Impact of the COVID-19 epidemic on medical product imports from china from outbreak to stabilization: Monthly panel data regression and instrumental variable test.

This study conduct regressions of panal data with OLS and test with IV, empirically examines the COVID-19 epidemic's impact on the import of medical products from China from the perspective of the importing countries, exporting country, and other trading partners, and analyzes the inter-temporal impact across different product categories. The empirical results reveal that, in importing countries, the COVID-19 epidemic increased the import of medical products from China. In China, as an exporting country, the epidemic inhibited the export of medical products; by contrast, for other trading partners, it promoted the import of medical products from China. Among them, key medical products were most affected by the epidemic, followed by general medical products and medical equipment. However, the effect was generally found to wane after the outbreak period. Additionally, we focus on how political relations shape China's medical product export pattern and how the Chinese government is using trade means to improve external relations. In the post-COVID-19 era, countries should prioritize the stability of supply chains for key medical products and actively engage in international cooperation on health governance to further combat the epidemic.

All-Fabric-Based Flexible Capacitive Sensors with Pressure Detection and Non-Contact Instruction Capability

The flexible and wearable capacitive sensors have captured tremendous interest due to their enormous potential for healthcare monitoring, soft robotics, and human−computer interface. However, despite recent progress, there are still pressing challenges to develop a fully integrated textile sensor array with good comfort, high sensitivity, multisensing capabilities, and ultra-light detection. Here, we demonstrate a pressure and non-contact bimodal fabric-only capacitive sensor with highly sensitive and ultralight detection. The graphene nanoplatelets-decorated multidimensional honeycomb fabric and nickel-plated woven fabric serve as the dielectric layer and electrode, respectively. Our textile-only capacitive bimodal sensor exhibits an excellent pressure-sensing sensitivity of 0.38 kPa−1, an ultralow detection limit (1.23 Pa), and cycling stability. Moreover, the sensor exhibits superior non-contact detection performance with a detection distance of 15 cm and a maximum relative capacitance change of 10%. The sensor can successfully detect human motion, such as finger bending, saliva swallowing, etc. Furthermore, a 4 × 4 (16 units) textile-only capacitive bimodal sensor array was prepared and has excellent spatial resolution and response performance, showing great potential for the wearable applications.

Criteria for judging the immune markers of COVID-19 disease vaccines.

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sweeping the world, effective and affordable vaccines are in urgent need. A reliable system for the assessment of SARS-CoV-2 vaccines would boost the development of vaccines and reduce the research cost. We constructed a logistic regression model and analyzed the relationship between antibody (Ab) level and efficacy of different vaccine types. The relationship between assessment dates and Ab levels was depicted by plotting the mean of Ab levels evolved over time and a fitted cubic polynomial model. Anti-spike immunoglobulin G (IgG) could best estimate the vaccine efficacy (VE) (adjusted R 2  = 0.731) and neutralizing Ab to live SARS-CoV-2 also explained a fine relationship (adjusted R 2 = 0.577). Neutralizing Abs to live SARS-CoV-2 in inactivated virus vaccines reached a peak during days 40-60, and their receptor-binding domain (RBD)-IgG peaked during days 40-50. For messenger RNA (mRNA) and viral vector vaccines, their neutralizing Ab to live SARS-CoV-2 peaked later than day 40, and for RBD-IgG during days 30-50. For mRNA and viral vector vaccines, their peak time of Abs was later than that in inactivated virus vaccines. RBD-IgG peaked earlier than Ab to live SARS-CoV-2. Anti-spike IgG and Ab to live SARS-CoV-2 may be good immune markers for VE assessment.

Association between environmental factors and COVID-19 in Shanghai, China.

The outbreak of coronavirus disease 2019 (COVID-19) continues to spread worldwide and has led to recession, rising unemployment, and the collapse of the health-care system. The aim of this study was to explore the exposure-response relationship between daily confirmed COVID-19 cases and environmental factors. We used a time-series generalized additive model (GAM) to investigate the short-term association between COVID-19 and environmental factors by using daily meteorological elements, air pollutant concentration, and daily confirmed COVID-19 cases from January 21, 2020, to February 29, 2020, in Shanghai, China. We observed significant negative associations between daily confirmed COVID-19 cases and mean temperature (Tave), temperature humidity index (THI), and index of wind effect (K), whereas air quality index (AQI), PM2.5, PM10 NO2, and SO2 were significantly associated with the increase in daily confirmed COVID-19 cases. A 1 °C increase in Tave, one-unit increase in THI, and 10-unit increase in K (lag 0-7 days) were associated with 4.7, 1.8, and 1.6% decrease in daily confirmed cases, respectively. Daily Tave, THI, K, PM10, and SO2 had significant lag and persistence (lag 0-7 days), whereas the lag and persistence of AQI, PM2.5, and NO2 were significant at both lag 0-7 and 0-14 days. A 10-µg/m3 increase in PM10 and 1-µg/m3 increase in SO2 was associated with 13.9 and 5.7% increase in daily confirmed cases at lag 0-7 days, respectively, whereas a 10-unit increase in AQI and a 10-µg/m3 increase in PM2.5 and NO2 were associated with 7.9, 7.8, and 10.1% increase in daily confirmed cases at lag 0-14 days, respectively. Our findings have important implications for public health in the city of Shanghai.

Psychological status of medical workforce during the COVID-19 pandemic: A cross-sectional study.

The pandemic of 2019 coronavirus disease (COVID-19) has burdened an unprecedented psychological stress on people around the world, especially the medical workforce. The study focuses on assess the psychological status of them. The authors conducted a single-center, cross-sectional survey via online questionnaires. Occurrence of fear, anxiety and depression were measured by the numeric rating scale (NRS) on fear, Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD), respectively. A total of 2299 eligible participants were enrolled from the authors' institution, including 2042 medical staff and 257 administrative staff. The severity of fear, anxiety and depression were significantly different between two groups. Furthermore, as compared to the non-clinical staff, front line medical staff with close contact with infected patients, including working in the departments of respiratory, emergency, infectious disease, and ICU, showed higher scores on fear scale, HAMA and HAMD, and they were 1.4 times more likely to feel fear, twice more likely to suffer anxiety and depression. The medical staff especially working in above-mentioned departments made them more susceptible to psychological disorders. Effective strategies toward to improving the mental health should be provided to these individuals.