Effects of purifiers on the airborne transmission of droplets inside a bus Note: This paper is part of the special topic, Flow and the Virus

During an airborne infectious disease outbreak, bus passengers can be easily infected by the dispersion of exhaled droplets from an infected passenger. Therefore, measures to control the transport of droplets are necessary, such as a mask or purifier. The current research examined aerosol transport in a bus with air-conditioning. To determine the dispersion path, deposition distribution, and droplet escape time, the computational fluid dynamics were used to predict the flow field and the dispersion of droplets considering the effects of droplet size, location of the infected person, and purifier type. In addition, based on the viability and the number of virus particles in a droplet, the total number of virus particles inhaled by passengers over a 4-h journey was obtained by the superposition method. The Wells–Riley equation was then used to assess the infection risk of the passengers in the bus cabin. The results showed that droplets with a size of 1–20 μm have essentially the same deposition characteristics, and the location of the infected passenger affects the distribution of droplets' transport and the effectiveness of a purifier in removing droplets. A purifier can effectively remove droplets from passengers' coughs and reduce the infection risk of passengers. The performance of the smaller purifiers is not as stable as that of the larger purifiers, and the performance is influenced by the airflow structure where the infected passenger is located.

User Perception of Public Parks: A Pilot Study Integrating Spatial Social Media Data with Park Management in the City of Chicago

User-generated content (UGC) is a relatively young field of research;however, it has been proven useful in disciplines such as hospitality and tourism, to elicit public opinions of place usage. In landscape architecture and urban planning, UGC has been used to understand people’s emotions and movement in a space, while other areas and additional functions are yet to be discovered. This paper explores the capability of UGC in revealing city-scale park management problems and the applicability of social media as a future tool in bridging visitor feedback to city parks and recreation department staff. This research analyzed the spatial characteristics and patterns of Google Maps review quantity, rating score, and review comments. The results of this pilot study indicate the spatial and structural features of the Chicago parks and demonstrate distribution problems, financial investment priority concerns, park usage characteristics, and user preferences of the park attributes. Findings affirm that user-generated online reviews can be used as an alternative and self-reporting data source to effectively assess the natural performance and users’ experience of city parks and can potentially serve as an evaluative tool for public park management.

Predicting Progression to Severe COVID-19 Using the PAINT Score Based on Natural Killer Cells (preprint)

Objectives: One of the major challenges in treating patients with coronavirus disease 2019 (COVID-19) is predicting the severity of disease. Natural killer (NK) cells are innate lymphocytes that respond to viral infection and might relate to COVID-19 disease severity. Therefore, we aimed to develop a new predictive score for progression from mild/moderate to severe COVID-19 based on NK cells information. Method: In total, 239 hospitalized patients with COVID-19 from two medical center in China were retrospectively included. The prognostic effects of variables, including clinical data and laboratory findings from the electronic medical records of each hospital, were analyzed using Cox proportional hazards model and Kaplan-Meier methods. A prognostic score was developed to predict progression from mild/moderate to severe COVID-19. Results: Among the 239 patients, 216 (90.38%) patients had mild/moderate disease and 23 (9.62%) progressed to severe disease. After adjusting multiple confounding factors, pulmonary disease, age >75, IgM, CD16+/CD56+ NK cells and aspartate aminotransferase were independently predictors of progression to severe COVID-19. Based on these five factors, a new predictive score (the ‘PAINT score’) was established and showed a high predictive value (C-index = 0.91, 0.902 ± 0.021, p<0.001). The PAINT score was validated using nomogram, bootstrap internal validations, calibration curves, decision curves and clinical impact curve, all of which confirmed its high predictive value. Conclusions: The PAINT score for progression from mild/moderate to severe COVID-19 based on NK cell information may be helpful to identify patients at high risk of progression. Trial registration: None

Association between D-dimer level and chest CT severity score in patients with SARS-COV-2 pneumonia (preprint)

The elevated level of D-dimer and its relationship with poor outcomes in COVID-19 pneumonia patients have been demonstrated. In addition to a hypercoagulable state, D-dimer is also a biomarker of inflammation. We investigated the relationship between D-dimer level and chest computed tomography (CT) severity score, which could reflect the severity of inflammation in COVID-19 pneumonia patients. We retrospectively enrolled 86 consecutive COVID-19 pneumonia patients. CT severity scores were computed to quantify the overall lung involvement. The D-dimer level among CT score tertiles and the association of the D-dimer level with CT score were analyzed. Our results showed that the median D-dimer level was 0.70 mg/L (IQR: 0.35-1.76). 49 patients (57.0%) had D-dimer level above the normal range (≤ 0.55mg/L). The D-dimer levels were significantly different across CT score tertiles (0.37 mg/l [IQR, 0.31-0.87], 0.66 mg/l [IQR, 0.39-1.43], 1.83 mg/l [IQR, 0.85-4.41], P<0.001). The natural logarithm of the D-dimer level was significantly associated with the CT score (rs =0.586, P <0.001). In conclusion, the D-dimer level may predict the severity of inflammation of COVID-19 pneumonia prior to coagulopathy/thrombosis. This could be an additional explanation for the mechanism of elevated D-dimer level predicting higher mortality.

Clinical characteristics and risk factors for mortality in patients with COVID-19 and chronic obstructive pulmonary disease in Wuhan, China (preprint)

Patients with COVID-19 and COPD are at high risks. However, the risk factors for mortality in COPD patients infected COVID-19 are limited. In this retrospective study, consecutive COPD cases infected COVID-19 in East District of People's Hospital of Wuhan University from Jan 11th 2020 to Mar 28th 2020 were included. Different outcomes were compared between dead and discharged patients. Cox regression analysis was performed to explore the risk factors for death. Totally, 52 cases were included (aged 64.0-79.0 years, 39 [75.0%] males). Common symptoms on admission were cough (43, 82.6%), fever (41, 78.8%) and expectoration (21, 40.3%). Thirty-eight (73.1%) patients were discharged, and 14 (26.9%) cases were dead which mainly caused by multiple organ failure (7, 50.0%) and respiratory failure (6, 42.9%). Multivariate analysis indicated that age > 70 years (HR, 7.859, 95% CI: 1.376, 44.875; P = 0.020) and count of lymphocyte ≤ 0.8×109/L (HR, 27.429, 95% CI: 3.336, 225.530; P = 0.002) were risk factors for death. The study showed that close monitoring of the risk indexes is important for early supportive care during the management of patients with COVID-19 and COPD.

Clinical Characteristics of COVID-19 Patients with Recurrent PCR Positivity After Hospital Discharge (preprint)

Objective: This study aimed to investigate the clinical characteristics of COVID-19 patients with recurrent SARS-CoV-2 positivity after hospital discharge. Methods: This retrospective study included COVID-19 patients who were readmitted for recurrence of positive SARS-CoV-2 RNA. Univariate and multivariate analyses were performed to assess the risk factors associated to the duration of recurrent RNA positivity.Results: Among the 287 discharged COVID-19 patients, 33 (11.5%) patients with recurrent PCR positivity were included. Among these patients, 21 (63.7%) patients were female, their mean age was 48.7 (±19.7) years old. 22 (66.7%) patients were asymptomatic. The following clinical features were presented in other patients: cough, fatigue, sore throat, fever and expectoration. The chest CT findings revealed that 8 (24.2%) patients were characterized by deterioration compared to the previous results. The median duration of recurrent RNA positivity was 9.0 days (IQR, 6.0, 15.0). We found that increased serum SARS-CoV-2-specific IgG antibody titer, elevated serum creatinine level, and female gender were the risk factors for the prolonged duration of recurrent RNA positivity.Conclusion: SARS-CoV-2 turned positive in a minority of discharged patients with COVID-19. Most patients experienced mild clinical course. Increased IgG antibody titer, creatinine and female gender were correlated to the prolonged RNA clearance time.

CONUT score is associated with mortality in patients with COVID-19: a retrospective study in Wuhan (preprint)

Background The coronavirus disease 2019 (COVID-19) pneumonia, outbreak in Wuhan, China, has led to a global pandemic. The high mortality of COVID-19 patients makes it significant to evaluate possible disease progression. This study was designed to explore the prognostic value of Controlling Nutritional Status (CONUT) score in patients with COVID-19.Methods Patients diagnosed with COVID-19 of a single center in Wuhan, China from January 2020 to February 2020 were enrolled in this study. Logistic regression analysis was performed to find independent risk factor of mortality. Receiver operating characteristics (ROC) curve was drawn to evaluate the prognostic value of CONUT score.Results Among 442 included patients, there were 79 non-survivors with mortality of 17.9%. Compared with survivors, the median age (p < 0.001) and male ratio (p = 0.042) were higher in non-survivors. Non-survivors had higher incidence of comorbidities including hypertension (p < 0.001), chronic lung disease (p = 0.001) and cardiovascular disease (p = 0.005). Complications such as respiratory failure(p < 0.001), acute kidney injury (AKI) (p < 0.001) occurred more frequently in non-survivors. Multivariate logistic regression analysis showed that CONUT (p = 0.002), lactate dehydrogenase (LDH) (p < 0.001), C-reactive protein (CRP) (p = 0.020) were risk factor of mortality in COVID-19 patients. Area under the ROC curve (AUC) of CONUT and Nutrition risk screening 2002 (NRS2002) score were 0.813 and 0.795, respectively. Comprised of CONUT, LDH, CRP, the constructed prognostic model had higher AUC of 0.923 (Z = 3.5210, p < 0.001).Conclusion CONUT is an independent risk factor of mortality in COVID-19 patients. Evaluating CONUT is beneficial for clinicians to predict the progression of COVID-19 patients and strengthen monitoring and management to improve prognosis.

Clinical characteristics of COVID-19 and establishment of a disease risk prediction model (preprint)

Background: COVID-19 is spreading worldwide. No specific medicine has been used for the treatment of coronavirus infections. The aim of this study is to establish a new risk predictive model to screen potential critical patients for early intervention.Methods: In this study, Clinical characteristics were collected and analyzed from 317 confirmed cases of COVID-19. A total of 175 of the 317 cases with detailed examination results were included to establish models for predicting the risk of disease progression. Major independent risk factors were incorporated into MuLBSTA model to establish new models for predicting critical risk. We further tracked 25 mild or moderate patients with COVID-19 to research dynamic changes of the major independent risk factors in COVID-19 progression.Results: The average age of all of the 317 patients was 47.76 (SD 17.22). A total of 48 (15.14%) were diagnosed with mild disease with a median age of 34(39.29±13.04), 116(36.59%) were diagnosed with moderate disease with a median age of 34(38.78±12.32), 38(11.99%) were diagnosed as severe with a median age of 56(58.24±15.12), and 115(36.28) were diagnosed as critical with a median age of 59(56.89+17.09). The most common symptom at onset of illness were fever(211[66.56%] patients). Age>50, CK>64, CD4≤461, and CD8≤241 were predicted to be major independent risk factors that could promote COVID-19 progression. Compared with the MuLBSTA model, the predictive ability of the CD4-CD8-MuLBSTA model and the CD4-MuLBSTA model were improved by 11.87% and 11.79%, respectively. In the prospective study, CK value began to show significant differences from day13. The average CD4 in Severe Group began to decline significantly on the fourth day, and the CD8 maintained a relatively low level in the Severe Group after day13.Conclusions: Severe COVID-19 patients were significantly older than non-severe patients. Immune systems of severe COVID-19 patients were significantly suppressed, and advanced age(>50 years), low levels of CD4(≤461) or CD8(≤241) was important clinical manifestations of rapid deterioration. CK values in severe COVID-19 patients were significantly higher than in no severe patients. CD4 and CD8 were incorporated into the MuLBSTA to establish a new model, which is an ideal risk prediction model for COVID-19 patients.

Clinical characteristics of 82 death cases with COVID-19 (preprint)

Background A recently developing pneumonia caused by SARS-CoV-2 was originated in Wuhan, China, and has quickly spread across the world. We reported the clinical characteristics of 82 death cases with COVID-19 in a single center. Methods Clinical data on 82 death cases laboratory-confirmed as SARS-CoV-2 infection were obtained from a Wuhan local hospital's electronic medical records according to previously designed standardized data collection forms. Findings All patients were local residents of Wuhan, and the great proportion of them were diagnosed as severe illness when admitted. Most of the death cases were male (65.9%). More than half of dead patients were older than 60 years (80.5%) and the median age was 72.5 years. The bulk of death cases had comorbidity (76.8%), including hypertension (56.1%), heart disease (20.7%), diabetes (18.3%), cerebrovascular disease (12.2%), and cancer (7.3%). Respiratory failure remained the leading cause of death (69.5%), following by sepsis syndrome/MOF (28.0%), cardiac failure (14.6%), hemorrhage (6.1%), and renal failure (3.7%). Furthermore, respiratory, cardiac, hemorrhage, hepatic, and renal damage were found in 100%, 89%, 80.5%, 78.0%, and 31.7% of patients, respectively. On the admission, lymphopenia (89.2%), neutrophilia (74.3%), and thrombocytopenia (24.3%) were usually observed. Most patients had a high neutrophil-to-lymphocyte ratio of >5 (94.5%), high systemic immune-inflammation index of >500 (89.2%), increased C-reactive protein level (100%), lactate dehydrogenase (93.2%), and D-dimer (97.1%). A high level of IL-6 (>10 pg/ml) was observed in all detected patients. Median time from initial symptom to death was 15 days (IQR 11-20), and a significant association between aspartate aminotransferase (p=0.002), alanine aminotransferase (p=0.037) and time from initial symptom to death were interestingly observed. Conclusion Older males with comorbidities are more likely to develop severe disease, even die from SARS-CoV-2 infection. Respiratory failure is the main cause of COVID-19, but either virus itself or cytokine release storm mediated damage to other organ including cardiac, renal, hepatic, and hemorrhage should be taken seriously as well.