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Since December 2019, the COVID-19 epidemic has been spreading continuously in China and many countries in the world, causing widespread concern among the whole society. To cope with the epidemic disaster, most provinces and cities in China have adopted prevention and control measures such as home isolation, blocking transportation, and extending the Spring Festival holiday, which has caused a serious impact on China's output of various sectors, international trade, and labor employment, ultimately generating great losses to the Chinese economic system in 2020. But how big is the loss? How can we assess this for a country? At present, there are few analyses based on quantitative models to answer these important questions. In the following, we describe a quantitative-based approach of assessing the potential impact of the COVID-19 epidemic on the economic system and the sectors taking China as the base case. The proposed approach can provide timely data and quantitative tools to support the complex decision-making process that government agencies (and the private sector) need to manage to respond to this tragic epidemic and maintain stable economic development. Based on the available data, this article proposes a hypothetical scenario and then adopts the Computable General Equilibrium (CGE) model to calculate the comprehensive economic losses of the epidemic from the aspects of the direct shock on the output of seriously affected sectors, international trade, and labor force. The empirical results show that assuming a GDP growth rate of 4-8% in the absence of COVID-19, GDP growth in 2020 would be -8.77 to -12.77% after the COVID-19. Companies and activities associated with transportation and service sectors are among the most impacted, and companies and supply chains related to the manufacturing subsector lead the economic losses. Finally, according to the calculation results, the corresponding countermeasures and suggestions are put forward: disaster recovery for key sectors such as the labor force, transportation sector, and service sectors should be enhanced; disaster emergency rescue work in highly sensitive sectors should be carried out; in the long run, precise measures to strengthen the refined management of disaster risk with big data resources and means should be taken., (© 2021 Society for Risk Analysis.)

Background: and Purpose: Increasingly frequent meteorological disasters have brought severe challenges that should be urgently handled in the sustainable development. However, meteorological data, loss data, social economic data and so forth relating to meteorological disasters rarely be effectively fused, failing to generate, rapidly and efficiently, economic losses and thus hindering the emergency management of disasters., Methods: A new economic losses evaluation information system has been developed for monitoring severe rainfall and flooding disasters in cities. The data mining method, econometric regression model and input-output model are implemented in the system, on the basis of multi-source data including hourly rainfall, geographical conditions, historical and real-time disaster information, socioeconomic data, and defense countermeasure., Results: Combined with the weather forecast information, this system can has the capability for reporting the real-time direct and indirect economic losses incurred by urban heavy rainfall and flooding disasters, automatically generating defense countermeasure reports for typical rainstorm and flooding points, and providing the spatial distribution of disasters., Conclusions: Finally, the system is conducive to improving the ability to manage disaster emergencies and eventually reducing the economic losses from the disaster., (Copyright © 2020 Elsevier Inc. All rights reserved.)