Risk assessment of global COVID-19 pandemic in October 2022

Objective: To assess the global epidemic of Coronavirus disease 2019(COVID-19) in October 2022 and the risk of importation.

Research on Credit Assessment and Prediction Based on Deep Learning

The huge pressure of market demand and competitive environment makes supply chain finance the choice of most enterprises. The emergence of public health emergencies such as the COVID-19 epidemic has made it particularly urgent to improve the risk management capabilities of the pharmaceutical industry's supply chain in a transitional period. In-depth exploration of the key factors affecting the financial credit risk of pharmaceutical companies' supply chain, and the construction of a high-accuracy forecast model is of great significance to the stability of the macroeconomy. Combining the characteristics of the pharmaceutical manufacturing industry, this paper builds a financial credit risk assessment system for the pharmaceutical supply chain. On the basis of Factor Analysis and Random Forest variable screening, the AdaBoost algorithm is used to build the prediction model. By comparing basic machine learning models such as SVM model, decision tree, logistic regression, Bayesian classifier, BP neural network, and integrated learning models such as Random Forest, Bagging meta-estimator, GBM, and XGBoost, the study found that the AdaBoost model has higher accuracy. And through the data forecast in 2020, the superiority and effectiveness of the model for credit risk assessment in the pharmaceutical industry are further verified. According to the prediction results, this paper finds that the epidemic has no obvious negative impact on pharmaceutical manufacturing enterprises and proposes suggestions from the perspectives of the government and enterprises for reference. © 2022 SPIE.

Security strategy of large general hospitals in the context of COVID-19 epidemic prevention and control

Coronavirus disease 2019 (COVID-19), characterized by high infectivity and invisibility, has spread quickly throughout the world and brought great challenges to hospital security work. Regarding the medical service reality of large general hospitals, the Security Department actively responded to the epidemic prevention and control work. They classified the risk areas in the hospital and formulated corresponding security strategies. Current paper summarize the improvement of the existing security management and control system, the management level of major public health emergencies and the emergency management. Then the control measures for scientific deployment of personnel and proper planning of the diagnosis and treatment process of risk patients during the epidemic are discussed. This study aimed to provide helpful reference for ensuring the stability of medical reception order in large general hospitals under COVID-19 epidemic. Copyright © 2022, Editorial Board of Journal of Xi'an Jiaotong University (Medical Sciences). All right reserved.