Context-dependent leadership in global health science: Brazil's role across North–South, South–South, and triangular collaboration models (2010–2019)
Year: 2026
Type: article
Abstract: Brazil plays an important role in global scientific collaboration in health and life sciences (HLS), yet systematic analysis of how patterns differ across North–South, South–South, and Triangular partnerships remains limited. This study examines Brazil's international HLS collaborations (2010–2019) using Scopus data (362,860 publications), analyzing growth, leadership, citation impact, and thematic specialization across three models: Brazil with high-income countries (BR–HIC; North–South), Brazil with low- and middle-income countries (BR–LMIC; South–South), and Brazil with both (BR–HIC–LMIC; triangular). International collaborations nearly doubled (1.71-fold), with Triangular cooperation growing fastest (3.08-fold), though this growth was not accompanied by a proportional increase in Brazilian authorship leadership. Scientific leadership, operationalized here as first and last authorship position, varied markedly across models: 75% in BR–LMIC, 67% in BR–HIC, and only 31% in Triangular partnerships, a gradient suggesting context-dependent rather than uniformly peripheral or central positioning. Citation impact followed a clear hierarchy: 49% of Triangular collaborations ranked in top 10% most-cited versus 34% for BR–HIC and 22% for BR–LMIC. Thematic focus diverged across models: BR–HIC spanned several areas and Triangular partnerships concentrated on clinical trials. Notably, BR–LMIC thematic focus aligned closely with Brazil's highest Specialization Index fields: Agricultural and Biological Sciences and Veterinary Sciences. These findings demonstrate that emerging scientific powers may occupy context-dependent positions in global research networks, with implications for how bibliometric frameworks assess leadership and equity in international collaboration.
Source: Scientometrics
Institutions: Fundação Oswaldo Cruz, Calvin University
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,190
Awards: G1378852081, G3315780251, G4723017874
OpenAlex ID: W7204442244
