The Association between Obesity and Severity in Patients with Coronavirus Disease 2019: a Retrospective, Single-center Study, Wuhan.

Aim: In other respiratory infectious diseases, obesity may be associated with a poor outcome. For coronavirus disease 2019 (COVID-19), the association between obesity and severity or prognosis requires further analysis. Methods: This was a retrospective, single-center study. Hospitalized patients were recruited in Renmin Hospital of Wuhan University from January 2, 2020 to February 20, 2020. The data of body mass index (BMI) was obtained from follow-up of surviving patients. According to BMI, normal weight was defined as 18.5-23.9 kg/m2, overweight as 24.0-27.9 kg/m2 and obesity as > 28.0 kg/m2. Results: A total of 463 patients were enrolled, of which 242 (52.3%) patients were in the normal weight group; 179 (38.7%) were in the overweight group; and 42 (9.1%) were in the obesity group. Compared to the normal group, obese patients were more likely to have a higher heart rate; lower finger oxygen saturation; higher levels of white blood cells, neutrophil counts, basophil counts, intravenous glucose, triacylglycerol, uric acid, alanine aminotransferase, creatine kinase-MB, CD19+ cell counts and percentage; and lower levels of monocyte percentage, high density lipoprotein and CD3+ cell percentage. In addition, the proportions of hypertension (21.5% vs. 42.6%) and severe+critical illness (47.8 vs. 81.0 %) were significantly higher in the obesity group than those in normal group. However, no significant differences were observed between the normal and obesity groups in critical illness, organ damage and defined endpoint (mechanical ventilation or intensive care unit). Multiple logistic regression showed that obesity increased the risk of developing severe+critical illness (Odd ratio 3.586, 95% CI 1.550-8.298, P=0.003) in patients with COVID-19, and did not affect the risk of critical illness, organ damage and endpoints. Overweight did not affect the risk of severity, organ damage or endpoint in patients with COVID-19. Conclusion: Obesity may be a risk factor for developing severity in patients with COVID-19.

An analysis of the domestic resumption of social production and life under the COVID-19 epidemic.

Population migration and urban traffic are two important aspects of the socioeconomic system. We analyze the trends of social production and resumption of life after the coronavirus disease 2019 (COVID-19)-influenced Spring Festival in 2020 with statistics on reported cases of COVID-19 from China's National Health Commission and big data from Baidu Migration (a platform collecting population migration data). We find that (1) the distribution of COVID-19 cases throughout mainland China has a specific spatial pattern. Provinces in eastern China have more reported cases than those in western China, and provinces adjacent to Hubei have more confirmed COVID-19 cases than nonadjacent provinces. Densely populated regions with well-developed economies and transportation are more likely to have cluster infection incidents. (2) The COVID-19 epidemic severely impacts the return of the migrant population in the Spring Festival travel rush, as demonstrated by the significant reduction in the return scale, along with the extended timespan and uncertainty regarding the end of the travel rush. Among 33 provinces, special administrative regions, autonomous regions and municipalities, 23 of them (approximately 70%) have a return rate below 60%. Hubei, Hong Kong, Xinjiang, and Inner Mongolia have the lowest return rates (below 5%), whereas the return rates in Hainan and Shandong, 272.72% and 97.35%, respectively, indicate the best trend of resumption. Due to government regulations, the population return in densely populated and well-developed regions shows a positive trend. (3) The resumption of urban traffic is slow and varies greatly in different regions. The urban traffic conditions in 22 provinces and municipalities have a more than 60% level of resumption. Guizhou and Yunnan have the highest level of resumption of urban traffic, whereas Xinjiang, Hubei, and Heilongjiang have the lowest (29.37%, 35.76%, and 37.90%, respectively). However, provinces and municipalities with well-developed intercity traffic have a lower level of resumption, mainly because of regulatory methods such as lockdowns and traffic restrictions. The increased public awareness of epidemic prevention and the decreased frequency of outdoor activities are also two positive factors slowing the spread of the epidemic. (4) Time will be necessary to fully resume social production and life throughout China. Xining and Jinan have the highest levels of resumption, 82.14% and 71.51%, respectively. Urumqi and Wuhan are the cities with the lowest levels of resumption, only 0.11% and 0.61%, respectively. Currently, 12 of 33 provinces and municipalities have levels of resumption of more than 80%; among them, Guizhou, Yunnan, and Gansu have with the highest levels of resumption and have nearly resumed the 2019 levels of work and life, whereas Xinjiang and Hubei have the lowest resumption rates, only 0.09% and 7.57%, respectively. Thus, relevant government departments should focus more on densely populated and well-developed provinces and cities when applying epidemic prevention and work resumption methods. We reveal the general conditions of the epidemic and the population return scale across China, along with urban traffic conditions and the resumption of social production and life under COVID-19, providing a scientific basis for local governments to make further decisions on work resumption.