Sustainable Statistical Capacity-Building for Africa: The Biostatistics Case

Author:

Reddy Tarylee12,Nsubuga Rebecca N.34,Chirwa Tobias5,Shkedy Ziv6,Mwangi Ann7,Awoke Ayele Tadesse8,Duchateau Luc9,Janssen Paul610

Affiliation:

1. Biostatistics Research Unit, South African Medical Research Council, Durban, South Africa

2. School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Durban, South Africa

3. USAID Strategic Information Technical Support (SITES), Social & Scientific Systems, Inc., a DLH Holding Company, Kampala, Uganda

4. School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda

5. Epidemiology and Biostatistics Division, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa

6. Center for Statistics, Data Science Institute, Hasselt University, Diepenbeek, Belgium;

7. School of Science and Aerospace Studies, Moi University, Eldoret, Kenya

8. Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia

9. Biometrics Research Group, Ghent University, Merelbeke, Belgium

10. School of Statistics and Mathematical Sciences, North-West University, Potchefstroom Campus, Potchefstroom, South Africa

Abstract

Several major global challenges, including climate change and water scarcity, warrant a scientific approach to generating solutions. Developing high quality and robust capacity in (bio)statistics is key to ensuring sound scientific solutions to these challenges, so collaboration between academic and research institutes should be high on university agendas. To strengthen capacity in the developing world, South–North partnerships should be a priority. The ideas and examples of statistical capacity-building presented in this article are the result of several monthly online discussions between a mixedgroup of authors having international experience and formal links with Hasselt University in Belgium. The discussion focuses on statistical capacity-building through education (teaching), research, and societal impact. We have adopted an example-based approach, and in view of the background of the authors, the examples refer mainly to biostatistical capacity-building. Although many universities worldwide have already initiated university collaborations for development, we hope and believe that our ideas and concrete examples can serve as inspiration to further strengthen South–North partnerships on statistical capacity-building.

Publisher

Annual Reviews

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

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