Sarkodie Samuel Asumadu, Owusu Phebe Asantewaa
Nord University Business School, Norway.
Heliyon. 2020 Apr;6(4):e03747. doi: 10.1016/j.heliyon.2020.e03747. Epub 2020 Apr 4.
The initial investigation by local hospital attributed the outbreak of the novel coronavirus disease (COVID-19) to pneumonia with unknown cause that appeared like the 2003 severe acute respiratory syndrome (SARS). The World Health Organization declared COVID-19 as public health emergency after it spread outside China to several countries. Thus, an assessment of the novel coronavirus disease (COVID-19) with novel estimation approaches is essential to the global debate. This study is the first to develop both time series and panel data models to construct conceptual tools that examine the nexus between death from COVID-19 and confirmed cases. We collected daily data on four health indicators namely deaths, confirmed cases, suspected cases, and recovered cases across 31 Provinces/States in China. Due to the complexities of the COVID-19, we investigated the unobserved factors including environmental exposures accounting for the spread of the disease through human-to-human transmission. We used estimation methods capable of controlling for cross-sectional dependence, endogeneity, and unobserved heterogeneity. We predicted the impulse-response between confirmed cases of COVID-19 and COVID-19-attributable deaths. Our study revealed that the effect of confirmed cases on the novel coronavirus attributable deaths is heterogeneous across Provinces/States in China. We found a linear relationship between COVID-19 attributable deaths and confirmed cases whereas a nonlinear relationship was confirmed for the nexus between recovery cases and confirmed cases. The empirical evidence revealed that an increase in confirmed cases by 1% increases coronavirus attributable deaths by 0.10%-1.71% (95% CI). Our empirical results confirmed the presence of unobserved heterogeneity and common factors that facilitates the novel coronavirus attributable deaths caused by increased levels of confirmed cases. Yet, the role of such a medium that facilitates the transmission of COVID-19 remains unclear. We highlight safety precaution and preventive measures to circumvent the human-to-human transmission.
当地医院的初步调查将新型冠状病毒病(COVID-19)疫情归因于病因不明的肺炎,这种肺炎症状类似2003年的严重急性呼吸综合征(SARS)。新型冠状病毒病传播到中国以外的几个国家后,世界卫生组织宣布其为突发公共卫生事件。因此,采用新颖的估计方法对新型冠状病毒病(COVID-19)进行评估,对于全球讨论至关重要。本研究首次开发了时间序列模型和面板数据模型,以构建概念工具,检验COVID-19死亡病例与确诊病例之间的关系。我们收集了中国31个省/直辖市的四项健康指标的每日数据,即死亡病例、确诊病例、疑似病例和康复病例。由于COVID-19的复杂性,我们调查了包括环境暴露在内的未观察到的因素,这些因素解释了疾病通过人际传播的扩散情况。我们使用了能够控制横截面依赖性、内生性和未观察到的异质性的估计方法。我们预测了COVID-19确诊病例与COVID-19所致死亡之间的脉冲响应。我们的研究表明,确诊病例对新型冠状病毒所致死亡的影响在中国各省/直辖市之间存在异质性。我们发现COVID-19所致死亡与确诊病例之间存在线性关系,而康复病例与确诊病例之间的关系则被确认为非线性关系。实证证据表明,确诊病例增加1%会使冠状病毒所致死亡增加约0.10% - 约1.71%(95%置信区间)。我们的实证结果证实了未观察到的异质性和共同因素的存在,这些因素促进了确诊病例增加导致的新型冠状病毒所致死亡。然而,这种促进COVID-19传播的媒介的作用仍不清楚。我们强调了安全预防措施和预防措施,以规避人际传播。