First Imported Case of SARS-CoV-2 Omicron Subvariant BA.5—Shanghai Municipality,China,May 13,2022

On April 27,2022,an international flight KL857 from Amsterdam,the Netherlands arrived at Pudong International Airport,Shanghai Municipality.Passengers were transferred to the quarantine hotel for a routine 14-day medical observation in Songjiang District and regularly tested for severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).One of the passengers(a 37-year-old Chinese male)was reported positive and diagnosed as a mild case on April 29.The case set out from Uganda(flight KL535)on April 25 and transferred at Amsterdam,the Netherlands on April 26 and Seoul,the Republic of Korea(KL857)on April 27.The patient has been vaccinated in four doses against coronavirus disease 2019(COVID-19)(Beijing Institute of Biological Products Co.,Ltd)in China and Uganda.After diagnosis,he was transferred to Shanghai Public Health Clinical Center for treatment.He recovered after treatment and was discharged on May 12.

Antibody Response to COVID-19 Virus--Heilongjiang Province and Gansu Province,China,2020

What is already known about this topic?Coronavirus disease 2019(COVID-19)has become a global pandemic,while the profile of antibody response against the COVID-19 virus has not been well clarified.What is added by this report?In this study,210 serum samples from 160 confirmed COVID-19 cases with different disease severities were recruited.The IgM,IgA,IgG,and neutralizing antibodies(NAb)against COVID-19 virus were determined.Our findings indicated that four antibodies could be detectable at low levels within 2 weeks of disease onset,then rapidly increasing and peaking from the 3^(rd) to 5^(th) Weeks.NAb decreased between 5^(th) and 9^(th) Weeks,and a higher IgM/IgA level was observed in the groups with mild/moderate severity within 2 weeks(p<0.05),while all 4 types of antibodies were higher in the group with severe/critical severity after 4 weeks(p<0.05).What are the implications for public health practice?Our study on the dynamics of serological antibody responses against COVID-19 virus among COVID-19 patients complements the recognition regarding the humoral immune response to COVID-19 virus infection.The findings will help in the interpretation of antibody detection results for COVID-19 patients and be beneficial for the evaluation of vaccination effects.

A New Hybrid Machine Learning Model for Short-Term Climate Prediction by Performing Classification Prediction and Regression Prediction Simultaneously

Machine learning methods are effective tools for improving short-term climate prediction.However,commonly used methods often carry out classification and regression prediction modeling separately and independently.Such a single modeling approach may obtain inconsistent prediction results in classification and regression and thus may not meet the needs of practical applications well.To address this issue,this study proposes a selective Naive Bayes ensemble model(SENB-EM)by introducing causal effect and voting strategy on Naive Bayes.The new model can not only screen effective predictors but also perform classification and regression prediction simultaneously.After being applied to the area prediction of summer western North Pacific subtropical high(WNPSH)from 2008 to 2021,it is found that the accuracy classification score(a metric to assess the overall classification prediction accuracy)and the time correlation coefficient(TCC)of SENB-EM can reach 1.0 and 0.81,respectively.After integrating the results of different models[including multiple linear regression ensemble model(MLR-EM),SENB-EM,and Chinese Multimodel Ensemble Prediction System(CMME)used by National Climate Center(NCC)]for 2017-2021,the TCC of the ensemble results of SENB-EM and CMME can reach 0.92(the highest result among them).This indicates that the prediction results of the summer WNPSH area provided by SENB-EM have a high reference value for the real-time prediction.It is worth noting that,except for the numerical prediction results,the SENB-EM model can also give the range of numerical prediction intervals and predictions for anomalous degrees of the WNPSH area,thus providing more reference information for meteorological forecasters.Overall,as a new hybrid machine learning model,the SENB-EM has a good prediction ability;the approach of performing classification prediction and regression prediction simultaneously through integration is informative to short-term climate prediction.