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Since 2019n-CoV has swept the whole world, people's daily life is affected seriously and the public space system is facing to major challenges. Community public space should be re-evaluated and optimized as people change the way they use it. This research conducted a nationwide questionnaire survey in China, which collected the opinions of residents on community public space from the perspective of epidemic prevention and social needs to select research indicators. The questionnaire data were processed through the frequency analysis method, precedence chart and TOPSIS. We found: (1) under the background of the epidemic, people pay more attention to the satisfaction of leisure activities in community public space and the control of social spacing during activities; (2) the current assessment result of community public space risk of 2019-nCoV exposure is 0.386, which is relatively high; and (3) the exposure risk of the community can be effectively reduced by controlling for the two indicators of social distance and social facility sterilization. When the social distance is 1.8–3 m and the facility sterilization is once a day, the community public space minimizes exposure risk. In view of the above results, this paper selects the Wuhan start-up area of Wuhan, China, as an example for carrying out the optimization design of community public space based on the epidemic and the design the space optimization model for the two indicators of social distance and facility disinfection from both software and hardware aspects. [ABSTRACT FROM AUTHOR]

Coronavirus spread in Wuhan, China, in December 2019. A few weeks later, the virus was present in over 100 countries around the globe. Governments have adopted extreme measures to contain the spreading virus. Quarantine is considered the most effective way to control the spreading speed of COVID-19. In this study, a mathematical model is developed to explore the influence of quarantine and the latent period on the spatial spread of COVID-19. We use the mathematical model with quarantine, and delay to predict the spreading speed of the virus. In particular, we transform the model to a single integral equation and then apply the Laplace transform to find implicit equations for the spreading speeds. The basic reproduction number of COVID-19 is also found and calculated. Numerical simulations are performed to confirm our theoretical results. To validate the proposed model, we compare our outcomes with the actual reported data published by the National Health Commission of China and the Health Commission of local governments. The model demonstrates good qualitative agreement with the actual data reported. The results show that delay and quarantine highly influence the spreading speeds of COVID-19. Also, we can only contain the disease if we quarantine 75% of the infected people. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has resulted in an unprecedented amount of medical waste, presenting significant challenges for the safe disposal of hazardous waste. A systematic review of existing research on COVID-19 and medical waste can help address these challenges by providing insights and recommendations for effective management of the massive medical waste generated during the pandemic. This study utilized bibliometric and text mining methods to survey the scientific outcomes related to COVID-19 and medical waste, drawing on data from the Scopus database. The results show that the spatial distribution of medical waste research is unbalanced. Surprisingly, developing countries rather than developed countries lead research in this area. Especially, China, a major contributor to the field, has the highest number of publications and citations, and is also a centre of international cooperation. The main study authors and research institutions are also mainly from China. And the research on medical waste is a multidisciplinary field. Text mining analysis shows that COVID-19 and medical waste research is mainly organized around four themes: (i) medical waste from personal protective equipment; (ii) research on medical waste in Wuhan, China; (iii) threats of medical waste to the environment and (iv) disposal and management of medical waste. This would serve to better understand the current state of medical waste research and to provide some implications for future research. [ABSTRACT FROM AUTHOR]

Spinal cord injuries are incredibly disabling and can have fatal consequences. At present, there is a lack of available information regarding the epidemiological characteristics of patients who have experienced spinal cord injury (SCI) in China. This retrospective hospital-based study was conducted in the Rehabilitation department of Wuhan's Tongji Hospital between 2016 and 2022. A total of 649 individuals diagnosed with SCI (both traumatic and non-traumatic) were admitted during this period. Data regarding various epidemiological features were gathered, including sex, age, etiology, occupation, neurological level of injury, the American Spinal Injury Association Impairment Scale at the time of admission, and information on any accompanying injuries. Out of the 649 cases of SCI, there were 539 cases of traumatic SCI and 110 cases of non-traumatic SCI. The mean age at the time of injury was 45.6 ± 14.8 years. The ratio of male to female patients was higher in traumatic SCI at 2.82:1compared to non-traumatic SCI at 1.68:1. Traffic accidents were the most common cause of TSCI, accounting for (n = 207/539; 38.40%) of cases. On the other hand, neoplasm was the most common cause of NTSCI, accounting for (n = 38/110; 34.54%) of cases. The findings indicated a higher proportion of males, with traffic accidents being the main cause of injury among TSCI patients. It is crucial to prioritize the risk of falling among older adults and allocate more attention to this issue. These results emphasize the need for tailored preventive strategies that consider the unique characteristics of different types of SCI patients. [ABSTRACT FROM AUTHOR]

Better understanding of social media uses in crisis situations can help improve disaster management by policy-makers, organizations, businesses, and members of the public. It can also build theoretical understanding of how social life and citizenship incorporate social media usage. This study tracks the evolution of public sentiment in Wuhan, China, during the first 12 weeks after the identification of COVID-19 on the Chinese microblogging platform Sina Weibo. Data consist of 133,079 original Sina Weibo posts dealing with the novel coronavirus. The relative prevalence of eight different emotion groups is traced longitudinally using the ROST Content Mining System and the Emotion Vocabulary of Dalian University of Technology. The study finds a progression from confusion/fear, to disappointment/frustration, to depression/anxiety, then finally to happiness/gratitude. It argues that this progression indexes the changing affective energies of digital medical citizenship, which in turn indicates the context for intervention in future crises. [ABSTRACT FROM AUTHOR]