ABSTRACT
COVID-19 pandemic created a shockwave that can be felt across every sphere of society and the environment. The disease grew from a local event to a pandemic and the impacts are not the same everywhere. Therefore, there is a need to characterise the impact at different levels to ensure that initiatives to cushion the impacts are well-targeted. This study utilised graph analysis to examine the network attributes of Facebook Users’ mobility during the pandemic in comparison with the baseline period before the pandemic to characterise the economic impact. Movement data were collated from the Facebook Data for Good platform while economic output and census data were collated from the National Bureau of Statistics. The result shows that economic output and baseline network attributes have a positive and highly significant relationship (P<0.01). Nodal efficiency was statistically different across the crisis and baseline periods while betweenness showed no difference. The sum of the difference from baseline values identified two extremes – Lagos State (most negatively impacted) and Kwara State (most positively impacted). The States adopted varying measures to combat the disease, these variations also emerged in the graph analysis results. Economic output from each State is related to its centrality and efficiency. It is therefore plausible that changes in network attributes will bring commensurate changes in the economic output of each State. States with high centrality and betweenness values had a greater decline in their network attributes. The study provided an insight into one aspect of the extent of the economic impact of the COVID-19 on each State. We recommend more investigations into the inclusion of local interactions in capturing intra-state movements and changes in modelling economic output. © 2021, Comenius University in Bratislava. All rights reserved.