By Alberto Leny                                    

Biostatistics – the development of statistical methodology to solve practical problems in health and medicine – is a critical discipline in informing public health policy in Africa.

However, there is prevailing lack of capacity and the big gap in the number of biostatisticians has had a major impact on the formulation and implementation of health policy on the continent. How can biostatistics help build robust health systems and interventions?

The scientific application of statistical methods to a wide range of topics in biology has gained significance globally and is essential for the achievement of the health-related sustainable development goals (SDGs). Many African countries are still way off in meeting the SDGs and the African Union’s 2030 Agenda targets.

Although progress has been made against several leading causes of death and disease, challenges remain.  Widening economic and social inequalities, rapid urbanization, threats to climate and the environment, the burden of HIV and other infectious diseases and non-communicable diseases (NCDs) have compounded public health issues in Africa.

An accurate estimate of the proportion affected by a disease is important for prioritizing the control of that disease relative to another and for allocating resources to control or prevention programmes.

Since high-quality surveillance data for developing countries such as those in Africa is frequently lacking, calculations of the burden of a disease are often based on prevalence estimates from cross-sectional surveys, which are rarely randomized or representative of the whole population.

That is why biostatistics has emerged as a crucial profession in informing health policymakers to implement evidence-based decisions for control strategies, and to advice government ministries of health and the community at large.

While there has been a surge of biomedical/health research generating data that could be used to inform health policy, this has not been matched by the statistical capacity to analyse the data for evidence-based decision-making, according to Henry Mwambi, academic leader at the School of Mathematics, Statistics and Computer Science, University of KwaZulu Natal (UKZN), South Africa.

This gap in the number of biostatisticians means that the demand for efficient data analysis cannot be met; leading to inefficient use of information from data that is costly generated. This gap needs to be urgently addressed.

The Sub-Saharan Africa Consortium of Advanced Biostatistics (SSACAB) was established in 2014, to bring together a network of biostatisticians and statisticians in Sub-Saharan Africa to address the lack of biostatistics capacity in the region.

Biostatisticians affiliated to SSACAB are at UKZN, University of Nairobi, University of Zambia, University of Malawi, South African Medical Research Council, University of the Witwatersrand, Johannesburg, South Africa, University of Namibia, Makerere University, Human Sciences Research Council, South Africa, London School of Hygiene and Tropical Medicine, Mwanza, Tanzania and University of Stellenbosch, South Africa.

SSACAB is one of the 11 awardees of the US$100 million DELTAS Africa programme supporting collaborative teams to conduct health research, offer training fellowships and mentorship, and invest in research infrastructure.

The programme is being implemented by The African Academy of Sciences (The AAS) through its programmatic platform, the Alliance for Accelerating Excellence in Science in Africa (AESA) with the support of Wellcome Trust and the UK Department for International Development (DfID).

SSACAB was therefore formed to accelerate the training of the next generation of biostatisticians within academic institutions in the region in collaboration with research institutions where fellows can get practical exposure to real data of direct importance in providing solutions to health problems on Africa and impact policy.

SSACAB’s first phase is training 90 biostatisticians at Master’s level and 15 at PhD level at, among others, UKZN, Wits, University of Malawi and University of Nairobi.

The results have been encouraging, with a renewed interest and awareness of biostatistics both from users and students. There is also increased interaction between consumers of biostatistics (research institutions, government health departments and research councils, health institutions) and academic training institutions within SSACAB.

Biostatistics has become critical in informing public health policy in Africa because of its methodological nature where statistical methods can be used to critically analyse data to find out what evidence it has about association of disease and risk or causal factors.

This way health and government policymakers can make informed decisions about intervention and mitigation strategies.

Over the past decades, African scientists have not been able to effectively analyse the data collected because of the non-existence of biostatistical support. While studies on very important health problems were being carried out, no expert statistical support was available.

It was only in projects funded from Europe or North America where statistical data could be sourced from the developed countries. SSACAB aims to fill this gap by ensuring that biostatisticians are locally trained. Regular in-house workshops should be the norm as part of the training.

Fellows across the SSACAB consortium and non-SSACAB biostatistics students and researchers are encouraged to hold in-house workshops on analysis of complex multi-level data from biomedical research, monitoring and evaluation of clinical trials and statistical methods for data management methods with software.

One of the major challenges facing biostatistics in Africa is that most academic training institutions are under-resourced with state-of-the-art facilities such as computer labs and LANS.

Another challenge is competition for statisticians by other employers. “We are regularly seeing students who had initially opted to train as biostatisticians being absorbed in other sectors such as finance, insurance and energy, where demand for statisticians is also high.”

“Previous efforts to develop statistics in the region existed but have been fragmented, with limited impact,” according to Project Coordinator Ngianga-Bakwin Kandala of Northumbria University. “As disease burden and populations increase with the industrialisation of the region, increasing data is being collected on various communicable and non-communicable diseases, but little is being done with the data to the subsequent impact on the area.”

SSACAB has since evolved into a consortium of 20 African and Northern academic institutions focusing on creating a series of research nodes that promote and support the growth and development of biostatistical skills amongst researchers in the region.

Programme Manager Pascalia Munyewende says it is important for public health data to inform public health policy by breaking down the data to plan interventions and priorities. “Biostatistics is important for planning the economy, so it is essential that we understand the numbers.”

Statistical analysis of data concerning human health, migration patterns, energy usage, healthcare demands and economic growth help governments plan the best use of limited resources, ensuring that such resources are used in the most appropriate way.

As disease burden and populations increase with the industrialisation of the region, increasing data is being collected on various communicable and non-communicable diseases, but little is being done with the data to the subsequent impact on the area.

Through SSACAB, the lack of informed statisticians capable of dealing with the specialities of biological systems is being addressed.  Kandala and a group of researchers are spearheading efforts to address the shortage of knowledge in the critical area of biostatistics in Africa.

Kandala has applied the principles of biostatistics to the numerous social and healthcare problems encountered by African nations, with detailed research into geo-additive models on child undernutrition, and the prevalence of illnesses such as diarrhoea and fever morbidity in the region.

His research has made a substantial contribution to the fields of tropical disease mapping, development aid and public health, and complex interventions.

 

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