Application of Big Data and Artificial Intelligence in COVID-19 Prevention, Diagnosis, Treatment and Management Decisions in China

Abstract

COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spread rapidly and affected most of the world since its outbreak in Wuhan, China, which presents a major challenge to the emergency response mechanism for sudden public health events and epidemic prevention and control in all countries. 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.

Keywords: Artificial intelligence; Big data; COVID-19; Deep learning; Epidemic prevention and control.

Fig. 1

Diagram of summarized domains in COVID-19 pandemic prevention and control in China

Fig. 2

The definition of populations represented by different colour health codes. A: Red code: including confirmed cases, suspected cases, asymptomatic cases, persons who had close contact with confirmed cases, and persons under medical observation. B: Yellow code: including fellow travellers who have no close contact with confirmed cases, persons registered in fever clinics, persons with discomfort such as fever, fatigue, cough, diarrhoea and conjunctival congestion or persons who left a high-risk epidemic area in the past 14 days. C: Green code: indicating that the health status of the holder is basically normal, without discomfort, and that they are allowed to move around and resume work and production.

Fig. 3

The nomogram prediction results of three different severe cases by the COVID-19 model developed by Zhong’s team [33]