摘要：The COVID-19 pandemic has spread rapidly all over the world, affecting many countries to varying degrees. In this study, an in-depth analysis of the factors influencing the spread of COVID-19 is offered mainly through big data in the European Union (EU) context. In doing so, the data of the first wave of the pandemic are assessed. Afterward, we evaluate the impacts of the COVID-19 spread in specific countries and regions. Based on the existing literature, mobility is recognized as a significant direct factor affecting disease transmission. The same applies to the case of COVID-19. However, compared with the analysis of mobility itself, this paper explores more profound reasons that affect mobility, ranging from policy and economy to geographical and transportation factors. Specifically, this paper studies nine EU countries based on their population density and the degree of impact of the epidemic in the first six months (February to July 2020) of the pandemic. Our study aims to illustrate how policies, economies, and geographical locations (including transportation factors) directly or indirectly affect the spread of the novel coronavirus by applying the SEIR model to analyze all selected countries’ big data. The key findings of this research are: (1) the timeliness of relevant policies and the effectiveness of government implementation indirectly limit the spread of the epidemic by reducing population mobility; (2) a better medical level would contribute to detect, isolate, and treat patients, and help control the epidemic; and (3) the large land borders and developed transportation between countries exacerbate the spread of the COVID-19. The paper contributes to ongoing research on COVID-19 by addressing the above points.
