An allocation model for emergency medical services based on integrated healthcare during an epidemic

Enhanced virus control and patient treatment outcomes during an epidemic requires flexible and efficient medical services. This research explores an epidemic medical service allocation model from an integrated healthcare perspective, aiming to enhance the overall regional emergency medical service capability based on collaborative medical treatment. The study is based on COVID-19 medical services and its main treatment stages, and resource allocation models are constructed for the allocation of multiple medical services. The model addresses the dispersed medical service resources and demands in a certain region, and realizes the division of labor and resource sharing among medical institutions from the perspectives of distance, cost, and fairness with the advantage of integrated healthcare. We design examples in the context of COVID-19 epidemic and verify the validity and applicability of the model under different phases. This paper provides reference to the research and practice of achieving collaborative medical treatment between multiple medical institutions.

Understanding the antecedents of mobile social media acceptance during the public health crisis maintenance stage

Mobile social media experienced explosive growth during the COVID-19 pandemic. To understand the underlying causes of users' acceptance towards mobile social media, this study draws upon the uses and gratifications theory, media dependency theory, and related literature of individuals' perceived appraisal (perceived trust, perceived benefits, and perceived risk) to explore the determinants that influenced mobile social media acceptance during the public health crisis maintenance stage. Data were obtained from 724 mobile social media users in China through an online paid questionnaire survey platform. The results revealed that perceived trust and perceived benefits positively affected information seeking and information sharing, which jointly influenced an individual's intention to use mobile social media during the public health crisis maintenance stage. Social media dependency also positively affected mobile social media users' usage intentions. However, perceived risk negatively influenced information seeking and information sharing. The results of this study offer valuable theoretical and practical implications for crisis communication researchers, emergency management practitioners, and mobile social media platforms.

Establishment of epidemic early warning index system and optimization of infectious disease model: Analysis on monitoring data of public health emergencies.

The ability to mitigate the damages caused by emergencies is an important symbol of the modernization of an emergency capability. When responding to emergencies, government agencies and decision makers need more information sources to estimate the possible evolution of the disaster in a more efficient manner. In this paper, an optimization model for predicting the dynamic evolution of COVID-19 is presented by combining the propagation algorithm of system dynamics with the warning indicators. By adding new parameters and taking the country as the research object, the epidemic situation in countries such as China, Japan, Korea, the United States and the United Kingdom was simulated and predicted, the impact of prevention and control measures such as effective contact coefficient on the epidemic situation was analyzed, and the effective contact coefficient of the country was analyzed. The paper strives to provide early warning of emergencies scientifically and effectively through the combination of these two technologies, and put forward feasible references for the implementation of various countermeasures. Judging from the conclusion, this study reaffirmed the importance of responding quickly to public health emergencies and formulating prevention and control policies to reduce population exposure and prevent the spread of the pandemic.