The epidemic of novel coronavirus (COVID-19) has exhibited the decline trend with the enhanced containment and mitigation strategies. However, the resumption of work and reproduction, and the increasingly serious epidemic situation in other countries have brought severe challenges to face domestic non-proliferation and external input, in order to ensure the success of the prevention and control of the epidemic. Therefore, the execution and compliance of mitigation strategies will become the key factors that affecting the development of COVID-19 epidemic during late epidemic stage. By proposing a mathematical model that can describe the execution of decision makers and compliance of individuals, and integrating multi-source data, the impact of execution and compliance on the effective reproduction number and cumulative confirmed cases is analyzed. This improves people's understanding of the important role of execution and compliance of epidemic mitigation strategies, and serves the decision-making of resumption of work and prevention and control strategies.

With the global prevalence of coronavirus disease 2019 (COVID-19), the development of anti-COVID-19 drugs is becoming more and more urgent. As there are no specific drugs available for COVID-19 currently, “new use of old drugs” has become one of the main anti-epidemic strategies adopted by many research institutions at home and abroad. On the basis of analyzing COVID-19 characteristics, infection mechanism and the similarities of SARS-CoV-2 (the pathogen of COVID-19) with SARS-CoV and other related RNA viruses, the antiviral drugs and therapies which may be useful to treat COVID-19 were analyzed and summarized, including virus-targeted drugs, host-targeted drugs, herbal medicine, stem cell therapy and RNAi therapy. The specific action mechanism of relevant drugs and therapies as well as their current application status in the treatment of COVID-19 were mainly elucidated, so as to provide certain reference for the development of effective drugs and treatment methods for COVID-19.

The outbreak of COVID-19 at the end of 2019 is spreading around the world, causing serious impact on socio-economic development and human health and safety. Clarification of the spatial-temporal spread of COVID-19 at individual and population levels is necessary for epidemic prevention and control as well as resource allocation. This study targeted on Shenzhen city which locates far away from the COVID-19 origin city of Wuhan but experienced high incidence of COVID-19. Based on the officially published and confirmed cases, manually collected case details and the related POI data of Shenzhen, the epidemiological characteristics, spatio-temporal evolution and prevention and control measures regarding COVID-19 in Shenzhen were analyzed through text analysis, mathematical statistics, spatial analysis and other methods. The results showed that: (1)the confirmed COVID-19 cases covered all age levels, mainly concentrated in the young adults. Most of them were the second generation of infection originating from the places out of Shenzhen, and they were mainly from family cluster transmission with “linear” migration and diffusion mode between cities. (2)The time evolution of epidemic experienced 4 stages: low incidence period, growing period, deceleration period and ending period. The number of cured cases presented the evolution process from slow growth to rapid growth. The time interval from onset to admission was mostly within 0~2 days, and the time interval from admission to diagnosis was about 1~3 days. (3)In terms of spatial distribution, the confirmed cases moved out mainly through two types: “directly from Hubei” and “stop by Hubei”, with the main purpose of visiting relatives during the Spring Festival. The spatial distribution of COVID-19 affected communities demonstrated “northeast to southwest” trend, mainly gathered in the southwest part around the “two cores”.(4)The overall risk distribution of the city was “two cores and three areas”. The high-risk areas were located in the south of Nanshan District and in the center of Futian District. Finally, combined with the situation of COVID-19, requirement of work recovery and the new risk from overseas, this study put forward an accurate prevention and control measure system based on the dimensions of “real-time, daily, normal”, “community, district, city” and “individual,family,society” from the perspective of “time-space-human” mutual feedback and integration.

The data of confirmed cases, death cases and cured cases of coronavirus disease 2019 (COVID-19) in seven epidemic seriously affected countries (Italy, South Korea, the United Kingdom, the United States, France, Spain, Germany) were obtained from the System Science and Engineering Center at Johns Hopkins University. Data were collected between March 4, 2020 and April 4, 2020. Traditional SIR model was used and improved by adding a new parameter to characterize the infection coefficient changes over time, and regression analysis was introduced to estimate the parameters. Based on the improved SIR model, the development of COVID-19 in 7 countries were simulated and predicted, and the effects of contact rate control measures of different countries on epidemic development were analyzed. Results showed that the improved SIR model was reliable for analyzing the epidemic trend of COVID-19. Apart from the United Kingdom and the United States, the other five countries have had their pandemic under initial control, while the United Kingdom and the United States need to do more to reduce the pandemic damage. Our finding confirmed the importance of reducing population contact rate in COVID-19 prevention and control, such as reducing assembly, avoiding contact and centralized admission, so as to provide reference for the subsequent epidemic prevention and control.