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Spatial variability of COVID-19 and its risk factors in Nigeria: a spatial regression method

The novel and unprecedented Coronavirus disease (COVID-19) pandemic has negatively impacted most nations of the world within a short period. While its disproportionate social and spatial variability has been established, the reality in Nigeria is yet to be studied. In this paper, advanced spatial st...

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Main Authors: Bayode, Taye (Author) , Popoola, Ayobami (Author) , Akogun, Olawale (Author) , Siegmund, Alexander (Author) , Magidimisha-Chipungu, Hangwelani (Author) , Ipingbemi, Olusiyi (Author)
Format: Article (Journal)
Language:English
Published: [January 2022]
In: Applied geography
Year: 2022, Volume: 138
ISSN:0143-6228
DOI:10.1016/j.apgeog.2021.102621
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.apgeog.2021.102621
Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S014362282100237X
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Author Notes:Taye Bayode, Ayobami Popoola, Olawale Akogun, Alexander Siegmund, Hangwelani Magidimisha-Chipungu, Olusiyi Ipingbemi
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Summary:The novel and unprecedented Coronavirus disease (COVID-19) pandemic has negatively impacted most nations of the world within a short period. While its disproportionate social and spatial variability has been established, the reality in Nigeria is yet to be studied. In this paper, advanced spatial statistical techniques were engaged to study the burden of COVID-19 and its risk factors within the first quarter (March-May) of its incidence in Nigeria. The spatial autocorrelation (Moran's I) test reveals a significant but marginal cluster of COVID-19 occurrence in Nigeria (I = 0.11, p < 0.05). A model comparison between ordinary least square (OLS) and spatial error model (SER) was explored having checked for multicollinearity in the dataset. The OLS model explained about 64% (adjusted R2 = 0.64) of variation in COVID-19 cases, however with significantly clustered residuals. The SER model performed better with randomly distributed residuals. The significant predictors were population density, international airport, and literacy ratio. Furthermore, this study addressed the spatial planning implications of the ongoing disease outbreak while it advocates transdisciplinary approach to urban planning practices in Nigeria.
Item Description:Available online 3 December 2021, version of record 7 December 2021
Gesehen am 26.0.2022
Physical Description:Online Resource
ISSN:0143-6228
DOI:10.1016/j.apgeog.2021.102621

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