Background and Purpose The coronavirus disease 2019 (COVID-19) pandemic presents an unprecedented health crisis to the entire world. As reported, the body mass index (BMI) may play an important role in COVID-19; however, this still remains unclear. The aim of this study was to explore the association between BMI and COVID-19 severity and mortality. Methods The Medline, PubMed, Embase and Web of science were systematically searched until August 2020. Random-effects models and dose-response meta-analysis were used to synthesize the results. Combined odds ratios (ORs) with their 95% confidence intervals (CIs) were calculated, and the effect of covariates were analyzed using subgroup analysis and meta-regression analyses. Results A total of 16 observational studies involving 109,881 patients with COVID-19 were included in the meta-analysis. The pooled results showed that patients with a BMI≥30kg/m 2 had a 2.35-fold risk(OR = 2.35, 95%CI = 1.64 − 3.38, P < 0.001) for critical COVID-19 and a 2.68-fold risk for COVID-19 mortality (OR = 2.68, 95%CI = 1.65 −4.37, P < 0.001 ) compared with patients with a BMI <30kg/m 2 . Subgroup analysis results showed that patients with obesity and age > 60 years was associated with a significantly increased risk of critical COVID-19(OR = 3.11, 95%CI = 1.73 − 5.61, P < 0.001) and COVID-19 mortality(OR = 3.93, 95%CI = 2.18 − 7.09, P < 0.001). Meta-regression analysis results also showed that age had a significant influence on the association between BMI and COVID-19 mortality(Coef.=0.036, p=0.048). Random-effects dose-response meta-analysis showed a linear association between BMI and both critical COVID-19(P non-linearity = 0.242) and mortality (P non-linearity = 0.116). The risk of critical COVID-19 and mortality increased by 9%(OR = 1.09, 95%CI = 1.04 −1.14, P < 0.001) and 6%(OR = 1.06, 95%CI = 1.02 −1.10, P = 0.002) for each 1 kg/m 2 increase in BMI, respectively. Conclusions Evidence from this meta-analysis suggested that a linear dose-response association between BMI and both COVID-19 severity and mortality. Further, obesity(BMI≥30kg/m 2 ) was associated with a significantly increased risk of critical COVID-19 and in-hospital mortality of COVID-19.

Varicella is an acute respiratory infectious diseases, with high transmissibility and quick dissemination. In this study, an SEIR (susceptible-exposed-infected-recovered) dynamic model was established to explore the optimal prevention and control measures according to the epidemiological characteristics about varicella outbreak in a school in a central city of China. Berkeley Madonna 8.3.18 and Microsoft Office Excel 2010 software were employed for the model simulation and data management, respectively. The result showed that the simulated result of SEIR model agreed well with the reported data when β (infected rate) equal to 0.067. Models showed that the cumulative number of cases was only 13 when isolation adopted when the infected individuals were identified (assuming isolation rate was up to 100%); the cumulative number of cases was only two and the TAR (total attack rate) was 0.56% when the vaccination coefficient reached 50%. The cumulative number of cases did not change significantly with the change of efficiency of ventilation and disinfection, but the peak time was delayed; when δ (vaccination coefficient) = 0.1, m (ventilation efficiency) = 0.7 or δ = 0.2, m = 0.5 or δ = 0.3, m = 0.1 or δ = 0.4 and above, the cumulative number of cases would reduce to one case and TAR would reduce to 0.28% with combined interventions. Varicella outbreak in school could be controlled through strict isolation or vaccination singly; combined interventions have been adopted when the vaccination coefficient was low.

Background: Mumps is an acute respiratory infectious disease with obvious regional and seasonal differences. Exploring the impact of climate factors on the incidence of mumps and predicting its incidence trend on this basis could effectively control the outbreak and epidemic of mumps. Methods: Considering the great differences of climate in the vast territory of China, this study divided the Chinese mainland into seven regions according to the administrative planning criteria, data of Mumps were collected from the China Disease Prevention and Control Information System, ARIMA model and ARIMAX model with meteorological factors were established to predict the incidence of mumps. Results: In this study, we found that precipitation, air pressure, temperature, and wind speed had an impact on the incidence of mumps in most regions of China and the incidence of mumps in the north and southwest China was more susceptible to climate factors. Considering meteorological factors, the average relative error of ARIMAX model was 10.87%, which was lower than ARIMA model (15.57%). Conclusions: Meteorology factors were the important factors which can affect the incidence of mumps, ARIMAX model with meteorological factors could better simulate and predict the incidence of mumps in China, which has certain reference value for the prevention and control of mumps.

Objective: Recently, ribosome binding protein 1 (RRBP1) is reported to be involved in tumorigenesis. However, the expression and clinical significance of RRBP1 in prostate cancer (PCa) remains unknown. This study is aimed to investigate the expression and clinical significance of RRBP1 in PCa. Materials and methods: RRBP1 expression was firstly detected in 6 cases of PCa and matched adjacent non-cancerous prostate tissues by reverse transcription-quantitative PCR (RT-qPCR) and Western blot. Then, RRBP1 expression was further detected in 127 cases of PCa and 40 cases of non-cancerous prostate tissues by immunohistochemistry (IHC). The relationship of RRBP1 with clinical-pathological characters and patients’ prognosis was analyzed in PCa. Results: RT-qPCR and Western blot analysis showed that RRBP1 expression levels in PCa tissues were significantly higher compared with those in matched adjacent non-cancerous prostate tissues. IHC results shown that the high-expression rate of RRBP1 in PCa was 69.3%, which was significantly greater than those in non-cancerous prostate tissues (15.0%, P <0.001). RRBP1 expression was significantly associated with T stage, lymph node metastasis, PSA and Gleason score in PCa. Survival analysis indicated that patients with RRBP1 low-expression presented longer survival time compared with those with RRBP1 high-expression. Moreover, RRBP1 as well as T stage, lymph node metastasis and Gleason score could serve as independent prognostic factors in PCa. Conclusion: RRBP1 is highly expressed in PCa and correlates with prognosis, which may serve as a potential biomarker in PCa.

No abstract