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In the face of the severe situation of epidemic prevention and control and the arduous task of social management, the tremendous power of science and technology in prevention and control has emerged. The new generation of information technology, represented by big data and artificial intelligence (AI) technology, has been widely used in the prevention, diagnosis, treatment and management of COVID-19 as an important basic support. Although the technology has developed, there are still challenges with respect to epidemic surveillance, accurate prevention and control, effective diagnosis and treatment, and timely judgement. The prevention and control of sudden infectious diseases usually depend on the control of infection sources, interruption of transmission channels and vaccine development. Big data and AI are effective technologies to identify the source of infection and have an irreplaceable role in distinguishing close contacts and suspicious populations. Advanced computational analysis is beneficial to accelerate the speed of vaccine research and development and to improve the quality of vaccines. AI provides support in automatically processing relevant data from medical images and clinical features, tests and examination findings; predicting disease progression and prognosis; and even recommending treatment plans and strategies. This paper reviews the application of big data and AI in the COVID-19 prevention, diagnosis, treatment and management decisions in China to explain how to apply big data and AI technology to address the common problems in the COVID-19 pandemic. Although the findings regarding the application of big data and AI technologies in sudden public health events lack validation of repeatability and universality, current studies in China have shown that the application of big data and AI is feasible in response to the COVID-19 pandemic. These studies concluded that the application of big data and AI technology can contribute to prevention, diagnosis, treatment and management decision making regarding sudden public health events in the future.<\/jats:p>","DOI":"10.1007\/s10916-021-01757-0","type":"journal-article","created":{"date-parts":[[2021,7,24]],"date-time":"2021-07-24T11:02:41Z","timestamp":1627124561000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":64,"title":["Application of Big Data and Artificial Intelligence in COVID-19 Prevention, Diagnosis, Treatment and Management Decisions in China"],"prefix":"10.1007","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9646-2853","authenticated-orcid":false,"given":"Jiancheng","family":"Dong","sequence":"first","affiliation":[]},{"given":"Huiqun","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Dong","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Kaixiang","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yuanpeng","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Hanzhen","family":"Ji","sequence":"additional","affiliation":[]},{"given":"Zhuang","family":"Tong","sequence":"additional","affiliation":[]},{"given":"Shuai","family":"Lou","sequence":"additional","affiliation":[]},{"given":"Zhangsuo","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,7,24]]},"reference":[{"key":"1757_CR1","unstructured":"WHO. 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