This study aims to investigate the effects and influencing mechanisms of regular physical activity (RPA) on the COVID-19 pandemic. Daily data from 279 prefecture-level cities in mainland China were collected from 1 January to 17 March 2020. A two-way fixed-effects model was used to identify the causal relationship between physical activity and COVID-19, while also considering factors such as patterns of human behavior and socioeconomic conditions. The instrumental variable (IV) approach was applied to address potential endogeneity issues for a more accurate causal identification, and the mediating effect model was applied to examine the mechanisms of the influence of physical activity on the epidemic. We found that regular physical activity significantly improves individual immunity, which, in turn, leads to a reduction in the probability of being infected with COVID-19. Furthermore, we investigated the heterogeneity of the influence, finding that the negative impact of physical activity on the pandemic is more pronounced in the absence of adequate medical resources, strong awareness of prevention among residents, and fully implemented public health measures. Our results provide empirical evidence for the mechanisms of influence of physical activity on the pandemic. We would suggest that not only should physical activity be actively practiced during the pandemic, but also long-term regular exercise habits should be consciously cultivated to improve the ability of the individual immune system to better cope with sudden outbreaks of emerging infectious diseases.

What kind of role do sports champions play in the COVID-19 epidemic? Do they contribute to the mitigation of the epidemic by some pathway? In this paper, we empirically explore the influence and mechanism of the demonstration effect of sports champions upon the COVID-19 epidemic using COVID-19-related dataset of prefecture-level cities in China from 1 January 2020 to 17 March 2020. The two-way fixed effect model of econometrics is applied to estimate the result, the instrumental variable approach is adopted to address potential endogeneity issues, and socio-economic factors including public health measures, residents’ self-protection awareness, effective distance from Wuhan are also taken into consideration. The results show that the demonstration effect of champions in major sporting events increases the participation in physical exercise, which in turn reduces the possibility of being infected with the epidemic. An increase of one gold medal results in a 0.93% increase in the sports population, then leads to a 3.58% decrease in the cumulative case growth rate (p < 0.01). Further, we find that the effect is greater in regions with developed economies and abundant sports resources. Interestingly, it is greater in regions with less attention to sports, which again confirms the role of the demonstration effect.

With the continuous advancement of the urbanization process, the scale of cities has expanded rapidly, and the amount of floating population has grown rapidly. Big data not only brings changes in thinking, technology, and management but also promotes the renewal and development of social governance concepts, technologies, methods, and models, which creates new opportunities for urban floating population governance innovation. City governments at all levels are facing enormous management pressure and urgently need to promote innovative reforms in the governance of urban floating population. The development of information technology has developed into the era of big data, and strong data collection and processing capabilities can greatly improve the scientific level of urban floating population management. In the research of spatial correlation of innovation ability, the research of domestic and foreign scholars has been very mature, and the methods used are more comprehensive, combining big data with urban floating population governance, placing urban floating population governance in the context of big data research and analysis, exploring the channels for the government to use big data to optimize urban floating population governance, and putting forward specific and feasible countermeasures and suggestions. After a series of tests, the double-fixed-effects spatial Dubin model is used to explore the influence of population structure on regional innovation ability from five aspects: population urban-rural structure, population industrial structure, population education structure, population age structure, and population density. The results show that the population structure of higher education has the most significant role in promoting regional innovation capability, followed by urban population, population density, and secondary industry population structure; the working-age population structure has no significant impact on regional innovation capability; provincial innovation capability has a significant effect positive spatial spillover effect.