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

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.