Analysis of Prognostic Factors and Establishment of a Nomogram to Predict Risk for COVID-19 Convalescent Patients Based on Metabolomic and Lipidomic (preprint)

Ethnopharmacological relevance: Qimai Feiluoping Mixture (QM) is a traditional Chinese herbal formulation that has demonstrated efficacy in improving both clinical symptoms and radiological indications of pulmonary fibrosis in patients convalescing from Coronavirus Disease 2019 (COVID-19).Aim of the study: To analyze factors associated with the prognosis of COVID-19 patients. It seeks to develop and validate a nomogram based on metabolomic and lipidomic for predicting improvements in lung imaging in COVID-19 patients. Additionally, the study evaluates the clinical application value of this nomogram.Methods and materials: A retrospective analysis was conducted on the clinical data of COVID-19 recovery patients from January 2020 to April 2022. Non-targeted metabolomic and lipidomic plasma analysis of the patients were performed using LC-MS and normal phase (NP)-HPLC coupled with mass spectrometry. Patients were divided into training and validation sets in a 7:3 ratio based on their omics data. Multivariate logistic regression analysis was conducted to identify independent risk factors associated with the recovery of lung imaging. Based on these factors, a nomogram prediction model was developed. The efficacy of the model was evaluated using receiver operating characteristic (ROC) curves and calibration curves. In addition, decision curve analysis (DCA) was performed to assess the performance of the predictive model in clinical applications.Results The use of QM was found to be associated with the recovery of lung imaging in COVID-19 patients (P < 0.05). Among the 75 metabolites detected in the metabolomic test and 32 lipids identified in the lipidomic test, Pro Ser Ser Val, PC36:1(18:0_18:1), and BMP36:3(18:2_18:1) were utilized for constructing the predictive model. The model demonstrated good discriminative ability, with an Area Under the Curve (AUC) of 0.821 (95% CI: 0.718–0.924) in the training set and 0.808 (95% CI: 0.627–0.989) in the validation set. The calibration curves indicated good agreement between predicted probabilities and actual probabilities in both the training and validation sets. Finally, the DCA curve suggested that the model has good clinical utility.Conclusion The utilization of QM may beneficially influence the recovery of lung imaging in patients with COVID-19. A straightforward nomogram, developed based on metabolomic and lipidomic, could be a valuable tool for clinicians to predict the likelihood of lung imaging recovery in COVID-19 patients.

Why people failed to adhere to COVID-19 preventive behaviors? Perspectives from an integrated behavior change model

According to the integrated model,5 individuals who are driven by controlled motivation (ie, acting due to external contingencies, internal pressure, or sense of ego) may adhere to the advisory behavior as soon as the external factors (eg, contingencies of following COVID-19 preventive behaviors or not) are present, but they are more vulnerable to nonadherence in the long term than those who hold autonomous motivation (ie, acting for inherent interest, satisfaction, personal goals, and values) for the action. In support to the psychological factors in the integrated model5, there are social situations or personal beliefs that facilitate autonomous motivation (eg, “preventing COVID-19 is what I want to do because I am responsible for my own health”), attitude (eg, accessible online information about the values of COVID-19 prevention), subjective norms (eg, family or friends who are following the COVID-19 preventive strategies say I should do the same), and perceived behavioral control (eg, training resources that make it easier for me to correctly apply COVID-19 preventive behavior such as hand hygiene). [...]the integrated model of self-determination theory and the theory of planned behavior explains why some individuals fail to adhere to the preventive behaviors of COVID-19.

Multiple-Inputs Convolutional Neural Network for COVID-19 Classification and Critical Region Screening From Chest X-ray Radiographs: Model Development and Performance Evaluation

Background The COVID-19 pandemic is becoming one of the largest, unprecedented health crises, and chest X-ray radiography (CXR) plays a vital role in diagnosing COVID-19. However, extracting and finding useful image features from CXRs demand a heavy workload for radiologists. Objective The aim of this study was to design a novel multiple-inputs (MI) convolutional neural network (CNN) for the classification of COVID-19 and extraction of critical regions from CXRs. We also investigated the effect of the number of inputs on the performance of our new MI-CNN model. Methods A total of 6205 CXR images (including 3021 COVID-19 CXRs and 3184 normal CXRs) were used to test our MI-CNN models. CXRs could be evenly segmented into different numbers (2, 4, and 16) of individual regions. Each region could individually serve as one of the MI-CNN inputs. The CNN features of these MI-CNN inputs would then be fused for COVID-19 classification. More importantly, the contributions of each CXR region could be evaluated through assessing the number of images that were accurately classified by their corresponding regions in the testing data sets. Results In both the whole-image and left- and right-lung region of interest (LR-ROI) data sets, MI-CNNs demonstrated good efficiency for COVID-19 classification. In particular, MI-CNNs with more inputs (2-, 4-, and 16-input MI-CNNs) had better efficiency in recognizing COVID-19 CXRs than the 1-input CNN. Compared to the whole-image data sets, the efficiency of LR-ROI data sets showed approximately 4% lower accuracy, sensitivity, specificity, and precision (over 91%). In considering the contributions of each region, one of the possible reasons for this reduced performance was that nonlung regions (eg, region 16) provided false-positive contributions to COVID-19 classification. The MI-CNN with the LR-ROI data set could provide a more accurate evaluation of the contribution of each region and COVID-19 classification. Additionally, the right-lung regions had higher contributions to the classification of COVID-19 CXRs, whereas the left-lung regions had higher contributions to identifying normal CXRs. Conclusions Overall, MI-CNNs could achieve higher accuracy with an increasing number of inputs (eg, 16-input MI-CNN). This approach could assist radiologists in identifying COVID-19 CXRs and in screening the critical regions related to COVID-19 classifications.

Use of low molecular weight heparin and hemoglobin fall in COVID-19 patients: A STROBE-compliant study

In patients with coronavirus disease 2019 (COVID-19), anticoagulation was suggested as a mitigating strategy. However, little research has been conducted on the adverse consequences of anticoagulant medication. This study aimed to investigate the adverse effect of low molecular weight heparin (LMWH) on hemoglobin fall in COVID-19 treatment. The electronic medical records of COVID-19 patients with pneumonia were collected (including clinical characteristics, vaccination status, complete blood count, coagulation profile, inflammatory cytokines, serum biochemical indicators, and computerized tomography imaging score). Whether they received LMWH, patients were divided into the LMWH group and the control group. Count data were represented as frequency distribution, and a 2-tailed test was used to compare the 2 groups. Spearman rank correlation was used to evaluate the interrelation between changes in hemoglobin and LMWH. The confounding factors were excluded by logistic regression analysis. A total of 179 COVID-19 pneumonia patients were enrolled (81 in the LMWH group and 98 in the control group). The change in hemoglobin was −6.0g/L (IQR −10.8 to 1.0) in the LMWH group and −2.0g/L (IQR −7.0 to 4.0) in the control group (P < .001, between-group difference, −5.0 g/L;95% confidence interval, −7.0 to −3.0, calculated with the use of the Mann–Whitney U test and the Hodges–Lehmann estimate of confidence intervals for pseudo-medians). The results of multivariate regression analysis showed that after adjusting for confounding factors, LMWH use was not associated with a decrease in hemoglobin (P > .05). In nonsevere COVID-19 patients with pneumonia, the preventive use of LMWH did not lower hemoglobin.

Randomized, placebo-controlled, single-blind phase 1 studies of the safety, tolerability, and pharmacokinetics of BRII-196 and BRII-198, SARS-CoV-2 spike-targeting monoclonal antibodies with an extended half-life in healthy adults

Background: BRII-196 and BRII-198 are two anti-SARS-CoV-2 monoclonal neutralizing antibodies as a cocktail therapy for treating COVID-19 with a modified Fc region that extends half-life. Methods: Safety, tolerability, pharmacokinetics, and immunogenicity of BRII-196 and BRII-198 were investigated in first-in-human, placebo-controlled, single ascending dose phase 1 studies in healthy adults. 44 participants received a single intravenous infusion of single BRII-196 or BRII-198 up to 3,000 mg, or BRII-196 and BRII-198 combination up to 1500/1500 mg, or placebo and were followed up for 180 days. Primary endpoints were incidence of adverse events (AEs) and changes from pre-dose baseline in clinical assessments. Secondary endpoints included pharmacokinetics profiles of BRII-196/BRII-198 and detection of anti-drug antibodies (ADAs). Plasma neutralization activities against SARS-CoV-2 Delta live virus in comparison to post-vaccination plasma were evaluated as exploratory endpoints. Results: All infusions were well-tolerated without systemic or local infusion reactions, dose-limiting AEs, serious AEs, or deaths. Most treatment-emergent AEs were isolated asymptomatic laboratory abnormalities of grade 1-2 in severity. BRII-196 and BRII-198 displayed pharmacokinetics characteristic of Fc-engineered human IgG1 with mean terminal half-lives of 44.6–48.6 days and 72.2–83.0 days, respectively, with no evidence of interaction or significant anti-drug antibody development. Neutralizing activities against the live virus of the SARS-CoV-2 Delta variant were maintained in plasma samples taken on day 180 post-infusion. Conclusion: BRII-196 and BRII-198 are safe, well-tolerated, and suitable therapeutic or prophylactic options for SARS-CoV-2 infection. Clinical Trial Registration:ClinicalTrials.gov under identifiers NCT04479631, NCT04479644, and NCT04691180.

Shugan Jieyu capsule improve sleep and emotional disorder in coronavirus disease 2019 convalescence patients: a randomized, double-blind, placebo-controlled trial.

OBJECTIVE: To evaluate the efficacy of the Shugan Jieyu capsule on improving sleep and emotional disorder during Coronavirus disease 2019 (COVID-19) convalescence. METHODS: We conducted a randomized, double-blind, placebo-controlled trial, and recruit 200 COVID-19 convalescence patients and then divide the subjects into two groups respectively: the experimental group ( 100) and the control group ( 100). Patients in the control group were given doses as a placebo, while those in the experimental group were given Shugan Jieyu capsule. The investigators mainly observed the differences between the two groups before and after treatment in terms of the rate of reduction and the rate of efficiency in Hamilton Depression Scale (HAMD-17) total scores from baseline, and recorded the scores of Hamilton Anxiety Scale (HAMA), Patient Health Questionnaire-15 (PHQ-15), Insomnia Severity Index (ISI) and Treatment Emergent Symptom Scale at 2 week, the 4 week and the 6 week respectively after treatment, and compared the differences between the groups. And the occurrence of adverse events was recorded. RESULTS: After 6-week treatment, there were statistically significant differences in the rate of reduction as well as efficiency in HAMD-17 scores, HAMA Total Scores, PHQ-15 Score, ISI Score from baseline in the experimental group and control group (< 0.05). There were 4 adverse events in the experimental group and 1 in the control group. CONCLUSION: Shugan Jieyu capsule could significantly improve sleep and emotional disorder in patients during COVID-19 convalescence.

Behavioral Intention and Its Predictors toward COVID-19 Booster Vaccination among Chinese Parents: Applying Two Behavioral Theories

The booster vaccination of COVID-19 is being implemented in most parts of the world. This study used behavioral psychology to investigate the predictors of parents' intentions regarding the COVID-19 booster vaccination for their children. This is a cross-sectional study with a self-designed questionnaire based on two behavioral theories-protective motivation theory (PMT) and theory of planned behavior (TPB). A stratified multi-stage sampling procedure was conducted in Nanjing, China, and multivariable regression analyses were applied to examine the parents' intentions. The intention rate was 87.3%. The response efficacy (ORa = 2.238, 95% CI: 1.360–3.682) and response cost (ORa = 0.484, 95% CI: 0.319–0.732) in the PMT, were significant psychological predictors of parents' intentions, and so were the attitude (ORa = 2.619, 95% CI: 1.480–4.636) and behavioral control (ORa = 3.743, 95% CI: 2.165–6.471) in the TPB. The findings of crucial independent predictors in the PMT and TPB constructs inform the evidence-based formulation and implementation of strategies for booster vaccination in children.

Coronavirus GenBrowser for monitoring adaptive evolution and transmission of SARS-CoV-2 (preprint)

COVID-19 has widely spread across the world, and much research is being conducted on the causative virus SARS-CoV-2. To help control the infection, we developed the Coronavirus GenBrowser (CGB) to monitor the pandemic. CGB allows visualization and analysis of the latest viral genomic data. Distributed genome alignments and an evolutionary tree built on the existing subtree are implemented for easy and frequent updates. The tree-based data are compressed at a ratio of 2,760:1, enabling fast access and analysis of SARS-CoV-2 variants. CGB can effectively detect adaptive evolution of specific alleles, such as D614G of the spike protein, in their early stage of spreading. By lineage tracing, the most recent common ancestor, dated in early March 2020, of nine strains collected from six different regions in three continents was found to cause the outbreak in Xinfadi, Beijing, China in June 2020. CGB also revealed that the first COVID-19 outbreak in Washington State was caused by multiple introductions of SARS-CoV-2. To encourage data sharing, CGB credits the person who first discovers any SARS-CoV-2 variant. As CGB is developed with eight different languages, it allows the general public in many regions of the world to easily access pre-analyzed results of more than 132,000 SARS-CoV-2 genomes. CGB is an efficient platform to monitor adaptive evolution and transmission of SARS-CoV-2.

Clinical characteristics of the first known cases of death caused by COVID-19 pneumonia.

Severe pneumonia caused by COVID-19 has resulted in many deaths worldwide. Here, we analyzed the clinical characteristics of the first 17 reported cases of death due to COVID-19 pneumonia in Wuhan, China. Demographics, initial symptoms, complications, chest computerized tomography (CT) images, treatments, and prognoses were collected and analyzed from the National Health Committee of China data. The first 17 reported deaths from COVID-19 were predominately in older men; 82.35% of patients were older than 65 years, and 76.47% were males. The most common initial symptoms were fever or fatigue (14 cases, 82.35%), respiratory symptoms, such as cough (12 cases, 70.59%), and neurological symptoms, such as headache (3 cases, 17.65%). The most common finding of chest CT was viral pneumonia (5 cases, 29.41%). Anti-infectives (11 cases, 64.71%) and mechanical ventilation (9 cases, 52.94%) were commonly used for treatment. Most of the patients (16 cases, 94.12%) died of acute respiratory distress syndrome (ARDS). Our findings show that advanced age and male gender are effective predictors of COVID-19 mortality, and suggest that early interventions to reduce the incidence of ARDS may improve prognosis of COVID-19 pneumonia patients.

Nutritional screening based on objective indices at admission predicts in-hospital mortality in patients with COVID-19 (preprint)

Background: Could nutritional status serve as prognostic factors for coronavirus disease 2019 (COVID-19)? The present study evaluated the clinical and nutritional characteristics of COVID-19 patients and explored the relationship between nutritional risk at admission and in-hospital mortality.Methods: A retrospective, observational study was conducted in two hospitals in Hubei, China. Confirmed cases of COVID-19 were typed as mild/moderate, severe, or critically ill. Clinical data and in-hospital death were collected. Nutritional risk was assessed using the Geriatric Nutritional Risk Index (GNRI), the Prognostic Nutritional Index (PNI), and the Controlling Nutritional Status (CONUT) via objective parameters at admission.Results: 295 patients were enrolled, including 66 severe patients and 41 critically ill patients. 25 deaths were observed, making 8.47% in the whole population and 37.88% in the critically ill subgroup. Patients had significant differences in nutrition-related parameters and inflammatory biomarkers among three types of disease severity. Patients with lower GNRI and PNI score, as well as higher CONUT, had a higher risk of in-hospital mortality. The receiver operating characteristic curves demonstrated the good prognostic implication of GNRI and CONUT score. The multivariate logistic regression showed that baseline nutritional status, assessed by GNRI, PNI, or CONUT score, was a prognostic indicator for in-hospital mortality.Conclusions: Despite variant assessment tools, poor nutritional status was associated with in-hospital death in patients infected with COVID-19. This study highlighted the importance of nutritional screening at admission and the new insight of nutritional monitoring or therapy.

Add-On Semi-Individualized Chinese Medicine for Coronavirus Disease 2019 (ACCORD): A Retrospective Cohort Study of Hospital Registries (preprint)

Background: Previous studies showed that the effect of antivirals for COVID-19 was promising but varied across patient population, and was modest among severe cases. Chinese Medicine (CM) was extensively used and reported effective in China, awaiting further evidence support. We aimed to evaluate the real-world effectiveness of add-on semi-individualized.Methods: A retrospective total sampling cohort of 1788 adult confirmed COVID-19 patients were recruited from all 2235 consecutive records retrieved from 5 hospitals in Wuhan during15 January to 13 March 2020. Consultation notes, laboratory/imaging investigations, pharmacy and prognosis records were linked by an electronic medical record system and verified by at least 2 researchers independently. The mortality of add-on semi-individualized CM users and non-users was compared by weighted hazard ratios of multivariable Cox regression and by propensity score matching. Change of biomarkers was compared between groups and the frequency of CMs used was analysed. Subgroup analysis was performed to stratify disease severity and dose of CM exposure. Sensitivity analyses were conducted to test the robustness.Findings: The crude mortality was 3.8% in the semi-individualized CM user group and 17.0% among the non-users. Add-on CM was associated with a significant mortality reduction of 58% (HR=0.42, 95%CI: 0.23 to 0.77, p=0.005) and 66% (HR=0.34, 95%CI: 0.15 to 0.76, p=0.009) among all and severe/critical COVID-19 cases with dose-dependent response, after inversely weighted with propensity score calculated by age, gender, history of hypertension, diabetes, coronary artery disease and disease severity. The result was robust in various stratified, weighted, matched, adjusted and sensitivity analyses. Severe/critical patients received add-on CM had a trend of stabilized D-dimer level after 3-7 days of admission compared to baseline.Interpretation: Add-on semi-individualized CM was associated with reduced mortality demonstrating dose-dependent response, especially among severe/critical COVID-19 patients. Chinese medicine could be considered as an add-on regimen for trial use.Funding Statement: This work is partially supported by the National Key Research and Development Program (2017YFC1703506 and 2020YFC0841600). Declaration of Interests: No financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.Ethics Approval Statement: This study was approved by the ethics review board of Hubei Provincial Hospital of Traditional Chinese Medicine (HBZY2020-C01-01). Written consent was waived due to the retrospective nature.

Response to the COVID-19 Outbreak in Urban Settings in China (preprint)

The COVID-19 outbreak in China was devastating, and spread throughout the country before being contained. Stringent physical distancing recommendations and shelter-in-place were first introduced in the hardest-hit provinces, and by March, these recommendations were uniform throughout the country. In the presence of an evolving and deadly pandemic, we sought to investigate the impact of this pandemic on individual well-being and prevention practices among Chinese urban residents. From March 2-11, 2020, 4,607 individuals were recruited from 11 provinces with varying numbers of COVID-19 casers using the social networking app WeChat to complete a brief, anonymous, online survey. The analytical sample was restricted to 2,551 urban residents. Standardized scales measured generalized anxiety disorder (GAD), the primary outcome. Multiple logistic regression was conducted to identify correlates of GAD alongside assessment of community practices in response to the COVID-19 pandemic. We found that during the COVID-19 pandemic, recommended public health practices significantly (p<0.001) increased, including wearing facial mask, practicing physical distancing, handwashing, decreased public spitting, and going outside in urban communities. Overall, 40.3% of participants met screening criteria for GAD and 49.3%, 62.6%, and 55.4% reported that their work, social life, and family life were interrupted by anxious feelings, respectively. Independent correlates of having anxiety symptoms included being a healthcare provider (aOR=1.58, p<0.01), living in regions with a higher density of COVID-19 cases (aOR=2.13, p<0.01), having completed college (aOR=1.38, p=0.03), meeting screening criteria for depression (aOR=6.03, p<0.01) and poorer perceived health status (aOR=1.54, p<0.01). COVID-19 had a profound impact on the health of urban dwellers throughout China. Not only did they markedly increase their self- and community-protective behaviors, but they also experienced high levels of anxiety associated with a heightened vulnerability like depression, having poor perceived health, and the potential of increased exposure to COVID-19 such as living closer to the epicenter of the pandemic.

Neutrophil surged for mortality of COVID-19: a correlational study (preprint)

Background: Multiorgan damage by SARS-CoV-2 results in alterations of many clinical measures associated with mortality of COVID-19. This research discussed the pioneering pathogenicity factors that lead to the extensive damage elusive. Objectives: A cohort of COVID-19 patients. Methods: : We conducted a correlational analysis of hospital outcomes with an independent cohort of COVID-19 patients and we also presented a death case to illustrate for time course of immune cell density. Results: : The results showed that dysregulated immune cell densities were correlated with hospitalization duration before death, not before discharge. High neutrophil densities allowed sorting out one third of total death cases while a density of less than 70% of the white blood cells allowed sorting out 70% of surviving cases. Conclusion: Collectively surged neutrophil was a top trigger for mortality in patients with COVID-19.

Quarantine At Home May Not Enough!-From the Epidemiological Data In Shaanxi Province of China (preprint)

Objectives : A pneumonia associated with 2019 novel coronavirus (2019-nCoV, subsequently named SARS-CoV2) emerged worldwide since December, 2019. We aimed to describe the epidemiological characteristics of 2019 coronavirus disease (COVID-19) in Shaanxi province of China.  Results: 1. Among the 245 patients, 132 (53.9%) were males and 113 (46.1%) were females. The average age was 46.15±16.43 years, ranging from 3 to 89 years. 2.  For the clinical type, 1.63% (4/245) patients were mild type , 84.90% (208/245) were moderate type, 7.76% (19/245) were severe type, 5.31% (13/245) were critical type and only 0.41% (1/245) was asymptomatic. 3. Of the 245 patients, 116 (47.35%) were input case, 114 (46.53%) were non-input case , and 15 (6.12%) were unknown exposure. 4. 48.57% (119/245) cases were family cluster , involving 42 families. The most common pattern of COVID-19 family cluster was between husband and wife or between parents and children. 

Cohort Profile: Chinese Color Nest Project (preprint)

The ongoing CCNP was established to plot normative growth curves for brain structure and function across the human lifespan, and link age-related changes in brain imaging measures with psycho-behavioral functions at the behavioral, cognitive and emotional levels using an accelerated longitudinal design. It comprises three phases: developmental CCNP (devCCNP: 6-20 years), standardizing CCNP (stdCCNP: 20-60 years) and aging CCNP (ageCCNP: 60-90 years). The devCCNP started in 2013 and has successfully acquired CCNP-SWU data with three repeated measurements ( the trial stage of devCCNP), and accumulated CCNP-CAS baseline data (the second stage of devCCNP). CCNP-SWU consists of 201 age-sex stratified schoolchildren at enrollment (100 children followed up for 2.5 years at 1.25-year intervals) while CCNP-CAS has been recruiting participants since July 2018, and has collected data from 133 eligible children so far. A T1-weighted MRI and two resting functional MRI scans were acquired across three waves in CCNP-SWU with the same imaging protocols on a Siemens Trio 3T scanner at Southwest University in Chongqing, China. CCNP-SWU obtained longitudinal biophysical, social, behavioral and cognitive data via parent-reported questionnaires, self-reported questionnaires, behavioral assessment, as well as E-Prime computer tasks. Data were collected on the impact of COVID-19 on children’s learning and daily life from 46 children between March and May 2020. Children’s emotional states during COVID-19 pandemic were also measured. Data are accessed by researchers and collaborators of CCNP upon agreement with the principal investigator.

COVID-19: Look to the Future, Learn from the Past (preprint)

There is a current pandemic of a new type of coronavirus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The number of confirmed infected cases has been rapidly increasing. This paper analyzes the characteristics of SARS-CoV-2 in comparison with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and influenza. COVID-19 is similar to the diseases caused by SARS-CoV and MERS-CoV virologically and etiologically, but closer to influenza in epidemiology and virulence. The comparison provides a new perspective for the future of the disease control, and offers some ideas in the prevention and control management strategy. The large number of infectious people from the origin, and the highly infectious and occult nature have been two major problems, making the virus difficult to eradicate. We thus need to contemplate the possibility of long-term co-existence with COVID-19.

Radiologic evaluation of discharge quality in patients with COVID-19 (preprint)

Background   Worldwide spread of the novel coronavirus disease 2019 (COVID-19) has made hundreds of thousands people sick and fortunately many of them have been treated and discharged. However, it remains unclear how well the discharged patients were recovering. Chest CT scan, with demonstrated high sensitivity to COVID-19, was used here to examine clinical manifestations in patients at discharge.Methods This study registered retrospectively single-center case series of 180 discharged patients, all confirmed with COVID-19 at Wuhan Red Cross Hospital in Wuhan, China. Epidemiological, demographic, clinical, laboratory and treatment data were collected. CT imaging features of absorption vs progressive stage were compared and analyzed.Results Five pulmonary lobes were affected in 54 (30%) of the 180 patients at the absorption stage, comparing to 66% of them at the progressive stage (P=1.45×10-11). Forty five (25%) patients had pleural effusion on admission and 13 of them still carried hydrothorax when discharged as per standard discharge criteria(P=4.48×10-6). Besides, compared with those at progressive stage, 97 (54%) discharged patients had interlobular thickening (P=6.95×10-3) and 43% of them still presented adjacent pleura thickening (P=5.58×10-5). The median total CT score of discharged patients at absorption stage was lower than progressive stage (3 vs 12.5 ). The median total CT score recovery rate was 67% (range, 0-100%) and 139 (77%) patients showed less than 90% improvement at discharge.Conclusions A majority (77%) of the discharged patients had not recovered completely. The current discharge criteria may need to include 90% or higher CT score-based recovery rate.Authors Jingwen Li, Xi Long, Fang Fang, and Xuefei Lv contributed equally to this work.Authors Zhicheng Lin and Nian Xiong are joint last coauthors.

COVID-19: Look to the Future, Learn from the Past (preprint)

Background: There is a current worldwide outbreak of a new type of coronavirus COVID-19. The number of confirmed infected cases is rapidly increasing. Method: This paper analyzes the characteristics of COVID-19 in comparison with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and influenza. Diagnostic data for foreign citizens evacuated from Wuhan were collected and compiled. Current prevention and control strategies have been analyzed. Results: COVID-19 is similar to SARS-CoV and MERS-CoV virologically and etiologically, but similar to influenza in epidemiology and virulence. The prevalence rate in Wuhan was inferred to be close to 1%. The comparison provides a new perspective for the future of the disease, and offers some advice in the prevention and control management strategy. Conclusion: The large number of patients and the strong occult nature are two big problems, making the virus difficult to eradicate. We need to contemplate the possibility of long-term co-existence with COVID-19.

Temporal dynamics in viral shedding and transmissibility of COVID-19 (preprint)

We report temporal patterns of viral shedding in 94 laboratory-confirmed COVID-19 patients and modelled COVID-19 infectiousness profile from a separate sample of 77 infector-infectee transmission pairs. We observed the highest viral load in throat swabs at the time of symptom onset, and inferred that infectiousness peaked on or before symptom onset. We estimated that 44% of transmission could occur before first symptoms of the index. Disease control measures should be adjusted to account for probable substantial pre-symptomatic transmission.

Forecasting of COVID-19 Spread with dynamic transmission rate

The COVID-19 was firstly reported in Wuhan, Hubei province, and it was brought to all over China by people travelling for Chinese New Year. The pandemic coronavirus with its catastrophic effects is now a global concern. Forecasting of COVID-19 spread has attracted a great attention for public health emergency. However, few researchers look into the relationship between dynamic transmission rate and preventable measures by authorities. In this paper, the SEIR (Susceptible Exposed Infectious Recovered) model is employed to investigate the spread of COVID-19. The epidemic spread is divided into two stages: before and after intervention. Before intervention, the transmission rate is assumed to be a constant since individual, community and government response has not taken into place. After intervention, the transmission rate is reduced dramatically due to the societal actions or measures to reduce and prevent the spread of disease. The transmission rate is assumed to follow an exponential function, and the removal rate is assumed to follow a power exponent function. The removal rate is increased with the evolution of the time. Using the real data, the model and parameters are optimized. The transmission rate without measure is calculated to be 0.033 and 0.030 for Hubei and outside Hubei province, respectively. After the model is established, the spread of COVID-19 in Hubei province, France and USA is predicted. From results, USA performs the worst according to the dynamic ratio. The model has provided a mathematical method to evaluate the effectiveness of the government response and can be used to forecast the spread of COVID-19 with better performance.