Sustainable Emergency Management Based on Intelligent Information Processing

Luo, Yi; Liu, Wei; Yue, Xiao‐Guang; Rosen, Marc A.

doi:10.3390/su12031081

Cited by 31 publications

(19 citation statements)

References 15 publications

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“…In this battle of epidemic prevention and control, Chinese universities have provided significant support and made remarkable achievements in epidemic control and social stability. The outbreak has set new requirements for sustainable risk management (Luo et al 2020). For Chinese universities, these requirements have arisen primarily in the following areas.…”

Section: Challengesmentioning

confidence: 99%

Risk Management of COVID-19 by Universities in China

Wang

Cheng

Yue

et al. 2020

JRFM

Self Cite

409

302

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The rapid spread of new coronaviruses throughout China and the world in 2019-2020 has had a great impact on China's economic and social development. As the backbone of Chinese society, Chinese universities have made significant contributions to emergency risk management. Such contributions have been made primarily in the following areas: alumni resource collection, medical rescue and emergency management, mental health maintenance, control of staff mobility, and innovation in online education models. Through the support of these methods, Chinese universities have played a positive role in the prevention and control of the epidemic situation. However, they also face the problems of alumni's economic development difficulties, the risk of deadly infection to medical rescue teams and health workers, infection of teachers and students, and the unsatisfactory application of information technology in resolving the crisis. In response to these risks and emergency problems, we propose some corresponding solutions for public dissemination, including issues related to medical security, emergency research, professional assistance, positive communication, and hierarchical information-based teaching.

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Section: Challengesmentioning

confidence: 99%

Risk Management of COVID-19 by Universities in China

Wang

Cheng

Yue

et al. 2020

JRFM

Self Cite

409

302

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“…More recently, and with reference to epidemic emergencies, Qiu et al (2018) demonstrated how an open attitude and active engagement of stakeholders to address risk information needs can build trust and facilitate collaborations, whereas Perry and Laws (2020) developed a collaborative planning and shared decision making framework for risk informed decision making in biosecurity. A number of studies have also investigated the adoption of digital technologies to enhance emergency management ( Gasmelseid, 2014 ; Luo et al, 2020 ; Misra, Roberts and Rhodes, 2020 ; Yang, Yang and Plotnick, 2013 ).…”

Section: Epidemic Management As Emergency Managementmentioning

confidence: 99%

Managing the COVID-19 emergency: A coordination framework to enhance response practices and actions

Margherita

Elia

Klein

2021

Technological Forecasting and Social Change

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Highlights The COVID-19 is generating disrupting impact on economies and societies Sociotechnical research can contribute with new approaches to emergency management We define a framework for modeling coordination in epidemic management process We identify 25 resource types, 8 activities and 29 flow, fit, share dependencies We show an emergency management system of practices and response actions

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“…In December 2019, a new virus outbreak occurred and has not been under complete control. Therefore, we initiated research on this new pneumonia virus to predict its duration, infections, death toll, and the impact on China's economy for risk assessment, based on intelligent information processing methods (Luo et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Risk Prediction and Assessment: Duration, Infections, and Death Toll of the COVID-19 and Its Impact on China’s Economy

Yue

Shao

et al. 2020

JRFM

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This study first analyzes the national and global infection status of the Coronavirus Disease that emerged in 2019 . It then uses the trend comparison method to predict the inflection point and Key Point of the COVID-19 virus by comparison with the severe acute respiratory syndrome (SARS) graphs, followed by using the Autoregressive Integrated Moving Average model, Autoregressive Moving Average model, Seasonal Autoregressive Integrated Moving-Average with Exogenous Regressors, and Holt Winter's Exponential Smoothing to predict infections, deaths, and GDP in China. Finally, it discusses and assesses the impact of these results. This study argues that even if the risks and impacts of the epidemic are significant, China's economy will continue to maintain steady development.

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Sustainable Emergency Management Based on Intelligent Information Processing

Cited by 31 publications

References 15 publications

Risk Management of COVID-19 by Universities in China

Risk Management of COVID-19 by Universities in China

Managing the COVID-19 emergency: A coordination framework to enhance response practices and actions

Risk Prediction and Assessment: Duration, Infections, and Death Toll of the COVID-19 and Its Impact on China’s Economy

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