Spatiotemporal Variations of Aerosols in China during the COVID-19 Pandemic Lockdown

The widespread nature of the coronavirus disease 2019 (COVID-19) pandemic is gradually changing people’s lives and impacting economic development worldwide. Owing to the curtailment of daily activities during the lockdown period, anthropogenic emissions of air pollutants have greatly reduced, and this influence is expected to continue in the foreseeable future. Spatiotemporal variations in aerosol optical depth (AOD) can be used to analyze this influence. In this study, we comprehensively analyzed AOD and NO2 data obtained from satellite remote sensing data inversion. First, data were corrected using Eidetic three-dimensional‒long short-term memory to eliminate errors related to sensors and algorithms. Second, taking Hubei Province in China as the experimental area, spatiotemporal variations in AOD and NO2 concentration during the pandemic were analyzed. Finally, based on the results obtained, the impact of the COVID-19 pandemic on human life has been summarized. This work will be of great significance to the formulation of regional epidemic prevention and control policies and the analysis of spatiotemporal changes in aerosols.

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

High number and specific comorbidities independently of age are closely related to progression and poor prognosis in patients with COVID-19 (preprint)

Background— Some patients with comorbidities and rapid disease progression have a poor prognosis.Aim—In this study, we aimed to investigate the distribution characteristics of comorbidities and their relationship with disease progression and outcomes of COVID-19 patients.Methods— A total of 718 COVID-19 patients were divided into five clinical type groups and eight age-interval groups. The distribution characteristics of comorbidities were compared between the different clinical type groups and between the different age-interval groups, and their relationships with disease progression and outcomes of COVID-19 patients were assessed.Results—Approximately 88.62% (637/718) of the COVID-19 patients were twenty to fifty-nine years old. Approximately 65.73% (554/718) had one or more comorbidities, and common comorbidities included non-alcoholic fatty liver disease (NAFLD), hyperlipidaemia, hypertension, diabetes mellitus (DM), chronic hepatitis B (CHB), hyperuricaemia and gout. COVID-19 patients with comorbidities were older, especially those with chronic obstructive pulmonary disease (COPD) and cardiovascular disease (CVD). Hypertension, DM, COPD, chronic kidney disease (CKD) and CVD were mainly found in severe COVID-19 patients. According to spearman and partial correlation analysis the number of comorbidities was correlated positively with disease severity, the number of comorbidities and NAFLD were correlated positively with virus negative conversion time, hypertension, CKD and CVD were primarily associated with those who died, and the above-mentioned correlation existed independently of age. Risk factors included the number of comorbidities and hyperlipidaemia for disease severity, age, the number of comorbidities, hyperlipidaemia, NAFLD and COPD for the virus negative conversion time, and the number of comorbidities and CKD for prognosis. Number of comorbidities played a predictive role in disease progression and outcomes.Conclusions—High number and specific comorbidities independently of age are closely related to progression and poor prognosis in patients with COVID-19. These findings provide a reference for clinicians to focus on the number and specific comorbidities in COVID-19 patients to predict disease progression and prognosis.Clinical Trial Registry: Chinese Clinical Trial Register ChiCTR2000034563A statement about the manuscript in research square This manuscript has been presented as preprint in the research sqaure according to the following link: https://www.researchsquare.com/article/ rs-576949/v2.

Immunization with the receptor-binding domain of SARS-CoV-2 elicits antibodies cross-neutralizing SARS-CoV-2 and SARS-CoV without antibody-dependent enhancement (preprint)

Recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the ongoing coronavirus disease 2019 (COVID-19) pandemic. Currently, there is no vaccine available for preventing SARS-CoV-2 infection. Like closely related severe acute respiratory syndrome coronavirus (SARS-CoV), SARS-CoV-2 also uses its receptor-binding domain (RBD) on the spike (S) protein to engage the host receptor, human angiotensin-converting enzyme 2 (ACE2), facilitating subsequent viral entry. Here we report the immunogenicity and vaccine potential of SARS-CoV-2 RBD (SARS2-RBD)-based recombinant proteins. Immunization with SARS2-RBD recombinant proteins potently induced a multi-functional antibody response in mice. The resulting antisera could efficiently block the interaction between SARS2-RBD and ACE2, inhibit S-mediated cell-cell fusion, and neutralize both SARS-CoV-2 pseudovirus entry and authentic SARS-CoV-2 infection. In addition, the anti-RBD sera also exhibited cross binding, ACE2-blockade, and neutralization effects towards SARS-CoV. More importantly, we found that the anti-RBD sera did not promote antibody-dependent enhancement of either SARS-CoV-2 pseudovirus entry or authentic virus infection of Fc receptor-bearing cells. These findings provide a solid foundation for developing RBD-based subunit vaccines for SARS-CoV2.

Integrated approaches for COVID-19 case finding and their impact on timeliness for disease containment in Changning District, Shanghai, China (preprint)

The authors have removed this preprint from Research Square.