Modeling the Complexity and Dynamics of the Malaria Research Collaboration Network in Benin, West Africa: papers indexed in the Web Of Science (1996—2016)

Multidisciplinary approach to malaria research remain important to the national malaria control program in Benin. To unravel the mechanism underlying the establishment of research collaboration ties in malaria research in Benin, we model the complexity and dynamics of the malaria research co-authorship network of Benin using Exponential Random Graph models (ERGMs) and Temporal ERGMs (TERGMs). The network contains co-authorship information from January 1996 to December 2016. We fit ERGMs and TERGMs to the network as a function of nodal, dyadic and structural statistics terms, accounting for important principles of graph theory such as homophily and structural equivalence. The final ERGM and TERGM showed that the mechanistic phenomenon driving collaboration ties in malaria research in Benin is driven by homophily on the type of affiliation and by membership to a research group. Our study is one of a few to take a model-based approach to the study ofco-authorship networks