Modelling spatial variations of coronavirus disease (COVID-19) in Africa
Modelling spatial variations of coronavirus disease (COVID-19) in Africa
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DOI：
10.1016/j.scitotenv.2020.138998
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发表时间：
2020-08-10
影响因子：
9.8
通讯作者：
Ogunbanjo, Olakitan Wahab
中科院分区：
文献类型：
--
作者：
Adekunle, Ibrahim Ayoade;Onanuga, Abayomi Toyin;Ogunbanjo, Olakitan Wahab
自 2019 年底以来，新型冠状病毒在全球肆虐，其人际传播的临床和流行病学证据已经取得进展。人际传播的异常情况仍有待探索。在这项研究中，我们研究了空间密度，并为全球辩论提供了统计可信度。我们构建了聚类的空间变化，以检查 COVID-19 归因死亡与确诊病例之间的关系。我们依靠非洲各地确诊病例和死亡的公开数据来揭示可能导致 COVID-19 传播的未观察到的因素。我们依靠动态系统广义矩估计程序方法，发现非洲确诊病例与 0.045 例 Covid19 死亡人数相似。我们考虑了横截面依赖性并找到了严格正交关系的基础。讨论了政策措施。 (c) 2020 Elsevier B.V. 保留所有权利。
Clinical and epidemiological evidence has been advanced for human-to-human transmission of the novel coronavirus rampaging the world since late 2019. Outliers in the human-to-human transmission are yet to be explored. In this study, we examined the spatial density and leaned statistical credence to the global debate. We constructed spatial variations of clusters that examined the nexus between COVID-19 attributable deaths and confirmed cases. We rely on publicly available data on confirmed cases and death across Africa to unravel the unobserved factors, that could be responsible for the spread of COVID-19. We relied on the dynamic system generalised method of moment estimation procedure and found a similar to 0.045 Covid19 deaths as a result of confirmed cases in Africa. We accounted for cross-sectional dependence and found a basis for the strict orthogonal relationship. Policy measures were discussed. (c) 2020 Elsevier B.V. All rights reserved.