild cases) and 555 non-COVID-19 patients. The antibody response and routes and duration of viral shedding were systematically evaluated in serial clinical specimens. Moreover, SARS-CoV-2 RNA was also detected in a mouth rinse, urine, and tear samples. This study was approved by the Medical Ethical Committee of The First Affiliated Hospital of Guangzhou Medical University (approval No. 2020-77). Results: SARS-CoV-2 mainly existed in sputum, nasal and throat swabs, and feces samples. Virus latency was longer in sputum and feces samples than in nasopharyngeal samples. IgG antibody response in respiratory samples was related to disease severity. Although droplets and aerosols are the major transmission routes for COVID-19, covert routes of transmission from asymptomatic patients, contaminated surfaces, and wastewater are also of interest. Conclusion: Our findings provide a solid foundation for developing prophylactic measures against SARS-CoV-2.

Intelligent System for Distributed Social Governance Based on Big Data

In recent years, promoting the synergy and intelligence of social governance, and improving the social governance system of co-construction, co-governance and sharing are important development directions for the country. As a production factor, data plays an increasingly critical role in social governance. How to realize the secure query, collaborative management, and intelligent analysis of multi-party massive data is the key issue to improve the effectiveness of social governance. In major public events such as the prevention and control of the COVID-19, distributed social governance faces low computing efficiency, poor multi-party credible coordination, and difficult decision-making for complex tasks. In response to the above challenges, this study proposes on big data based distributed social governance intelligent system based on secure multi-party computing, blockchain technology, and precise intelligence theory. The proposed system can support various applications of social governance that provide decision-making support for the improvement of social governance in the new era. © Copyright 2022, Institute of Software, the Chinese Academy of Sciences. All rights reserved.