Despite increasing research output across Africa, weaknesses in statistical methodology continue to compromise the quality, reproducibility, and practical value of health research. Although substantial investments have been made in research capacity strengthening, limitations in statistical training and access to biostatistical expertise remain widespread. Existing initiatives, including regional postgraduate programmes and institution-specific training schemes, have contributed to advances in biostatistical capacity but remain fragmented, geographically limited, and insufficiently integrated into routine research practice. In this viewpoint, we argue that strengthening statistical capacity in Africa now requires a coordinated, continent-wide training network embedded within existing academic and research systems, rather than continued reliance on isolated programmes. The proposed model emphasises scalable training infrastructure, integration of statistical expertise throughout the research process, and structured collaboration between institutions facing similar methodological challenges. Central components include accessible training resources, mentorship, incorporation of statistics into existing curricula, and practical support linked to ongoing research activities. Emphasis is placed on standardising core competencies in statistical practice, including appropriate method selection, assessment of assumptions, transparent reporting, and accurate interpretation of findings. By embedding statistical thinking from study design through publication, the proposed network aims to improve methodological consistency, strengthen research credibility, and enhance the global impact and usability of health research conducted across Africa.
Ordak et al. (Tue,) studied this question.