Systematic Mendelian randomization study of the effect of gut microbiome and plasma metabolome on severe COVID-19 (preprint)

Background COVID-19 could develop severe respiratory symptoms in certain infected patients, especially in the patients with immune disorders. Gut microbiome and plasma metabolome act important immunological modulators in the human body and could contribute to the immune responses impacting the progression of COVID-19.Methods Based on two-sample Mendelian randomization framework, the causal effects of 131 microbiota in genus or species level and 452 plasma metabolites on severe COVID-19 are estimated. Single nucleotide polymorphisms (SNPs) strongly associated with the abundance of intestinal bacteria in gut and the concentration of metabolites in plasma have been utilized as the instrument variables to infer whether they are causal factors of severe COVID-19. In addition, mediation analysis is conducted to find the potential link between the microbiota and metabolite which identified by polygenic Mendelian randomization analysis, while colocalization analysis has been performed to validate the causal relationships which identified by cis-Mendelian randomization analysis.Results Mendelian randomization support 13 microbiota and 53 metabolites, which are significantly causal association with severe COVID-19. Mediation analysis find 11 mediated relations, such as myo-inositol, 2-stearoylglycerophosphocholine and alpha-glutamyltyrosine, which appeared to mediate the association of Howardella and Ruminiclostridium 6 with severe COVID-19 respectively, while Butyrivibrio and Ruminococcus gnavus appeared to mediate the association of myo-inositol and N-acetylalanine respectively. Ruminococcus torques abundance was colocalized with severe COVID-19 (PP.H4 = 0.77) and the colon expression of permeability related protein RASIP1 (PP.H4 = 0.95).Conclusions Our study results highlight the causal relationships of gut microbiome and plasma metabolome for severe COVID-19, which have the promise to be served as clinical biomarkers for risk stratification and prognostication, and novel basis to unravel the pathophysiological mechanisms of severe COVID-19.

Multi-verse Optimizer with Rosenbrock and Diffusion Mechanisms for Multilevel Threshold Image Segmentation from COVID-19 Chest X-Ray Images.

Coronavirus Disease 2019 (COVID-19) is the most severe epidemic that is prevalent all over the world. How quickly and accurately identifying COVID-19 is of great significance to controlling the spread speed of the epidemic. Moreover, it is essential to accurately and rapidly identify COVID-19 lesions by analyzing Chest X-ray images. As we all know, image segmentation is a critical stage in image processing and analysis. To achieve better image segmentation results, this paper proposes to improve the multi-verse optimizer algorithm using the Rosenbrock method and diffusion mechanism named RDMVO. Then utilizes RDMVO to calculate the maximum Kapur's entropy for multilevel threshold image segmentation. This image segmentation scheme is called RDMVO-MIS. We ran two sets of experiments to test the performance of RDMVO and RDMVO-MIS. First, RDMVO was compared with other excellent peers on IEEE CEC2017 to test the performance of RDMVO on benchmark functions. Second, the image segmentation experiment was carried out using RDMVO-MIS, and some meta-heuristic algorithms were selected as comparisons. The test image dataset includes Berkeley images and COVID-19 Chest X-ray images. The experimental results verify that RDMVO is highly competitive in benchmark functions and image segmentation experiments compared with other meta-heuristic algorithms.

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-verse Optimizer with Rosenbrock and Diffusion Mechanisms for Multilevel Threshold Image Segmentation from COVID-19 Chest X-Ray Images

Coronavirus Disease 2019 (COVID-19) is the most severe epidemic that is prevalent all over the world. How quickly and accurately identifying COVID-19 is of great significance to controlling the spread speed of the epidemic. Moreover, it is essential to accurately and rapidly identify COVID-19 lesions by analyzing Chest X-ray images. As we all know, image segmentation is a critical stage in image processing and analysis. To achieve better image segmentation results, this paper proposes to improve the multi-verse optimizer algorithm using the Rosenbrock method and diffusion mechanism named RDMVO. Then utilizes RDMVO to calculate the maximum Kapur's entropy for multilevel threshold image segmentation. This image segmentation scheme is called RDMVO-MIS. We ran two sets of experiments to test the performance of RDMVO and RDMVO-MIS. First, RDMVO was compared with other excellent peers on IEEE CEC2017 to test the performance of RDMVO on benchmark functions. Second, the image segmentation experiment was carried out using RDMVO-MIS, and some meta-heuristic algorithms were selected as comparisons. The test image dataset includes Berkeley images and COVID-19 Chest X-ray images. The experimental results verify that RDMVO is highly competitive in benchmark functions and image segmentation experiments compared with other meta-heuristic algorithms.

Entrepreneurial Intention and Delayed Job Satisfaction From the Perspective of Emotional Interaction: The Mediating of Psychological Capital.

The coronavirus disease 2019 (COVID-19) pandemic has exacerbated the labour shortage, and promoting entrepreneurship to spur job creation is one of the most effective strategies to address this problem. Entrepreneurs must lengthen their employment or start-up cycles due to COVID-19 normalisation. Consequently, the impact of career willingness to delay satisfaction on entrepreneurial ambition is investigated in this research via an online survey in Jiangsu Province, China. The findings show that students with a high level of career delayed contentment has a higher level of entrepreneurial intention (EI), implying that career delayed contentment intention influences EI positively. Psychological capital (PC) modifies this process, increasing the influence of job delayed satisfaction on EI by strengthening PC. PC's significant components are self-efficacy, hope, optimism, and flexibility. This study combines the willingness to wait for satisfaction with the willingness to start a business, providing a valuable reference for reducing the work condition caused by the COVID-19 epidemic.

Haze caused by NOx oxidation under restricted residential and industrial activities in a mega city in the south of North China Plain.

The formation of secondary aerosol species, including nitrate and sulfate, induces severe haze in the North China Plain. However, despite substantial reductions in anthropogenic pollutants due to severe restriction of residential and industrial activities in 2020 to stop the spread of COVID-19, haze still formed in Zhengzhou. We compared ionic compositions of PM2.5 during the period of the restriction with that immediately before the restriction and in the comparison period in 2019 to investigate the processes that caused the haze. The average concentration of PM2.5 was 83.9 µg m-3 in the restriction period, 241.8 µg m-3 before the restriction, and 94.0 µg m-3 in 2019. Nitrate was the largest contributor to the PM2.5 in all periods, with an average mass fraction of 24%-30%. The average molar concentration of total nitrogen compounds (NOx + nitrate) was 0.89 µmol m-3 in the restriction period, which was much lower than that in the non-restriction periods (1.85-2.74 µmol m-3). In contrast, the concentration of sulfur compounds (SO2 + sulfate) was 0.34-0.39 µmol m-3 in all periods. The conversion rate of NOx to nitrate (NOR) was 0.35 in the restriction period, significantly higher than that before the restriction (0.26) and in 2019 (0.25). NOR was higher with relative humidity in 40-80% in the restriction period than in the other two periods, whereas the conversion rate of SO2 to sulfate did not, indicating nitrate formation was more efficient during the restriction. When O3 occupied more than half of the oxidants (Ox = O3 + NO2), NOR increased rapidly with the ratio of O3 to Ox and was much higher in the daytime than nighttime. Therefore, haze in the restriction period was caused by increased NOx-to-nitrate conversion driven by photochemical reactions.

The Use of Remote Programming for Spinal Cord Stimulation for Patients With Chronic Pain During the COVID-19 Outbreak in China.

OBJECTIVES: Due to the impact of COVID-19 epidemic, face-to-face follow-up treatments for patients with chronic pain and implanted spinal cord stimulation (SCS) devices are forced to be delayed or stopped. This has led to more follow ups being done remotely. Meanwhile, with the development of 4G/5G networks, smartphones, and novel devices, remote programming has become possible. Here, we investigated the demand and utility of remote follow-ups including remote programming for SCS for patients with chronic pain. MATERIALS AND METHODS: A questionnaire including questions on demographic characteristics, pain history, postimplantation life quality, standard follow-up experience, remote follow-up, and remote programming experience was sent to patients diagnosed as chronic intractable pain and treated with SCS during January 2019 to January 2020. RESULTS: A total of 64 participants completed the questionnaire. About 70% of participants expressed demands for remote follow-ups due to the inconvenience, high costs, and time consumption of traditional follow-up visits. Nearly 97% of participants have attempted remote follow-ups, and about 81% of participants have further tried remote programming. Approximately, 96% of them recognized the benefits. CONCLUSIONS: The remote programming was in high demand among participants. Most of the participants have tried remote follow-ups or even remote programming. The remote programming appeared to be more efficient, economic and were widely recognized among participants.

Social media exposure during COVID-19 lockdowns could lead to emotional overeating via anxiety: The moderating role of neuroticism.

China was a major hotspot during the beginning of the COVID-19 pandemic. Several studies have reported changes in residents' eating behaviors and appetite during city wide lockdowns and home confinements. However, few have investigated how neuroticism interacts with the impact of COVID-19 to influence eating behaviors during city lockdowns. Thus, the current study aims to establish a pathway model to understand social media exposure, negative affect, neuroticism, and their interaction with eating behaviors during the COVID-19 lockdowns. We present data from 1,128 participants (Mage = 24.34 ± 10.48 years) who completed an online survey between February 17 and 27, 2020. The extent of respondents' social media exposure, negative affect, eating behaviors, and desire for high-calorie food during city lockdowns, as well as the personality trait of neuroticism, were measured. Results show that city lockdowns and home confinements had a negative impact on residents' eating behaviors and appetite. Forty-eight percent of respondents showed moderate to constant emotional overeating, and respondents' desire for high-calorie food significantly increased. Correlation analysis showed that emotional overeating is positively associated with social media exposure, neuroticism, and anxiety. Then, a moderated mediation model was established, showing that heavy social media exposure could lead to emotional overeating through anxiety, and the association between social media exposure and anxiety varies depending on the extent of neuroticism. The current study provides novel insight into how the interaction of a personality trait and the stressful situation of COVID-19 influence people's negative emotions and eating behaviors.

Diverse clinical processes of 16 COVID-19 cases who concentrated infection in the same workplace in Beijing, China: An observational study.

ABSTRACT: Since December 2019, an outbreak of COVID-19 sweeping the world. Understanding the clinical and SARS-CoV-2 dynamic changes of mild and ordinary patients of COVID-19, so as to provide basis for the prevention and control of COVID-19.On February 1st, 2020, 16 SARS-CoV-2 RNA positive patients diagnosed in the same site in Beijing. The patients symptoms, signs, medication, and SARS-CoV-2 results were recorded.Of the 16 patients, 12 were female. Although they were infected at the same time in the same workplace, their clinical processes were very different and can be roughly divided into three different types: persistent sputum positive, persistent stool positive and persistent both positive. In 7 patients with mild clinical manifestations, the median days of SARS-CoV-2 RNA negative conversion in sputum samples were significantly later than those with obvious lung injury (27 days [range: 18 to 36]; 17 days, [range 6 to 25], P = .021). The negative conversion of SARS-CoV-2 RNA in stool was significant later than in sputum.There were various clinical manifestations after SARS-CoV-2 infection, even if they were infected by the same source of infection in the same place. The presence of SARS-CoV-2 virus RNA in stool samples was longer than that in respiratory tract.

Analysis of food safety supervision and sampling inspection in Chongqing during prevention and control of COVID-19 pandemic

Objective: To analyse the food safety supervision and sampling inspection in Chongqing during the period of prevention and control of COVID-19.

Reflections on treatment of COVID-19 with traditional Chinese medicine.

Coronavirus disease 2019 (COVID-19) pandemic is spreading rapidly around the globe. By the establishment of an integrative system combining both traditional Chinese medicine (TCM) and western medicine, China has achieved good clinical efficacy in the prevention and control of the pandemic. The advantages of TCM in the treatment of COVID-19 include effective relief of symptoms, retarding the development from mild and moderate to severe, improvement of cure rate, reducing death rates, and promotion of rehabilitation. Besides, according to the different severity levels of individual cases, the National Health Commission of the People's Republic of China issued treatment guidelines that provide corresponding prescriptions for patients. From the perspective of TCM, this review aims to analyze the role of a variety of TCM prescriptions in the treatment of COVID-19, focusing on the analysis of the "Three TCM prescriptions and three medicines" recommended by the Chinese authorities during the pandemic. We expect that this review will provide insights into the prevention and treatment of COVID-19 with TCM.

Disease burden and clinical severity of the first pandemic wave of COVID-19 in Wuhan, China (preprint)

The pandemic of novel coronavirus disease 2019 (COVID-19) began in Wuhan, China, where a first wave of intense community transmission was cut short by interventions. Using multiple data source, we estimated the disease burden and clinical severity of COVID-19 by age in Wuhan from December 1, 2019 to March 31, 2020. We adjusted estimates for sensitivity of laboratory assays and accounted for prospective community screenings and healthcare seeking behaviors. Rates of symptomatic cases, medical consultations, hospitalizations and deaths were estimated at 796 (95%CI: 703-977), 489 (472-509), 370 (358-384), and 36.2 (35.0-37.3) per 100,000 persons, respectively. The COVID-19 outbreak in Wuhan had higher burden than the 2009 influenza pandemic or seasonal influenza, and that clinical severity was similar to that of the 1918 influenza pandemic. Our comparison puts the COVID-19 pandemic into context and could be helpful to guide intervention strategies and preparedness for the potential resurgence of COVID-19.

Infectivity, susceptibility, and risk factors associated with SARS-CoV-2 transmission under intensive contact tracing in Hunan, China (preprint)

BackgroundSeveral parameters driving the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain unclear, including age-specific differences in infectivity and susceptibility, and the contribution of inapparent infections to transmission. Robust estimates of key time-to-event distributions remain scarce as well. MethodsWe collected individual records for 1,178 SARS-CoV-2 infected individuals and their 15,648 contacts identified by contact tracing and monitoring over the period from January 13 to April 02, 2020 in Hunan Province, China. We provide descriptive statistics of the characteristics of cases and their close contacts; we fitted distributions to time-to-key-events distributions and infectiousness profile over time; and we used generalized linear mixed model to estimate risk factors for susceptibility and transmissibility of SARS-CoV-2. ResultsWe estimated the mean serial interval at 5.5 days (95%CI -5.0, 19.9) and the mean generation time at 5.5 days (95%CI 1.7, 11.6). The infectiousness was estimated to peak 1.8 days before symptom onset, with 95% of transmission events occurring between 7.6 days before and 7.3 days after the date of symptom onset. The proportion of pre-symptomatic transmission was estimated to be 62.5%. We estimated that at least 3.5% of cases were generated asymptomatic individuals. SARS-CoV-2 transmissibility was not significantly different between working-age adults (15-59 years old) and other age groups (0-14 years old: p-value=0.16; 60 years and over: p-value=0.33), whilst susceptibility to SARS-CoV-2 infection was estimated to increase with age (p-value=0.03). In addition, transmission risk was higher for household contacts (p-value<0.001), decreased for higher generations within a cluster (second generation: odds ratio=0.13, p-value<0.001; generations 3-4: odds ratio=0.05, p-value<0.001, relative to generation 1), and decreased for infectors with a larger number of contacts (p-value=0.04). InterpretationOur findings warn of the possible relevant contribution of children to SARS-CoV-2 transmission. When lockdown interventions are in place, we found that odds of transmission are highest in the household setting but, with the relaxation of interventions, other settings (including schools) could bear a higher risk of transmission. Moreover, the estimated relevant fraction of pre-symptomatic and asymptomatic transmission highlight the importance of large-scale testing, contact tracing activities, and the use of personnel protective equipment during the COVID-19 pandemic.

Experiences of front-line nurses combating coronavirus disease-2019 in China: A qualitative analysis.

OBJECTIVE: To explore the experiences of front-line nurses combating the coronavirus disease-2019 epidemic. DESIGN AND SAMPLE: Fifteen front-line nurses caring for COVID-19 patients were recruited from two hospitals in Wuhan, China from January 26 to February 5, 2020. Data were collected through semi-structured individual interviews and analyzed using standard qualitative methods. RESULTS: Four theme categories emerged from the data analysis: (a) "Facing tremendous new challenges and danger"; (b) "Strong pressure because of fear of infection, exhaustion by heavy workloads and stress of nursing seriously ill COVID-19 patients"; (c) "Strong sense of duty and identity as a healthcare provider"; (d) "Rational understanding of the epidemic-the nurses believed that the epidemic would soon be overcome and would like to receive disaster rescue training." CONCLUSIONS: Although the intensive rescue work drained front-line nurses, both physically and emotionally, they showed a spirit of dedication and felt a responsibility to overcome this epidemic. Their experiences provide useful insights into implementing a safer public health emergency rescue system in preparation for future outbreaks of infectious diseases. Specifically, psychological support and humanistic care should be provided to front-line nurses to maintain their well-being, and nationwide emergency rescue training and disaster education should be implemented.

Advances and challenges in the prevention and treatment of COVID-19.

Since the end of 2019, a new type of coronavirus pneumonia (COVID-19) caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has been spreading rapidly throughout the world. Previously, there were two outbreaks of severe coronavirus caused by different coronaviruses worldwide, namely Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and the Middle East Respiratory Syndrome Coronavirus (MERS-CoV). This article introduced the origin, virological characteristics and epidemiological overview of SARS-CoV-2, reviewed the currently known drugs that may prevent and treat coronavirus, explained the characteristics of the new coronavirus and provided novel information for the prevention and treatment of COVID-19.

Surgical treatment of thoracolumbar fracture with incomplete lower limb paralysis in a patient with COVID-19.

Since December 2019, COVID-19, an acute infectious disease, has gradually become a global threat. We report a case of thoracolumbar fractures (T12 and L1) and incomplete lower limb paralysis in a patient with COVID-19. After a series of conservative treatment which did not work at all, posterior open reduction and pedicle screw internal fixation of the thoracolumbar fracture were performed in Wuhan Union Hospital. Three weeks later, the patient could stand up and the pneumonia is almost cured. We successfully performed a surgery in a COVID-19 patient, and to our knowledge it is the first operation for a COVID-19 patient ever reported.

Better Strategies for Containing COVID-19 Epidemics --- A Study of 25 Countries via an Extended Varying Coefficient SEIR Model (preprint)

We evaluate the effectiveness of COVID-19 control strategies of 25 countries which have endured more than four weeks of community infections. With an extended SEIR model that allows infections in both the exposed and infected states, the key epidemic parameters are estimated from each country's data, which facilitate the evaluation and cross-country comparison. It is found quicker control measures significantly reduce the average reproduction numbers and shorten the time length to infection peaks. If the swift control measures of Korea and China were implemented, average reductions of 88% in the confirmed cases and 80% in deaths would had been attained for the other 23 countries from start to April 10. Effects of earlier or delayed interventions in the US and the UK are experimented which show at least 75% (29%) less infections and deaths can be attained for the US (the UK) under a Five-Day Earlier experiment. The impacts of two removal regimes (Korea and Italy) on the total infection and death tolls on the other countries are compared with the naturally forecast ones, which suggest there are still ample opportunity for countries to reduce the final death numbers by improving the removal process.

Case fatality risk of novel coronavirus diseases 2019 in China (preprint)

Objective The outbreak of novel coronavirus disease 2019 (COVID-19) imposed a substantial health burden in mainland China and remains a global epidemic threat. Our objectives are to assess the case fatality risk (CFR) among COVID-19 patients detected in mainland China, stratified by clinical category and age group. Method We collected individual information on laboratory-confirmed COVID-19 cases from publicly available official sources from December 29, 2019 to February 23, 2020. We explored the risk factors associated with mortality. We used methods accounting for right-censoring and survival analyses to estimate the CFR among detected cases. Results Of 12,863 cases reported outside Hubei, we obtained individual records for 9,651 cases, including 62 deaths and 1,449 discharged cases. The deceased were significantly older than discharged cases (median age: 77 vs 39 years, p<0.001). 58% (36/62) were male. Older age (OR 1.18 per year; 95%CI: 1.14 to 1.22), being male (OR 2.02; 95%CI: 1.02 to 4.03), and being treated in less developed economic regions (e.g., West and Northeast vs. East, OR 3.93; 95%CI: 1.74 to 8.85) were mortality risk factors. The estimated CFR was 0.89-1.24% among all cases. The fatality risk among critical patients was 2-fold higher than that among severe and critical patients, and 24-fold higher than that among moderate, severe and critical patients. Conclusions Our estimates of CFR based on laboratory-confirmed cases ascertained outside of Hubei suggest that COVID-19 is not as severe as severe acute respiratory syndrome and Middle East respiratory syndrome, but more similar to the mortality risk of 2009 H1N1 influenza pandemic in hospitalized patients. The fatality risk of COVID-19 is higher in males and increases with age. Our study improves the severity assessment of the ongoing epidemic and can inform the COVID-19 outbreak response in China and beyond.

Tracking and Predicting COVID-19 Epidemic in China Mainland (preprint)

By proposing a varying coefficient Susceptible-Infected-Removal model (vSIR), we track the epidemic of COVID-19 in 30 provinces in China and 15 cities in Hubei province, the epicenter of the outbreak. It is found that the spread of COVID-19 has been significantly slowing down within the two weeks from January 27 to February 10th with 87.0% and 84.3% reductions in the reproduction number R0 among the 30 provinces and 15 Hubei cities, respectively. This suggests the extreme control measures implemented since January 23, which include cutting off Wuhan and many other cities and towns, a great public awareness and high level of self isolation at home, have contributed to a substantial decline in the reproductivity of the COVID-19 in China. We predict that Hubei province will reach its peak between February 20 and 22, 2020, and if the removal rate can be increased to 0.1, the epidemic outside Hubei province will end in May 2020, and inside Hubei in early June.