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dc.contributor.authorSarkodie, Samuel Asumadu
dc.contributor.authorOwusu, Phebe Asantewaa
dc.date.accessioned2020-07-09T07:22:02Z
dc.date.available2020-07-09T07:22:02Z
dc.date.created2020-04-12T14:33:26Z
dc.date.issued2020
dc.identifier.citationSarkodie, S. A. & Owusu, P. A. (2020). Investigating the cases of novel coronavirus disease (COVID-19) in China using dynamic statistical techniques. Heliyon, 6(4): e03747. doi:en_US
dc.identifier.issn2405-8440
dc.identifier.urihttps://hdl.handle.net/11250/2661514
dc.description.abstractThe 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.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleInvestigating the cases of novel coronavirus disease (COVID-19) in China using dynamic statistical techniquesen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2020 The Author(s)en_US
dc.subject.nsiVDP::Medisinske Fag: 700::Helsefag: 800::Epidemiologi medisinsk og odontologisk statistikk: 803en_US
dc.subject.nsiVDP::Samfunnsvitenskap: 200::Økonomi: 210::Økonometri: 214en_US
dc.source.pagenumber5en_US
dc.source.volume6en_US
dc.source.journalHeliyonen_US
dc.source.issue4en_US
dc.identifier.doi10.1016/j.heliyon.2020.e03747
dc.identifier.cristin1805886
dc.description.localcodeUnit Licence Agreementen_US


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Med mindre annet er angitt, så er denne innførselen lisensiert som Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal