Mapping regional cooperation of state actors for health research systems in Africa: A social network analysis

Abstract

Regional bodies can potentially play an important role in improving health research in Africa. This study analyses the network of African state-based regional organisations for health research and assesses their potential relationship with national health research performance metrics. After cataloguing organisations and their membership, we conducted a social network analysis to determine key network attributes of national governments' connections via regional organisations supporting functions of health research systems. This data was used to test the hypothesis that state actors with more connections to other actors via regional organisations would have higher levels of health research performance across indicators. With 21 unique regional organisations, the African continent is densely networked around health research systems issues. In general, the regional network for health research is inclusive. No single actor serves as a nexus. However, when statistics are grouped by African Union regions, influential poles emerge, with the most predominate spheres of influence in Eastern and Western Africa. Further, when connectivity data was analysed against national health research performance, there were no statistically significant relationships between increased connectivity and higher performance of key health research metrics. The inclusive and dense network dynamics of African regional organisations for health research strengthening present key opportunities for knowledge diffusion and cooperation to improve research capacity on the continent. Further reflection is needed on appropriate and meaningful ways to assess the role of regionalism and evaluate the influence of regional organisations in strengthening health research systems in Africa.

Fig 1. African state-based network map for regional HSciR.

Legend: States are represented by individual nodes and connections between states represented by edges. More frequent connections are reflected with thicker edges. The total weighted degree for each State is indicated by the node size.