SIR model analysis and short-term prediction of epidemic progress of corona virus disease 2019 in China

Objective: To predict the short-term progress of corona virus disease 2019(COVID-19) and evaluate the degree of population control among different provinces.

Evaluation of Lung Involvement in COVID-19 Pneumonia Based on Ultrasound Images (preprint)

Background: Lung ultrasound (LUS) can be an important imaging tool for the diagnosis and assessment of lung involvement. Ultrasound sonograms have been confirmed to illustrate damage to a person’s lungs, which means that the correct classification and scoring of a patient’s sonogram can be used to assess lung involvement. Methods: : The purpose of this study was to establish a lung involvement assessment model based on deep learning. A novel multimodal channel and receptive field attention network combined with ResNeXt (MCRFNet) was proposed to classify sonograms, and the network can automatically fuse shallow features and determine the importance of different channels and respective fields. Finally, sonogram classes were transformed into scores to evaluate lung involvement from the initial diagnosis to rehabilitation. Results: and conclusion: Using multicenter and multimodal ultrasound data from 104 patients, the diagnostic model achieved 94.39% accuracy, 82.28% precision, 76.27% sensitivity, and 96.44% specificity. The lung involvement severity and the trend of COVID-19 pneumonia were evaluated quantitatively.

Evaluation of Lung Involvement in COVID-19 Pneumonia Based on Ultrasound Images (preprint)

Background: Lung ultrasound (LUS) can be an important imaging tool for the diagnosis and assessment of lung involvement. In this study, we determined the ultrasound manifestations of the lung associated with COVID-19 pneumonia, and obtained the ultrasound image changes of the patients from the initial diagnosis to rehabilitation. Methods: The purpose of this study is to establish a lung involvement assessment model based on deep learning. A channel attention classification method based on squeeze-and-excitation network combining with ResNeXt (SE_ResNeXt) is proposed, which can automatically learn the importance of different channel features, so as to achieve selective learning of channels and further achieve more accurate classification results. Results and conclusion: Among 104 patients' data from multicenter and multi-mode ultrasound, the diagnostic model can achieve 97.11% accuracy. The lung involvement severity of COVID-19 pneumonia and the trend of lesion were evaluated quantitatively.

Implications of the reverse associations between obesity prevalence and coronavirus disease (COVID-19) cases and related deaths in the United States (preprint)

The Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that was most recently discovered, quickly evolved into a global pandemic. Studies suggested that obesity was a major risk factor for its hospitalization and severity of symptoms. This study investigated the associations between obesity prevalence with overall COVID-19 cases and related deaths across states in the United States. General regression and Chi-square tests were used to examine those associations. The analyses indicated that obesity prevalence (%) across states were negatively associated with COVID-19 cases (p = 0.0448) and related deaths (p = 0.0181), with a decrease of 158 cases/100K population and 13 deaths/100K for every 5% increase of the obesity prevalence. When the states were divided based on the median of obesity prevalence (30.9%) into a group of states with low obesity prevalence and a group with high obesity prevalence, both the cases (671 vs 416 cases/100k population) and deaths (39 vs 21 deaths/100k population) were significantly different (p < 0.001) across groups. These findings provided important information for the relationship between the dual pandemic threats of obesity and COVID-19. These results should not currently be considered as an indication that obesity is a protective factor for COVID-19, and would rather be used as a warning of the public advice that obese people is more vulnerable to COVID-19 infection, which may lead to a false safety message probably given to people with normal body weight.

Sunlight and vitamin D in the prevention of coronavirus disease (COVID-19) infection and mortality in the United States (preprint)

The coronavirus disease (COVID-19) is an infectious disease caused by the most recently discovered coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study aims to investigate associations between sunlight and vitamin D, using latitude as an indicator, with COVID-19 cases and related deaths in the United States. General regression and Chi-square test were used to examine the associations between latitude and COVID-19 cases and deaths. The analyses indicated that latitudes were marginally associated with cases (p = 0.0792) and deaths (p = 0.0599), with an increase of 2491 cases and 189 deaths of the total numbers in the mainland of US for every unit of increase of the latitude. When the states were classified into high latitude (>N 370) and low latitude (<N 370) groups, both the cases (702 vs 255 cases/100k population) and deaths (43 vs 11 deaths/100k population) were significantly different (p < 0.001) between the two categories. The results suggested that sunlight and vitamin D, with latitude as an indicator, might be associated with decreased risks for both COVID-19 cases and deaths. These findings warranted urgent needs of large cohort, clinical and pre-clinical studies to assess the impact of VD on the prevention of COVID-19. 

Aveolar Macrophage Activation and Cytokine Storm in the Pathogenesis of Severe COVID-19 (preprint)

The coronavirus disease-19 (COVID-19) caused by SARS-CoV-2 infection can lead to a series of clinical settings from non-symptomatic viral carriers/spreaders to severe illness characterized by acute respiratory distress syndrome (ARDS)1,2. A sizable part of patients with COVID-19 have mild clinical symptoms at the early stage of infection, but the disease progression may become quite rapid in the later stage with ARDS as the common manifestation and followed by critical multiple organ failure, causing a high mortality rate of 7-10% in the elderly population with underlying chronic disease1-3. The pathological investigation in the lungs and other organs of fatal cases is fundamental for the mechanistic understanding of severe COVID-19 and the development of specific therapy in these cases. Gross anatomy and molecular markers allowed us to identify, in two fatal patients subject to necropsy, the main pathological features such as exudation and hemorrhage, epithelium injuries, infiltration of macrophages and fibrosis in the lungs. The mucous plug with fibrinous exudate in the alveoli and the activation of alveolar macrophages were characteristic abnormalities. These findings shed new insights into the pathogenesis of COVID-19 and justify the use of interleukin 6 (IL6) receptor antagonists and convalescent plasma with neutralizing antibodies against SARS-CoV-2 for severe patients.Authors Chaofu Wang, Jing Xie, Lei Zhao, Xiaochun Fei, Heng Zhang, and Yun Tan contributed equally to this work. Authors Chaofu Wang, Jun Cai, Rong Chen, Zhengli Shi, and Xiuwu Bian jointly supervised this work.