A comparative hierarchical data-centric approach to monitor social permeability, coping potential and social vulnerability in facing COVID-19 crisis in Africa

Abstract

The rapid spread of the COVID-19 virus and its high death rate have surprised many countries around the world. In such a situation, a lack of proper positioning against this disaster can lead to irreparable and long-term damages. Through designing a comparative interdependent platform in two phases of COVID-19's outbreak-epidemic and pandemic, this paper investigates the positioning of 8 African countries, including Egypt, South Africa, Tunisia, Morocco, Algeria, Nigeria, Cameroon, and Kenya, based on the composite indices of social permeability, coping potential and social vulnerability. Further, using the k-means approach, the under-study countries are involved in some dominant clusters by which their surrounding features compared to each other are implied. To reduce the risk arising from disasters such as COVID-19, the decision tree method is taken to extract patterns indicating the risk of vulnerability in the future. The results of the carried out analyses prove that Algeria has the most preferable position in the social permeability index and Tunisia has the most coping potential compared to other countries. On the other hand, Cameroon and Egypt have had relatively less vulnerability in dealing with COVID-19, which can lead to valuable management perspectives. The performed clustering depicts that the dominant clusters include 0–1) Egypt, Morocco, and Tunisia, 2–4) South Africa, 1-2-4) Algeria, and 3) Nigeria, Kenya, and Cameroon. Tracing the branches of the decision tree can also facilitate achieving different vulnerability ranges and guide the adoption of appropriate policies to balance the influencing factors and reduce their adverse effects.