Since the outbreak of the COVID-19 pandemic, the Ministry of Science and Technology, together with 13 government departments including the National Health Commission and National Medical Products Administration, has set up a scientific and technological research team under the Joint Prevention and Control mechanism of the State Council. Forty-two national emergency response projects have been deployed, while superior scientific and technological forces nationwide have been mobilized to tackle the scientific and technological issues confronting the epidemic prevention and control. As part of the aforementioned forces, Huazhong University of Science and Technology (HUST) took the lead in launching a special emergency response project to support front-line battle against COVID-19 through scientific research.

According to HUST President Li Yuanyuan, also an academician of Chinese Academy of Engineering, the university has given full play to its own advantages. Focusing on combining scientific and technological research with clinical practices and COVID-19 prevention and control, multiple batches of experts and scholars have actively involved themselves into the scientific research, contributing their wisdom and suggestions in scientific prevention and control, emergency response R&D and expert interpretation. So far, HUST has witnessed 28 scientific research units participate into anti-COVID-19 research, including 24 key teams. In terms of research direction, they mainly focus on epidemiology, rapid diagnostic detection and reagents, drug and vaccine R&D, clinical diagnosis and treatment, disease prevention and control mechanism, protective products and equipment, psychological intervention, comprehensive research on public health governance and other major scientific issues. To battle against COVID-19, the 10 hospitals affiliated with HUST have put in more than 30,000 medical staff and nearly 9,000 beds, while managing nearly 6,000 beds in the makeshift hospitals, thus being an institution contributing the largest number of beds and medical staff in China.

What achievements has HUST made in scientific and technological research?

---A rapid antibody test kit, offering results in 15 minutes with a finger-prick blood. "Preventive medicine can reduce the increment of patients, and proper disease control systems and means can flatten the curve." Jianguo Chen, Vice President of HUST and President of Tongji Medical College of HUST (HUST TMC), said that following the outbreak of the pandemic, the research team led by Professor Xiaohua Hou and Professor Rong Lin of Union Hospital of HUST TMC has developed the COVID-19 IgM/IgG antibody rapid test kit, which is mainly used to detect false negative nucleic acid tests. Through a finger-prick blood test, it takes only 15 minutes to get a result, with the efficacy rate higher than 80%. Jianguo Chen said, "The early diagnosis depends on nucleic acid, but later we find that some of the results are negative, actually 'false negative', which means it is still infectious. It can be further validated by this new antibody test kit."

---Detection of body temperature with infrared thermometer in 0.3 seconds. For days, at the gate of HUST, an infrared device has been in place to measure human temperature. In less than one second, the body temperature of people inside a vehicle several meters away is displayed on the screen. According to Professor Chen Jihong, the newest infrared thermometer device can measure temperature in 0.3 seconds; the measurement is accurate, with a tolerance of less than ±0.3℃. The measuring distance is long, up to 6 to 8 meters. Therefore, under application scenarios such as airports, high-speed trains and schools among other crowded places, it does not impact traffic flows and thus reduces the possibility of cross-infection. Moreover, the device uses facial recognition and other AI technologies to identify the targets, greatly cutting the false alarm rate. So far, more than 1,000 infrared thermometers have been used in Wuhan, Guangdong, Chongqing, Henan, Beijing and other places.

---AI-assisted medical imaging diagnosis system to provide more accurate diagnosis of COVID-19. Research team from HUST School of Electronic Information and Communications, together with Radiology Department of Union Hospital and other teams from relevant enterprises, has jointly developed a medical image quantitative analysis system assisted by Artificial Intelligence (AI) for novel coronavirus pneumonia diagnosis. Traditionally, a CT image of a patient is cut into 300 to 400 slices to be examined by naked eyes, which can take doctors more than half an hour, at the very least. However, the application of the AI-based system can reduce the detection time to a few seconds. Moreover, the system can automatically calculate the percentage of the lung lesion area by automatically separating millimeter-sized abnormalities, thus rendering a diagnosis dozens of times faster than the manual quantitative evaluation. At present, the system has been adopted in dozens of hospitals across China, with an average daily use of more than 3,000 times.

---Machine learning-based classification and early warning software for COVID-19 symptom development, which can achieve case classification and prediction in milliseconds. To classify COVID-19 cases rapidly, issue early warnings and make clinical interventions in accordance, Zhang Haitao, Yuan Ye, Cao Zhiguo, and Xiao Yang of School of Artificial Intelligence and Automation of HUST, teamed up with Yan Li, Xu Hui and Li Shusheng of Tongji Hospital of HUST TMC. They have utilized XGBoost and Softmax Neural Networks among other machine learning methods and thereby developed Pred-COVID-19, a machine learning-based classification and early warning software for COVID-19 symptom development. It can help convert the treatment of severely ill patients into pre-diagnosis based on a few key indicators, thus carrying out clinical interventions in advance. This software makes it possible to classify and predict cases in milliseconds, highly improving the efficiency of doctors" case classification and progress prediction.

---Vaccine development, immunization strategy and effect evaluation. Who needs vaccination? How to fastly develop a COVID-19 vaccine with an effective effect? Professor Fan xionglin and Professor Ouyang Zhuqing from the Department of Pathogen Biology, School of Basic Medicine of HUST TMC focused on the early and comprehensive antiviral response of the host to SARS-CoV-2. They cooperated with Professor Sun Ziyong and Professor Tao Shengce of Shanghai Jiaotong University to tackle key problems. Based on self-made proteome chip covering the 23 antigen of SARS-CoV-2, serum IgG and IgM antibody responses of 600 healthy uninfected people, 160 healthy close contacts and asymptomatic infected persons, 3104 mild, common, severe and critical cases, and 21 cases of recovered positive cases were profiled. At the same time, the research group established a lentivirus based pseudovirus neutralization antibody analysis method and evaluated the neutralization antibody levels in these different populations. They established the host's antibody responses to the virus and the interaction between the host and the virus, especially the antibody responses to virus antigen of the host during the early infection stage. They found that the neutralizing antibody was only elicited in 19% healthy close contacts and 63.5% asymptomatic infected persons and the levels were very low, which were 1:13 and 1:24 respectively, and disappeared after 2 months. Moreover, 11.8% of mild cases did not produce neutralizing antibody. According to the serological response spectrum, the target antigens of vaccines and serological diagnosis were defined. These findings provide a scientific foundation for the development of vaccines and diagnostic kits, the establishment of vaccination strategy and the evaluation of the effect of vaccines, seriological survey and public health intervention strategy.