数字金融行为能否提高中国疫情防控效果?

Sheng Wang
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There are many prevention and control measures adopted by various countries or regions for the epidemic of new coronavirus pneumonia, and digital financial behavior (DFB) is an important evaluation index for effective prevention and control measures, which is of very Chinese characteristics. \n \nMETHODS: DFB is defined by the Digital Financial Inclusion Payment Index, although there may be various versions of the understanding and definition of DFB. The data of the new crown pneumonia is calculated and accumulated through the real-time monitoring data published on the website of the health commissions of 31 provinces and municipalities directly under the central government every month, and is the first-hand raw data. Under the strict prevention and control measures adopted by China, these real-time data on new crown pneumonia released by various places are objective, true and comprehensive. 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The nonlinear exponential relationship between individuals with cumulative diagnosis of COVID-19 infection and DFB in 31 provinces and municipalities directly under the Central Government of China, excluding Hong Kong Special Administrative Region, Macao Special Administrative Region and Taiwan Province, has proved that this relationship is robust. Through regression analysis, it is found that the number of people infected with COVID-19 is significantly increased by one person for every additional unit of DFB. However, the similarity of DFB in 31 provinces and municipalities directly under the Central Government of China indicates that the number of COVID-19 infected individuals in 31 provinces and municipalities directly under the Central Government is increasing slowly. This result is very consistent with the distribution of actual statistical data, although the relevant data have certain regional differences. \n \nCONCLUSION: With extensive and in-depth practical basis and practical significance in all levels of Chinese society, DFB can measure the positive effect of the prevention and control of COVID-19 epidemic in China. Based on the positive role of DFB, there is every reason to believe that DFB will be one of the indispensable and trustworthy factors to improve its prevention and control performance in the face of similar social highly infectious diseases that may occur in the future. 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引用次数: 0

摘要

背景:2019年12月前,美国和部分欧洲国家出现了与COVID-19肺炎症状相似的白肺患者。自2019年12月中国武汉确诊新型冠状病毒肺炎以来,世界上几乎所有国家或地区都相继报告了新型冠状病毒肺炎病例。2020年是人类抗击新冠肺炎疫情最关键的一年。各国或地区针对新型冠状病毒肺炎疫情采取了诸多防控措施,数字金融行为(DFB)是防控措施有效与否的重要评价指标,非常具有中国特色。方法:DFB由数字普惠金融支付指数定义,尽管对DFB的理解和定义可能有不同的版本。新冠肺炎数据通过全国31个省、直辖市卫生健康委员会网站每月公布的实时监测数据计算积累,为第一手原始数据。在中国采取的严格防控措施下,各地发布的新冠肺炎疫情实时数据客观、真实、全面。本文采用的分析方法主要有统计分析方法、计量经济模型如对数线性回归模型、指数模型模拟法等。结果:COVID-19肺炎感染诊断为随机变量,与DFB呈非线性随机指数关系。实证研究发现,COVID-19感染诊断的最小二乘估计与DFB构成具有统计学意义的指数函数关系。该指标模型成功测度了中国新冠肺炎疫情防控效果,具有统计学意义,表明DFB对提高中国新冠肺炎疫情防控效果具有积极作用。对31个省市(不包括香港特别行政区、澳门特别行政区和台湾省)累计诊断COVID-19感染个体与DFB之间的非线性指数关系进行了研究,证明了这种关系是稳健的。通过回归分析发现,每增加1个单位的DFB, COVID-19感染人数就会显著增加1人。然而,31个省市的DFB相似性表明,31个省市的新冠肺炎感染人数增长缓慢。这一结果与实际统计数据的分布非常吻合,但相关数据存在一定的区域差异。结论:DFB在中国社会各层面具有广泛而深入的实践基础和现实意义,可以衡量中国防控新冠肺炎疫情的积极效果。基于DFB的积极作用,我们完全有理由相信,面对未来可能发生的类似社会高传染性疾病,DFB将成为提高其防控绩效不可或缺和值得信赖的因素之一。这里的研究方法是否具有更广泛的适用性,即对其他国家或地区的疫情防控是否具有统计学上显著的积极作用,应该是未来需要进一步探索的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Can Digital Financial Behavior Improve the Effect of Prevention and Control of COVID-19 in China?
BACKGROUND: Before December 2019, white lung patients with symptoms similar to COVID-19 pneumonia were found in the United States and some European countries. After COVID-19 pneumonia was diagnosed in Wuhan, China, in December 2019, almost all countries or regions in the world have successively reported cases of COVID-19 pneumonia. 2020 is the most critical year for all mankind to fight against the new crown pneumonia epidemic. There are many prevention and control measures adopted by various countries or regions for the epidemic of new coronavirus pneumonia, and digital financial behavior (DFB) is an important evaluation index for effective prevention and control measures, which is of very Chinese characteristics. METHODS: DFB is defined by the Digital Financial Inclusion Payment Index, although there may be various versions of the understanding and definition of DFB. The data of the new crown pneumonia is calculated and accumulated through the real-time monitoring data published on the website of the health commissions of 31 provinces and municipalities directly under the central government every month, and is the first-hand raw data. Under the strict prevention and control measures adopted by China, these real-time data on new crown pneumonia released by various places are objective, true and comprehensive. The analysis methods adopted in this paper mainly include statistical analysis methods, econometric models such as logarithmic linear regression model, exponential model simulation method, etc. RESULTS: The diagnosis of COVID-19 pneumonia infection is a random variable, and there is a nonlinear random exponential relationship between it and DFB. The empirical study found that the least square estimation of COVID-19 infection diagnosis and DFB constitute a statistically significant exponential function relationship. This index model has successfully measured the effect of COVID-19 epidemic prevention and control in China with statistical significance, which indicates that DFB plays a positive role in improving the effect of COVID-19 epidemic prevention and control in China. The nonlinear exponential relationship between individuals with cumulative diagnosis of COVID-19 infection and DFB in 31 provinces and municipalities directly under the Central Government of China, excluding Hong Kong Special Administrative Region, Macao Special Administrative Region and Taiwan Province, has proved that this relationship is robust. Through regression analysis, it is found that the number of people infected with COVID-19 is significantly increased by one person for every additional unit of DFB. However, the similarity of DFB in 31 provinces and municipalities directly under the Central Government of China indicates that the number of COVID-19 infected individuals in 31 provinces and municipalities directly under the Central Government is increasing slowly. This result is very consistent with the distribution of actual statistical data, although the relevant data have certain regional differences. CONCLUSION: With extensive and in-depth practical basis and practical significance in all levels of Chinese society, DFB can measure the positive effect of the prevention and control of COVID-19 epidemic in China. Based on the positive role of DFB, there is every reason to believe that DFB will be one of the indispensable and trustworthy factors to improve its prevention and control performance in the face of similar social highly infectious diseases that may occur in the future. Whether the research method here has wider applicability, that is, whether it has a statistically significant positive effect on the prevention and control of epidemics in other countries or regions, should be a question that needs to be further explored in the future.
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