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

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

[Current research in liver transplantation during the Covid-19 pandemic].

The coronavirus disease (Covid-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has drastically changed our daily life and clinical practice.Due to the reduction of liver transplantation and the liver injury caused by SARS-CoV-2 infection during the pandemic,the prognosis of waitinglisted liver transplant candidates is worse.Due to the long-term immunosuppressive therapy of liver recipients,their risk of infection is higher than the general population.Although some studies suggested that immunosuppressive therapy seems to have a protective effect in infected patients,it also leads to chronic infection.Due to the concerns about the risk of virus transmission,expert consensus does not recommend the utilization of donor livers with the history of Covid-19.Currently,published articles do not support the argument that virus can be transmitted to recipients through donor livers.Therefore,the feasibility of liver transplantation utilizing donor livers with SARS-CoV-2 infection remains controversial.In this article,current advances in liver transplantation during the Covid-19 pandemic are reviewed to provide a new perspective for liver transplantation in the future.

Nationwide evaluation of energy and indoor air quality predictive control and impact on infection risk for cooling season

Since the coronavirus disease 2019, the extended time indoors makes people more concerned about indoor air quality, while the increased ventilation in seeks of reducing infection probability has increased the energy usage from heating, ventilation, and air-conditioning systems. In this study, to represent the dynamics of indoor temperature and air quality, a coupled grey-box model is developed. The model is identified and validated using a data-driven approach and real-time measured data of a campus office. To manage building energy usage and indoor air quality, a model predictive control strategy is proposed and developed. The simulation study demonstrated 18.92% energy saving while maintaining good indoor air quality at the testing site. Two nationwide simulation studies assessed the overall energy saving potential and the impact on the infection probability of the proposed strategy in different climate zones. The results showed 20%–40% energy saving in general while maintaining a predetermined indoor air quality setpoint. Although the infection risk is increased due to the reduced ventilation rate, it is still less than the suggested threshold (2%) in general. © 2022, Tsinghua University Press.

Strategies of German Bundesliga and English Premier League clubs for the COVID-19 crisis: the case of international broadcasting fans

During the COVID-19 pandemic that paused sports worldwide, the German Bundesliga League (GBL) and English Premier League (EPL) took two different strategic approaches to agree with their players on returning to play. To become better informed and prepared for future crisis management, this study examines consumer responses to these opposing strategies. We also identify how perceived organizational legitimacy, trustworthiness, reliance, and justifiability have an impact on consumer multimedia consumption of the games. A sample of 503 participants responded to an online questionnaire regarding the contrasting decisions taken by the GBL and the EPL during the global health crisis. SEM with multi-group analysis was conducted to test the research hypotheses. When comparing the two selected sport leagues, the league that reached an agreement with their players experienced higher levels of perceived legitimacy while needing fewer perceptions of trustworthiness, reliance, and justifiability to obtain higher multimedia consumption intention from consumers. © 2022, The Author(s).

Using geospatial social media data for infectious disease studies: a systematic review

Geospatial social media (GSM) data has been increasingly used in public health due to its rich, timely, and accessible spatial information, particularly in infectious disease research. This review synthesized 86 research articles that use GSM data in infectious diseases published between December 2013 and March 2022. These articles cover 12 infectious disease types ranging from respiratory infectious diseases to sexually transmitted diseases with spatial levels varying from the neighborhood, county, state, and country. We categorized these studies into three major infectious disease research domains: surveillance, explanation, and prediction. With the assistance of advanced computing, statistical and spatial methods, GSM data has been widely and deeply applied to these domains, particularly in surveillance and explanation domains. We further identified four knowledge gaps in terms of contextual information use, application scopes, spatiotemporal dimension, and data limitations and proposed innovation opportunities for future research. Our findings will contribute to a better understanding of using GSM data in infectious diseases studies and provide insights into strategies for using GSM data more effectively in future research.

Nationwide evaluation of energy and indoor air quality predictive control and impact on infection risk for cooling season

Since the coronavirus disease 2019, the extended time indoors makes people more concerned about indoor air quality, while the increased ventilation in seeks of reducing infection probability has increased the energy usage from heating, ventilation, and air-conditioning systems. In this study, to represent the dynamics of indoor temperature and air quality, a coupled grey-box model is developed. The model is identified and validated using a data-driven approach and real-time measured data of a campus office. To manage building energy usage and indoor air quality, a model predictive control strategy is proposed and developed. The simulation study demonstrated 18.92% energy saving while maintaining good indoor air quality at the testing site. Two nationwide simulation studies assessed the overall energy saving potential and the impact on the infection probability of the proposed strategy in different climate zones. The results showed 20%-40% energy saving in general while maintaining a predetermined indoor air quality setpoint. Although the infection risk is increased due to the reduced ventilation rate, it is still less than the suggested threshold (2%) in general.

[Survey on infection source of a cold-chain product associated COVID-19 epidemic caused by 2019-nCoV Delta variant in Beijing].

Objective: To investigate the source and the transmission chain of a cold-chain product associated COVID-19 epidemic caused by 2019-nCoV Delta variant in Beijing. Methods: Epidemiological investigation were used to verify the exposure points of the cases. Close contacts were traced from the exposure points, and human and environmental samples were collected for nucleic acid tests. Positive samples were analyzed by gene sequencing. Results: A total of 112 cases of COVID-19 were reported in the epidemic from January 18 to February 6, 2022 in Beijing. Except for 1 case was uncertain, there were epidemiological links among 111 cases. The source of infection was the packages of imported cold-chain products from Southeast Asia, which were harvested and stored in a local cold-storage in January 2021, and packaged and sent to the cold-storage A in A district in June 2021, and then sold in batches in cold-storage B in B district from January 2022. The first case was infected in the handling of positive frozen products, and then 77 cases occurred due to working, eating and living together with the index case in the cold-storage B, cold-storage C and restaurant D. Besides the cold-storage B, C and the restaurant D, there were 16 sub-transmission chains, resulting in additional 35 cases. Conclusion: The epidemic indicated that the risk of 2019-nCoV infection from imported cold-chain products contaminated by package and highlighted the importance to strengthen the management of cold-chain industry in future.

[Survey of possible aerosol transmission of a COVID-19 epidemic caused by 2019-nCoV Delta variant].

Objective: To investigate the epidemiological characteristics and the transmission chain of a family clustering of COVID-19 cases caused by severe acute respiratory 2019-nCoV Delta variant in Changping district of Beijing. Methods: Epidemiological investigation was conducted and big data were used to reveal the exposure history of the cases. Close contacts were screened according to the investigation results, and human and environmental samples were collected for nucleic acid tests. Positive samples were analyzed by gene sequencing. Results: On November 1, 2021, a total of 5 COVID-19 cases caused by 2019-nCoV Delta variant were reported in a family detected through active screening. The infection source was a person in the same designated isolation hotel where the first case of the family cluster was isolated from 22 to 27, October. The first case was possibly infected through aerosol particles in the ventilation duct system of the isolation hotel. After the isolation discharge on October 27, and the first case caused secondary infections of four family members while living together from October 27 to November 1, 2021. Conclusion: 2019-nCoV Delta variant is prone to cause family cluster, and close attention needs to be paid to virus transmission through ventilation duct system in isolation hotels.

Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence

Artificial intelligence provides a promising solution for streamlining COVID-19 diagnoses;however, concerns surrounding security and trustworthiness impede the collection of large-scale representative medical data, posing a considerable challenge for training a well-generalized model in clinical practices. To address this, we launch the Unified CT-COVID AI Diagnostic Initiative (UCADI), where the artificial intelligence (AI) model can be distributedly trained and independently executed at each host institution under a federated learning framework without data sharing. Here we show that our federated learning framework model considerably outperformed all of the local models (with a test sensitivity/specificity of 0.973/0.951 in China and 0.730/0.942 in the United Kingdom), achieving comparable performance with a panel of professional radiologists. We further evaluated the model on the hold-out (collected from another two hospitals without the federated learning framework) and heterogeneous (acquired with contrast materials) data, provided visual explanations for decisions made by the model, and analysed the trade-offs between the model performance and the communication costs in the federated training process. Our study is based on 9,573 chest computed tomography scans from 3,336 patients collected from 23 hospitals located in China and the United Kingdom. Collectively, our work advanced the prospects of utilizing federated learning for privacy-preserving AI in digital health. The COVID-19 pandemic sparked the need for international collaboration in using clinical data for rapid development of diagnosis and treatment methods. But the sensitive nature of medical data requires special care and ideally potentially sensitive data would not leave the organization which collected it. Xiang Bai and colleagues present a privacy-preserving AI framework for CT-based COVID-19 diagnosis and demonstrate it on data from 23 hospitals in China and the United Kingdom.

The LPGA's global tour and domestic audience: factors influencing viewer's intention to watch in the United States. (Special Issue: SportsWorld V: the evolving SportsWorld: sports and physical activities in the time of COVID-19.)

The purpose of current study was to examine the impact of potential factors that influence audience's attitude toward and intention to watch LPGA tournaments that are typically led by a large number of foreign golfers today. Research participants (N = 375) were LPGA consumers who responded to a questionnaire administered online. SEM analysis was performed to investigate the impact of diversity beliefs, cultural familiarity, perceived image, and femininity on attitude toward and intention to watch. The results revealed positive influence of perceived image and femininity on audience's attitude, while negative impact of assimilation belief on attitude was identified. Furthermore, positive associations between attitude and intention as well as subjective norm and intention were confirmed. These findings suggest that promotion of the image of tour-leading foreign golfers and femininity would be useful to attract media spectators while promotion of diversity mitigating audiences' belief on assimilation approach can be effective under the new globalized tour environment.

How do perceptions of non-mega sport events impact quality of life and support for the event among local residents? (Special Issue: SportsWorld V: the evolving SportsWorld: sports and physical activities in the time of COVID-19.)

Previous research has overlooked the influence of non-mega sport events on local residents' perceptions of quality of life and their attitude toward the hosting of events;in particular, there is a major research void in understanding residents' opinions in Chinese cities that are making escalated efforts in staging small to medium size sport events. This study examined the relationships among the perceived impacts of sport event, quality of life, and event support of local residents at a marathon event in China. Findings revealed that perceived psychological and social impacts by local residents were found to be positively predictive of their quality of life and event support, perceived economic impact had no significant influence, perceived environmental impact was significant in facilitating residents' quality of life although it was not influential of their support for the event directly. Implications are discussed furtherly.

Risk factors for severe disease and efficacy of treatment in patients infected with COVID-19: a systematic review, meta-analysis, and meta-regression analysis. (COVID special issue #2.)

The coronavirus disease 2019 (COVID-19) pandemic spread globally in the beginning of 2020. At present, predictors of severe disease and the efficacy of different treatments are not well understood. We conducted a systematic review and meta-analysis of all published studies up to 15 March 2020, which reported COVID-19 clinical features and/or treatment outcomes. Forty-five studies reporting 4203 patients were included. Pooled rates of intensive care unit (ICU) admission, mortality, and acute respiratory distress syndrome (ARDS) were 10.9%, 4.3%, and 18.4%, respectively. On meta-regression, ICU admission was predicted by increased leukocyte count (P < .0001), alanine aminotransferase (P=.024), and aspartate transaminase (P=.0040);elevated lactate dehydrogenase (LDH) (P < .0001);and increased procalcitonin (P < .0001). ARDS was predicted by elevated LDH (P < .0001), while mortality was predicted by increased leukocyte count (P=.0005) and elevated LDH (P < .0001). Treatment with lopinavir-ritonavir showed no significant benefit in mortality and ARDS rates. Corticosteroids were associated with a higher rate of ARDS (P=.0003).

PATIENTS UNDERGOING ASSISTED REPRODUCTIVE CYCLES ARE MORE LIKELY TO FOLLOW UP AFTER ATTEMPTED OUTREACH COMPARED WITH INTRAUTERINE INSEMINATION CYCLES DURING THE COVID-19 PANDEMIC

Objective: As COVID-19 has been spreading rapidly both globally and throughout the US, public fear of contracting and spreading the virus has greatly hindered access to medical care including fertility clinics. Given the time-sensitive nature of fertility treatment, especially in older women, the American Society of Reproductive Medicine published updated guidelines for clinics to safely resume fertility services on April 24, 2020. The purpose of this study was to assess whether contacting established patients who missed or cancelled follow-up appointments via phone calls improved patient retention in the midst of the COVID-19 global pandemic. Design: Practice management analysis. Materials and Methods: Patients undergoing fertility treatment during the COVID-19 pandemic and who missed scheduled follow-up appointments were contacted by designated clinical staff members. Patients who desired to continue their treatment were offered either physical appointments or telehealth consultations. The contacting staff member documented patient responses and demographics in a master spreadsheet. Approximately 1-4 weeks after the patients were initially contacted, their charts were revisited to determine if the follow-up prompted patients to pursue future treatment. A Chi-square test was used to compare outcomes between Assisted Reproductive Technology (ART) cycles and Intrauterine Insemination (IUI) cycles. Results: There were 700 patients identified who underwent 215 IUI cycles and 709 ART cycles in the form of Egg Retrieval (ER) or Embryo Transfer (ET) between January 2020 - April 2020. The average age of all patients undergoing IUI and ART was 37.9 and 39.6, respectively (p=0.001). The clinical team contacted 88 IUI and 213 ART patients who missed a follow-up appointment scheduled 2 weeks after undergoing their procedure. Of those contacted, 13 (15%) IUI patients and 72 (34%) ART patients scheduled appointments with their physicians (p=0.001). Fear about COVID-19 was cited as the most common reason for missing their follow-up appointment (p=0.001). Conclusions: These data support contacting patients lost to follow-up in order to improve patient retention rates. Patients who had undergone ART treatment were more likely to resume care compared to those who had IUI treatment. One explanation is that IUI patients may be more comfortable delaying active treated while attempting unmonitored timed intercourse cycles at home. There also may be differences in the population of patients undergoing ART vs IUI cycles, such as fertility prognosis or financial implications. Tracking patients during the pandemic also identified those who became pregnant post-procedure and helped ensure early monitoring when appropriate, but this data is not presented here. Lastly, the follow-up initiative provided clinical teams with a unique opportunity to assess patient satisfaction, as well as employee productivity during these difficult times. References: None

Comprehensive comparison and analysis of the prevention and treatment of coronavirus disease 2019 and severe acute respiratory syndrome with traditional chinese medicine

Since December 2019 the Coronavirus Disease 2019 (COVID-19) has erupted in many places around the world, which is strong infectious and highly epidemic. After the outbreak of COVID-19 in China, traditional Chinese medicine (TCM) has been in the front line of the fight against the epidemic. It has shown characteristics and advantages in the prevention and treatment of COVID-19. TCM also played an important role in the winter of 2002 and in the spring of 2003 during the outbreak of severe acute respiratory syndrome (SARS). This article compares the strategies, programs, measures, resource investments, and effects of TCM for the prevention and treatment of COVID-19 with those for SARS. At present, the involvement of TCM has been earlier, faster, and more comprehensive in the fight against the epidemic and has shown good clinical efficacy and treatment prospects.

Coronavirus disease 2019: a bibliometric analysis and review.

OBJECTIVE: On December 8, 2019, many cases of pneumonia with unknown etiology were first reported in Wuhan, China, subsequently identified as a novel coronavirus infection aroused worldwide concern. As the outbreak is ongoing, more and more researchers focused interest on the COVID-19. Therefore, we retrospectively analyzed the publications about COVID-19 to summarize the research hotspots and make a review, to provide reference for researchers in the world. MATERIALS AND METHODS: We conducted a search in PubMed using the keywords "COVID-19" from inception to March 1, 2020. Identified and analyzed the data included title, corresponding author, language, publication time, publication type, research focus. RESULTS: 183 publications published from 2020 January 14 to 2020 February 29 were included in the study. The first corresponding authors of the publications were from 20 different countries. Among them, 78 (42.6%) from the hospital, 64 (35%) from the university and 39 (21.3%) from the research institution. All the publications were published in 80 different journals. Journal of Medical Virology published most of them (n=25). 60 (32.8%) were original research, 29 (15.8%) were review, 20 (10.9%) were short communications. 68 (37.2%) epidemiology, 49 (26.8%) virology and 26 (14.2%) clinical features. CONCLUSIONS: According to our review, China has provided a large number of research data for various research fields, during the outbreak of COVID-19. Most of the findings play an important role in preventing and controlling the epidemic around the world. With research on the COVID-19 still booming, new vaccine and effective medicine for COVID-19 will be expected to come out in the near future with the joint efforts of researchers worldwide.