Network Analysis for Science and Technology Management: Evidence from Tuberculosis Research in Fiocruz, Brazil

Collaborative networks are of great value for science and technology (S&T) institutions as a way of sharing, generating and disseminating new knowledge that could ultimately lead to innovations. Driven by the need to assess the contribution and effectiveness of these networks in informing S&T management, we explored the evolution and dynamics of tuberculosis scientific networks involving the Oswaldo Cruz Foundation (Fiocruz), the major public health S&T Institution in Brazil. Social network analysis (SNA) was used to produce a 10-year (2005-2009, 2010-2014) retrospective longitudinal mapping of Brazilian tuberculosis research networks within the country and internationally, highlighting Fiocruz collaborations. Co-authorship analysis showed a significant expansion of collaboration in Brazil and the role of Fiocruz and other leading national institutions in maintaining connectivity, facilitating knowledge exchange and reducing network vulnerability. It also identified influential researchers that can act as information leaders and support strategic decisions. When we focused on networks inside the institution, the analysis showed a clear discontinuation between the clinical and the public health research areas, which needs specific internal policies to improve collaborations since outcomes in TB are expected to provide better diagnostic tools and more effective treatments. The approach provides evidence to support S&T management by pinpointing: key central institutions maintaining network connectivity; most influential researchers that can act as advisors/experts for investment and induction policies; key Fiocruz researchers that could improve information exchange, systems integration and innovation within the institution; opportunities for synergy between internal research groups working in complementary areas. In summary, we observed that SNA parameters proved to be a valuable tool that, along with other indicators, can strengthen knowledge platforms to support S&T management efforts.