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. 2021;1(11):269.
doi: 10.1007/s43545-021-00285-5. Epub 2021 Nov 22.

Place-based modelling of social vulnerability to COVID-19 in Nigeria

Olanrewaju Lawal  1 , Tolulope Osayomi  2
Affiliations

Place-based modelling of social vulnerability to COVID-19 in Nigeria

Olanrewaju Lawal et al. SN Soc Sci. 2021.

Abstract

COVID-19, within a short period of time, grew into a pandemic. The timely identification of places and populations at great risk of COVID-19 infection would aid disease control. In Nigeria, where a variety of recommended and adopted non-pharmaceutical interventions seem to have limited effectiveness, the number of cases is still increasing. To this end, this paper computed a social vulnerability to COVID-19 index (SoVI) in Nigeria within the local government area (LGA) framework with a view to revealing vulnerable places and populations. The study relied on several data sources and factor analysis for the development of the index. SoVI values ranged from 2.3 (least vulnerable) to 6.8 (most vulnerable). Three percent of the 774 LGAs were extremely vulnerable while 2% of these LGAs were least vulnerable to COVID-19. The predictive power of the index was confirmed to be strong (r = 0.812). Hopefully, the visual representation of place-based vulnerability to COVID-19 index should guide and direct the relevant authorities in the containment of further spread and vaccination coverage.

Keywords: COVID-19; GIS; Nigeria; Pandemic; Social vulnerability.

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Conflict of interest statement

Conflict of interestThe authors have none to declare.

Figures

Fig. 1
Fig. 1
Population density of states in Nigeria
Fig. 2
Fig. 2
States and geopolitical zones in Nigeria
Fig. 3
Fig. 3
Steps for modelling place-based vulnerability to COVID-19
Fig. 4
Fig. 4
Distribution of SVS values for the four factors
Fig. 5
Fig. 5
Place-based social vulnerability Index for LGAs
Fig. 6
Fig. 6
Location of LGAs with above-average SoVI values
See this image and copyright information in PMC

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