A game theory-based COVID-19 close contact detecting method with edge computing collaboration.

People all throughout the world have suffered from the COVID-19 pandemic. People can be infected after brief contact, so how to assess the risk of infection for everyone effectively is a tricky challenge. In view of this challenge, the combination of wireless networks with edge computing provides new possibilities for solving the COVID-19 prevention problem. With this observation, this paper proposed a game theory-based COVID-19 close contact detecting method with edge computing collaboration, named GCDM. The GCDM method is an efficient method for detecting COVID-19 close contact infection with users' location information. With the help of edge computing's feature, the GCDM can deal with the detecting requirements of computing and storage and relieve the user privacy problem. Technically, as the game reaches equilibrium, the GCDM method can maximize close contact detection completion rate while minimizing the latency and cost of the evaluation process in a decentralized manner. The GCDM is described in detail and the performance of GCDM is analyzed theoretically. Extensive experiments were conducted and experimental results demonstrate the superior performance of GCDM over other three representative methods through comprehensive analysis.

Comparison of Predictors of COVID-19 Vaccination Intention Between Healthcare Workers and Non-Healthcare Workers in China.

BACKGROUND: Vaccination is an effective strategy to mitigate the spread of COVID-19. This study aimed to compare predictors of vaccination intention between healthcare workers (HCWs) and non-healthcare workers (non-HCWs) in China. METHODS: A web-based cross-sectional survey was conducted among HCWs and non-HCWs. Several bivariate analysis techniques, eg, crosstab with Chi-square, independent t-test and single factor ANOVA, were performed to analyze the correlation. After that, a series of multivariate binary regressions were employed to determine predictors of vaccination intention. RESULTS: Intention was closely and significantly related with gender, perceived vaccination knowledge, perceived importance and effectiveness of vaccine to prevent COVID-19. HCWs and non-HCWs were heterogeneous, since vaccination intention, perceived knowledge, and attitudes (eg, importance, severity, risk) toward COVID-19 or vaccine had statistically significant difference between the two groups. With comparison of predictors of vaccination intention, for HCWs, demographic factors were the major predictors of COVID-19 vaccination intention. Female HCWs and HCWs with a Master's or higher degree were more hesitant about vaccination (P = 0.01 and P < 0.001, respectively), while HCWs had greater vaccination intention as their age increased (P = 0.02). For non-HCWs, perceived vaccination knowledge was the major predictor of COVID-19 vaccination intention (P < 0.001). Additionally, perceived importance and effectiveness of vaccine were predictors for both HCWs and non-HCWs. CONCLUSION: Vaccination intention of HCWs was greater than that of non-HCWs in China. Measures should be taken to improve the vaccination rate based on the predictors of vaccination intention identified in this study. For HCWs, especially those with a high level of education or who were females, the safety and effectiveness of vaccines in use may reinforce their vaccination intention. For non-HCWs, popularization of general medical knowledge, including of vaccine-preventable diseases, may increase their vaccination intention.