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Clinical research reports serve as the presentation of scientific research findings and directly reflect the quality of the research. This article describes the writing of different types of clinical research reports， such as observational studies and randomized controlled trial studies， with a particular focus on randomized controlled trials. Each scientific research design has its reporting focus， and the writing of scientific research papers has uniform requirements and a specific writing format. Mastering the proper format of drafting research reports is of practical value and significant importance for conduction high-quality clinical research.

ObjectiveTo determine the influence of COVID-19 prevention and control on the epidemic characteristics and dynamics of notifiable infectious diseases in the first quarters， Zhejiang Province， and to explore more effective countermeasures against infectious diseases.MethodsDescriptive epidemiology was conducted to determine the change in notifiable infectious diseases during the prevention and control of COVID-19 in Zhejiang Province by retrieving the data of notifiable infectious diseases from 2017 to 2022 in the Chinese information system for disease control and prevention. Cumulative reported new cases of notifiable infectious diseases in the first quarters of 2017‒2019 were compared with that of 2020‒2022.ResultsA total of 546 753 cases of notifiable infectious diseases were newly reported in the first quarters of 2017‒2019， with an average incidence of 321.92/105. In contrast， a total of 509 908 cases of notifiable infectious diseases were newly reported in the first quarters of 2020‒2022， during which the COVID-19 epidemic occurred， with an average incidence of 270.39/105. The incidence in 2020‒2022 significantly declined by 51.53/105， compared with that in 2017‒2019 （χ²=8 072.06， P

ObjectiveTo compare the annual and age trends of the age-standard incidence rate （ASIR） and the age-standard mortality rate （ASMR） of lung cancer in countries with different human development index （HDI） from 1990 to 2019.MethodsThe data were collected from the global burden of disease study and GLOBOCAN 2020. The average annual percentage change （AAPC） and age trends of ASIR and ASMR in lung cancer were analyzed by the Joinpoint regression model， and the comparison between the four groups was analyzed by Kruskale-Wallis analysis.ResultsIn 2020， the incidence and mortality of lung cancer gradually increased with age and HDI grade. From 1990 to 2019， the global ASIR and ASMR of lung cancer decreased， and the ASIR of lung cancer among male decreased， while the ASIR of lung cancer among female increased. The results showed that ASIR of lung cancer in female residents in countries with very high HDI increased significantly from 1996 to 2011， resulting in an overall upward trend in female ASIR， while the other groups showed a downward trend. It was found that ASIR and ASMR of lung cancer in China and India were on the rise， while ASIR and ASMR of lung cancer in Russia and the United States were on the decline.ConclusionAlthough very high/high HDI countries face a higher burden of lung cancer occurrence and death， the accumulation of lung cancer burden is completed in the transitioning period. Therefore， lung cancer prevention measures in countries in transition are critical for global lung cancer control.

Chronic diseases have become an important public health problem for people under 70 years of age worldwide， while also causing a great economic burden. The establishment of clinical prediction models can help to predict the risk of a disease or the prognostic effect of a study subject in advance by means of index testing at the early stage of chronic diseases， and plays an increasingly important role in clinical practice. This study introduces clinical diagnostic prediction models and clinical prognostic prediction models， and reviews clinical data processing， clinical prediction model building， visualization methods and model evaluation from the perspective of the application of clinical prediction models， which contribute to the correct and reasonable use of prediction models in clinical research.

Corona virus disease 2019 （COVID-19） has led to more than 500 million cases， including 6.19 million deaths. Mutated strains of SARS-CoV-2 （alpha， beta， gamma， delta and omicron） have successively emerged. Currently the omicron variant is gradually replacing the delta variant， driving a surge of cases in most countries including China， posing a great challenge to the prevention and treatment of COVID-19. In the face of the severe pandemic situation， a large number of non-medical volunteers are fighting on the front lines of the war against the pandemic and are vulnerable to exposure due to lack of professional knowledge. This paper introduces the routine skills training of volunteers and emergency response， aiming to provide behavioral guidance for non-medical volunteers in designated isolation facilities.

COVID-19 has emerged around the world since December 2019 and rapidly evolves as a major global public health challenge. SARS-CoV-2 is a positive single-stranded RNA virus with a relatively high natural mutation rate. The emergence of SARS-CoV-2 variants is generally considered as the outcome of a “mutation-selection-adaption” process. The enzyme APOBECs that is activated in the inflammatory microenvironment may facilitate viral mutagenesis. Currently， the major SARS-CoV-2 variants that impose public health significance are B.1.1.7， B.1.351， P.1， B.1.6.7.2， B.1.1.529 and so on， with probably increasing transmissibility， decreasing reactivity to the neutralizing antibodies， immune escape， and enhancing disease severity and mortality. Consequently， it warrants up-to-date countermeasures against evolving SARS-CoV-2， including tracing viral mutagenesis， developing vaccines against major variants， and enhancing social distancing.