Identify the natural and socio-economic influencing factors of the new coronavirus pneumonia（COVID-19） incidence rates in Chinese cities

This study explored the effects of both natural and socio-economic factors, such as city size and healthcare capacity, on the spreading of COVID-19 in China's urban population from January 1 to March 5, 2020. Several statistical models and machine learning methods were used to identify the key determinants of the incidence rate of COVID-19. Based on the interpretable machine learning framework, possible nonlinear relationships between incidences and key impact factors were explored. The results showed that the incidence rate of COVID-19 in cities was influenced by several factors simultaneously. Among the factors, the population inflow rate from Wuhan was the factor that showed the highest correlation coefficient（0.43）, followed by the population growth rate（0.38）. Population migration size, city size and healthcare capacity were the key influencing factors. Nonlinear relationships existed between the key influencing factors and incidence rates. To be specific, the inflow rate from Wuhan had a S-shaped relationship and reaches an asymptote after 2%;the population density had an approximately linear relationship;the per capita GDP showed an evident inverted U curve with the per capita GDP over 100,000 yuan as the inflection point. City development needs to pay more attention to population density control and economic growth in order to bring more health benefits.

Speaking-Induced Charge-Laden Face Masks with Durable Protectiveness and Wearing Breathability.

Face masks, which serve as personal protection equipment, have become ubiquitous for combating the ongoing COVID-19. However, conventional electrostatic-based mask filters are disposable and short-term effective with high breathing resistance, causing respiratory ailments and massive consumption (129 billion monthly), intensifying global environmental pollution. In an effort to address these challenges, the introduction of a piezoelectric polymer was adopted to realize the charge-laden melt-blown via the melt-blowing method. The charge-laden melt-blown could be applied to manufacture face masks and to generate charges triggered by mechanical and acoustic energy originated from daily speaking. Through an efficient and scalable industrial melt-blown process, our charge-laden mask is capable of overcoming the inevitable electrostatic attenuation, even in a high-humidity atmosphere by long-wearing (prolonging from 4 to 72 h) and three-cycle common decontamination methods. Combined with outstanding protective properties (PM2.5 filtration efficiency >99.9%), breathability (differential pressure <17 Pa/cm2), and mechanical strength, the resultant charge-laden mask could enable the decreased replacement of masks, thereby lowering to 94.4% of output masks worldwide (∼122 billion monthly) without substituting the existing structure or assembling process.

Effect of blood analysis and immune function on the prognosis of patients with COVID-19.

INTRODUCTION: This retrospective study investigated the implications of changes in blood parameters and cellular immune function in patients with Coronavirus Disease 2019 (COVID-19). METHODS: Records were reviewed of 85 patients admitted with COVID-19 between February 4 and 16, 2020. The primary outcome was in-hospital death. RESULTS: Fourteen patients died. The baseline leukocyte count, neutrophil count and hemoglobin was significantly higher in non-survivors compared with survivors, while the reverse was true of lymphocyte count, platelet, PaO2/FiO2, CD3+ count and CD4+ count. The percentage of neutrophil count > 6.3×109/L in death group was significantly higher than that in survival group, and multivariate logistic regression showed neutrophil count > 6.3×109/L was independently associated with mortality. However, there were not significant difference in IgG, IgM, IgA, C3, C4 and the percentage of IgE > 100 IU/ml between the death group and survival group. Areas under the receiver operating characteristic curves of the following at baseline could significantly predict mortality: leukocyte, neutrophil, lymphocyte, CD3+ and CD4+ counts. CONCLUSIONS: For hospitalized patients with COVID-19, lymphocyte, CD3+ and CD4+ counts that marked decrease suggest a poor outcome. Admission neutrophil count > 6.3 ×109/L is independently associated with mortality. At admission, leukocyte, neutrophil, lymphocyte, CD3+ and CD4+ counts should receive added attention.

Characteristics of coagulation alteration in patients with COVID-19.

Abnormal blood coagulation often occurs in critically ill patients, which seriously affects their prognosis. This retrospective study investigated the implications of changes in blood coagulation in patients with coronavirus disease 2019 (COVID-19). Records were reviewed for patients admitted with COVID-19 between February 4 and 16, 2020. The primary outcome was in-hospital death. A total of 85 patients were included, of whom 12 died in the hospital. The admission prothrombin time (PT), international normalized ratio (INR), and levels of D-dimer and fibrin/fibrinogen degradation products (FDP) were significantly higher in non-survivors than in survivors, while the reverse was true for prothrombin time activity (PT-act) and PaO2/FiO2. Multivariate logistic regression showed that PT-act < 75% was independently associated with mortality. The area under the receiver operating characteristic curves for PT-act, D-dimer, and FDP at admission could significantly predict mortality. The AUCs for PT-act were larger than those for D-dimer and FDP; however, there was no significant difference. After 2 weeks of treatment, the coagulation parameters of the surviving patients improved. COVID-19 is often accompanied by abnormal coagulation. PT-act at admission is able to predict mortality in patients with COVID-19 as can D-dimer and FDP levels. PT-act < 75% is independently associated with mortality.