This study investigates the propagation power and effects of the coronavirus disease 2019 (COVID-19) in light of published data. We examine the factors affecting COVID-19 together with the spatial effects, and use spatial panel data models to determine the relationship among the variables including their spatial effects. Using spatial panel models, we analyse the relationship between confirmed cases of COVID-19, deaths thereof, and recovered cases due to treatment. We accordingly determine and include the spatial effects in this examination after establishing the appropriate model for COVID-19. The most efficient and consistent model is interpreted with direct and indirect spatial effects.

根据公开的数据，本研究调查了2019年冠状病毒病（COVID-19）的繁殖力和作用。我们研究了影响COVID-19的因素以及空间效应，并使用空间面板数据模型来确定变量之间的关系，包括其空间效应。使用空间面板模型，我们分析了确诊的COVID-19病例，其死亡与因治疗而康复的病例之间的关系。因此，在为COVID-19建立适当的模型后，我们在此检查中确定并包括了空间效应。用直接和间接的空间效应来解释最有效和一致的模型。