Less Social Support for Patients With COVID-19: Comparison With the Experience of Nurses.

Context: Since December 2019, more than 80,000 patients have been diagnosed with coronavirus disease 2019 (COVID-19) in China. Social support status of COVID-19 patients, especially the impact of social support on their psychological status and quality of life, needs to be addressed with increasing concern. Objectives: In this study, we used social support rating scale (SSRS) to investigate the social support in COVID-19 patients and nurses. Methods: The present study included 186 COVID-19 patients at a Wuhan mobile cabin hospital and 234 nurses at a Wuhan COVID-19 control center. Responses to a mobile phone app-based questionnaire about social support, anxiety, depression, and quality of life were recorded and evaluated. Results: COVID-19 patients scored significantly lower than nurses did on the Social Support Rating Scale (SSRS). Among these patients, 33.9% had anxiety symptoms, while 23.7% had depression symptoms. Overall SSRS, subjective social support scores and objective support scores of patients with anxiety were lower than those of patients without anxiety. This result was also found in depression. In addition, all dimensions of social support were positively correlated with quality of life. Interestingly, in all dimensions of social support, subjective support was found to be an independent predictive factor for anxiety, depression, and quality of life, whereas objective support was a predictive factor for quality of life, but not for anxiety and depression via regression analysis. Conclusion: Medical staffs should pay attention to the subjective feelings of patients and make COVID-19 patients feel respected, supported, and understood from the perspective of subjective support, which may greatly benefit patients, alleviate their anxiety and depression, and improve their quality of life.

The impact of invisible-spreaders on COVID-19 transmission and work resumption.

The global impact of coronavirus disease 2019 (COVID-19) is unprecedented, and many control and prevention measures have been implemented to test for and trace COVID-19. However, invisible-spreaders, who are associated with nucleic acid detection and asymptomatic infections, have received insufficient attention in the current COVID-19 control efforts. In this paper, we analyze the time series infection data for Italy, Germany, Brazil, India and Sweden since the first wave outbreak to address the following issues through a series of experiments. We conclude that: 1) As of June 1, 2020, the proportion of invisible-spreaders is close to 0.4% in Sweden, 0.8% in early Italy and Germany, and 0.4% in the middle and late stages. However, in Brazil and India, the proportion still shows a gradual upward trend; 2) During the spread of this pandemic, even a slight increase in the proportion of invisible-spreaders could have large implications for the health of the community; and 3) On resuming work, the pandemic intervention measures will be relaxed, and invisible-spreaders will cause a new round of outbreaks.

Role of cytokine storm in coronavirus infections: culprit or accomplice?

At present, there are seven known types of human coronaviruses (HCoVs), which can be further divided into two categories: low pathogenic and highly pathogenic. The low pathogenic HCoVs infect the upper respiratory tract, mainly causing mild, cold-like respiratory diseases. By contrast, highly pathogenic HCoVs mainly infect the lower respiratory tract and cause fatal types of pneumonia, which include severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), as well as the recent outbreak of coronavirus disease 2019 (COVID-19). Highly pathogenic HCoV infection has a high morbidity and mortality, which is usually related to the strong immune response induced by highly proinflammatory cytokines, which is also known as "cytokine storm". Therefore, it is particularly important to explore the role of cytokine storm in the process of highly pathogenic HCoV infection. We review the epidemiological and clinical manifestations of highly pathogenic HCoV infection, and reveal the pathology of cytokine storm and its role in the process of highly pathogenic HCoV infection.

Can Digital Transformation Promote the Rapid Recovery of Cities from the COVID-19 Epidemic? An Empirical Analysis from Chinese Cities.

BACKGROUND: Digital transformation has become a key intervention strategy for the global response to the COVID-19 epidemic, and digital technology is helping cities recover from the COVID-19 epidemic. However, the effects of urban digital transformation on the recovery from the COVID-19 epidemic still lack mechanism analyses and empirical testing. This study aimed to explain the theoretical mechanism of urban digital transformation on the recovery from the COVID-19 epidemic and to test its effectiveness using an empirical analysis. METHODS: This study, using a theoretical and literature-based analysis, summarizes the impact mechanisms of urban digital transformation on the recovery of cities from the COVID-19 epidemic. A total of 83 large- and medium-sized cities from China are included in the empirical research sample, covering most major cities in China. The ordinary least squares (OLS) method is adopted to estimate the effect of China's urban digitalization level on population attraction in the second quarter of 2020. RESULTS: The theoretical analysis found that urban digital transformation improves the ability of cities to recover from the COVID-19 epidemic by promoting social communication, collaborative governance, and resilience. The main findings of the empirical analysis show that the digital level of a city has a significant positive effect on urban population attraction (p < 0.001). CONCLUSIONS: A positive relationship was found between urban digital transformation and the rapid recovery of cities from the COVID-19 epidemic. Digital inventions for social communication, collaborative governance, and urban resilience are an effective way of fighting the COVID-19 emergency.

Nervous system involvement after infection with COVID-19 and other coronaviruses.

Viral infections have detrimental impacts on neurological functions, and even to cause severe neurological damage. Very recently, coronaviruses (CoV), especially severe acute respiratory syndrome CoV 2 (SARS-CoV-2), exhibit neurotropic properties and may also cause neurological diseases. It is reported that CoV can be found in the brain or cerebrospinal fluid. The pathobiology of these neuroinvasive viruses is still incompletely known, and it is therefore important to explore the impact of CoV infections on the nervous system. Here, we review the research into neurological complications in CoV infections and the possible mechanisms of damage to the nervous system.

Predicting COVID-19 epidemiological trend by applying population mobility data in two-stage modeling.

:To predict the epidemiological trend of coronavirus disease 2019 (COVID-19) by mathematical modeling based on the population mobility and the epidemic prevention and control measures. : As of February 8，2020，the information of 151 confirmed cases in Yueqing，Zhejiang province were obtained，including patients' infection process，population mobility between Yueqing and Wuhan，etc. To simulate and predict the development trend of COVID-19 in Yueqing, the study established two-stage mathematical models，integrating the population mobility data with the date of symptom appearance of confirmed cases and the transmission dynamics of imported and local cases. : It was found that in the early stage of the pandemic，the number of daily imported cases from Wuhan (using the date of symptom appearance) was positively associated with the number of population travelling from Wuhan to Yueqing on the same day and 6 and 9 days before that. The study predicted that the final outbreak size in Yueqing would be 170 according to the number of imported cases estimated by consulting the population number travelling from Wuhan to Yueqing and the susceptible-exposed-infectious-recovered (SEIR) model; while the number would be 165 if using the reported daily number of imported cases. These estimates were close to the 170，the actual monitoring number of cases in Yueqing as of April 27，2020. : The two-stage modeling approach used in this study can accurately predict COVID-19 epidemiological trend.

Impact of socioeconomic status，population mobility and control measures on COVID-10 development in major cities of China.

:To evaluate the impact of socioeconomic status，population mobility，prevention and control measures on the early-stage coronavirus disease 2019 (COVID-19) development in major cities of China. : The rate of daily new confirmed COVID-19 cases in the 51 cities with the largest number of cumulative confirmed cases as of February 19，2020 (except those in Hubei province) were collected and analyzed using the time series cluster analysis. It was then assessed according to three aspects，that is, socioeconomic status，population mobility，and control measures for the pandemic. : According to the analysis on the 51 cities，4 development patterns of COVID-19 were obtained，including a high-incidence pattern (in Xinyu)，a late high-incidence pattern (in Ganzi)，a moderate incidence pattern (in Wenzhou and other 12 cities)，and a low and stable incidence pattern (in Hangzhou and other 35 cities). Cities with different types and within the same type both had different scores on the three aspects. : There were relatively large difference on the COVID-19 development among different cities in China，possibly affected by socioeconomic status，population mobility and prevention and control measures that were taken. Therefore，a timely public health emergency response and travel restriction measures inside the city can interfere the development of the pandemic. Population flow from high risk area can largely affect the number of cumulative confirmed cases.

Impact of Wuhan lockdown on the spread of COVID-19 in China: a study based on the data of population mobility.

This study aimed to quantitatively assess the effectiveness of the Wuhan lockdown measure on controlling the spread of coronavirus diesase 2019 (COVID-19). : Firstly，estimate the daily new infection rate in Wuhan before January 23，2020 when the city went into lockdown by consulting the data of Wuhan population mobility and the number of cases imported from Wuhan in 217 cities of Mainland China. Then estimate what the daily new infection rate would have been in Wuhan from January 24 to January 30th if the lockdown measure had been delayed for 7 days，assuming that the daily new infection in Wuhan after January 23 increased in a high，moderate and low trend respectively (using exponential, linear and logarithm growth models). Based on that，calculate the number of infection cases imported from Wuhan during this period. Finally，predict the possible impact of 7-day delayed lockdown in Wuhan on the epidemic situation in China using the susceptible-exposed-infectious-removed (SEIR) model. : The daily new infection rate in Wuhan was estimated to be 0.021%，0.026%，0.029%，0.033% and 0.070% respectively from January 19 to January 23. And there were at least 20 066 infection cases in Wuhan by January 23，2020. If Wuhan lockdown measure had been delayed for 7 days，the daily new infection rate on January 30 would have been 0.335% in the exponential growth model，0.129% in the linear growth model，and 0.070% in the logarithm growth model. Correspondingly，there would have been 32 075，24 819 and 20 334 infection cases travelling from Wuhan to other areas of Mainland China，and the number of cumulative confirmed cases as of March 19 in Mainland China would have been 3.3-3.9 times of the officially reported number. Conclusions: Timely taking city-level lockdown measure in Wuhan in the early stage of COVID-19 outbreak is essential in containing the spread of the disease in China.

Demographic and social correlates and indicators for behavioural compliance with personal protection among Chinese community-dwellers during COVID-19: a cross-sectional study.

OBJECTIVES: Examine compliance with personal protective measures in communities for the prevention and control of local transmission of the COVID-19, and explore indicators for such behavioural compliance. DESIGN: Cross-sectional design with a self-selecting sample. Data collected in February 2020. SETTING: Community dwellers in China. PARTICIPANTS: 2956 participants aged 16 and above completed the study and were included in the analysis. OUTCOME MEASURES: Nationwide COVID-19 survey. Demographics and self-reported compliance with four personal protective measures-home quarantine, mask-wearing, temperature-taking and hand-sanitising were collected. Outbreak severity and timeliness of personal protection order were obtained from the China Center for Disease Control and Prevention website. Logistic regression models were employed to examine the association between demographic and social indicators and behavioural compliance. RESULTS: Compliance with home quarantine was only associated with gender (men, OR=0.61 (0.51-0.73), inverse association) but no other indicators. In contrast, men had higher compliance with mask-wearing (OR=1.79 (1.49-2.16)) and temperature-taking (OR=1.27 (1.05-1.53)). Compared with younger adults (≤20 years), the middle-age groups (31-40 and 41-50 years of age) were more compliant with all protective behaviours, except for home quarantine (OR=0.71 (0.54-0.93) and 0.67 (0.46-0.97), respectively). CONCLUSION: Male gender was associated with lower compliance with home quarantine yet higher compliance with mask-wearing and temperature-taking. The middle-age participants (31-50 years) had lower compliance with home quarantine but higher with other measures. These findings may be supported by the economic considerations and the long-inherited Confucian values among Chinese. In light of the ongoing COVID-19 pandemic, public health authorities should tailor policy implementation to disparities in psychosocial indicators.

Role of angiotensin-converting enzyme 2 in neurodegenerative diseases during the COVID-19 pandemic.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) uses the angiotensin-converting enzyme 2 (ACE2) receptor for infecting and spreading in humans. Studies have shown that the widespread expression of ACE2 in human tissues may be associated with organ function damage (e.g., lung, kidney, and stomach) in patients with coronavirus disease 2019 (COVID-19). However, in neurodegenerative diseases, whose pathogenesis is closely related to advanced age, ACE2 plays a neurotrophic and protective role by activating the ACE2/Ang-(1-7)/Mas axis, thus inhibiting cognitive impairment. Early reports have revealed that the elderly are more susceptible to COVID-19 and that elderly patients with COVID-19 have faster disease progression and higher mortality. Therefore, during the COVID-19 pandemic, it is crucial to understand the role of ACE2 in neurodegenerative diseases. In this paper, we review the relationship between COVID-19, neurodegenerative diseases, and ACE2, as well as provide recommendations for the protection of elderly patients with neurodegenerative diseases during the COVID-19 pandemic.

Vicarious traumatization in the general public, members, and non-members of medical teams aiding in COVID-19 control.

Since December 2019, more than 79,000 people have been diagnosed with infection of the Corona Virus Disease 2019 (COVID-19). A large number of medical staff was sent to Wuhan city and Hubei province to aid COVID-19 control. Psychological stress, especially vicarious traumatization caused by the COVID-19 pandemic, should not be ignored. To address this concern, the study employed a total of 214 general public and 526 nurses (i.e., 234 front-line nurses and 292 non-front-line nurses) to evaluate vicarious traumatization scores via a mobile app-based questionnaire. Front-line nurses are engaged in the process of providing care for patients with COVID-19. The results showed that the vicarious traumatization scores for front-line nurses including scores for physiological and psychological responses, were significantly lower than those of non-front-line nurses (P < 0.001). Interestingly, the vicarious traumatization scores of the general public were significantly higher than those of the front-line nurses (P < 0.001); however, no statistical difference was observed compared to the scores of non-front-line nurses (P > 0.05). Therefore, increased attention should be paid to the psychological problems of the medical staff, especially non-front-line nurses, and general public under the situation of the spread and control of COVID-19. Early strategies that aim to prevent and treat vicarious traumatization in medical staff and general public are extremely necessary.