A capacity-building platform for advancing biostatistics in Ethiopia, Kenya and Malawi
Lead Research Organisation:
Lancaster University
Department Name: Medicine
Abstract
The overarching goal of this proposal is to develop a self-sustaining capacity building platform for advancing biostatistical methodology research in Kenya, Malawi and Ethiopia.
The grant will sponsor six training fellowships for full-time employed researchers in biostatistics at the Kenya Medical Research Institute Wellcome Trust Research Programme (KEMRI-WTRP) in Nairobi and Kilifi (Kenya), the Malawi-Liverpool Wellcome Trust Clinical Research Programme (MLW-CRP) in Blantyre (Malawi) and the Department of Statistics of Hawassa University in Ethiopia. The rationale for our chosen partners is that Hawassa has a strong postgraduate programme in statistics while KEMRI-WTRP and MLW-CRP provide applied biostatistics environments linked to substantive public health context and expertise.
The six Fellows will be placed in Lancaster University and Cambridge University for the duration of 12 months and will work on the development of advanced statistical methodology motivated by three substantive global health problems. The programme will enable the Fellows to operate as integral members of multi-disciplinary research teams by further development of their expertise in biostatistics, skills in teaching of statistical subjects and their ability to develop high-quality documented statistical software.
The specific activities of this proposal are the following. Training courses in geospatial statistical methods and mathematical modelling of infectious diseases will be delivered by Lancaster and Cambridge. These courses will be tailored to the specific needs and projects of each Fellows. During the programme, the Fellows will also design new courses in statistics to be delivered at their respective institutes after completion of the project. This will be carried out in collaboration with the PI and CIs who will provide high quality support in the creation of new teaching material and educational statistical software. The core spirit of this programme is of a continuous and strong interaction between the Fellows and the investigators, who will act both as project supervisors and mentors.
The grant will sponsor six training fellowships for full-time employed researchers in biostatistics at the Kenya Medical Research Institute Wellcome Trust Research Programme (KEMRI-WTRP) in Nairobi and Kilifi (Kenya), the Malawi-Liverpool Wellcome Trust Clinical Research Programme (MLW-CRP) in Blantyre (Malawi) and the Department of Statistics of Hawassa University in Ethiopia. The rationale for our chosen partners is that Hawassa has a strong postgraduate programme in statistics while KEMRI-WTRP and MLW-CRP provide applied biostatistics environments linked to substantive public health context and expertise.
The six Fellows will be placed in Lancaster University and Cambridge University for the duration of 12 months and will work on the development of advanced statistical methodology motivated by three substantive global health problems. The programme will enable the Fellows to operate as integral members of multi-disciplinary research teams by further development of their expertise in biostatistics, skills in teaching of statistical subjects and their ability to develop high-quality documented statistical software.
The specific activities of this proposal are the following. Training courses in geospatial statistical methods and mathematical modelling of infectious diseases will be delivered by Lancaster and Cambridge. These courses will be tailored to the specific needs and projects of each Fellows. During the programme, the Fellows will also design new courses in statistics to be delivered at their respective institutes after completion of the project. This will be carried out in collaboration with the PI and CIs who will provide high quality support in the creation of new teaching material and educational statistical software. The core spirit of this programme is of a continuous and strong interaction between the Fellows and the investigators, who will act both as project supervisors and mentors.
Planned Impact
- Who will benefit from this research?
The methodological research undertaken by the Fellows will be developed and validated using both simulations and data generated within disease control programmes in developing countries. Partner institutions will use their extensive links with knowledge translation and policy stakeholders at local, national and international levels in order to allow any of the resulting methods to feed directly into policy-relevant applications that will in turn inform control programme of infectious diseases, with a special focus on malaria. The non-academic beneficiaries will thus include policy makers and staff of disease control programmes in Kenya, Malawi and Ethiopia and, indirectly, those based in other developing countries.
- How will they benefit from this research?
Our training will increase the number of highly skilled Africa-based biostatisticians. On completion of the programme, they will be well positioned to secure further career opportunities, within and beyond the programme's partners. Building on their collective statistical expertise and professional networks they will be ambassadors and future trainers, thus ensuring the training platform's sustainability.
Sound statistical methodology provides essential underpinning for the design and analysis of biomedical research projects to inform decisions around public health policy and practice that will ensure progression towards national goals of improving health in-country. Our programme will replace the all-too-common current outsourcing of statistical support for health research by a sustainable model of training and development that will create new jobs and career paths for African students. In collaboration with our African research partners, we will ensure that proactive steps are taken to inform public health policies and decision-making in each of the countries covered by three research projects. The application of the best statistical methods is crucial so as to make the best possible use of biomedical data in constrained resource settings. Our project will provide a platform of research activities that will benefit population health and welfare in sub-Sahara Africa. Monitoring the changes in disease risk over time and space using modern statistical methods will highlight the strengths of more targeted control measures, compared to blanket control efforts, towards both high burden and low transmission areas for a more cost-efficient and efficacious combination of interventions.
Policy makers will have free access to the research outputs of the projects which we will make freely available on a dedicated website of the programme. For the specific identified applications, we expect that the knock-on impact on policy-development will be realised within one year following completion of the training programme. The time-scale for the wider benefits will be longer, owing to the need to publish case-study reports and build new collaborations both within and outside the countries involved in the programme.
The methodological research undertaken by the Fellows will be developed and validated using both simulations and data generated within disease control programmes in developing countries. Partner institutions will use their extensive links with knowledge translation and policy stakeholders at local, national and international levels in order to allow any of the resulting methods to feed directly into policy-relevant applications that will in turn inform control programme of infectious diseases, with a special focus on malaria. The non-academic beneficiaries will thus include policy makers and staff of disease control programmes in Kenya, Malawi and Ethiopia and, indirectly, those based in other developing countries.
- How will they benefit from this research?
Our training will increase the number of highly skilled Africa-based biostatisticians. On completion of the programme, they will be well positioned to secure further career opportunities, within and beyond the programme's partners. Building on their collective statistical expertise and professional networks they will be ambassadors and future trainers, thus ensuring the training platform's sustainability.
Sound statistical methodology provides essential underpinning for the design and analysis of biomedical research projects to inform decisions around public health policy and practice that will ensure progression towards national goals of improving health in-country. Our programme will replace the all-too-common current outsourcing of statistical support for health research by a sustainable model of training and development that will create new jobs and career paths for African students. In collaboration with our African research partners, we will ensure that proactive steps are taken to inform public health policies and decision-making in each of the countries covered by three research projects. The application of the best statistical methods is crucial so as to make the best possible use of biomedical data in constrained resource settings. Our project will provide a platform of research activities that will benefit population health and welfare in sub-Sahara Africa. Monitoring the changes in disease risk over time and space using modern statistical methods will highlight the strengths of more targeted control measures, compared to blanket control efforts, towards both high burden and low transmission areas for a more cost-efficient and efficacious combination of interventions.
Policy makers will have free access to the research outputs of the projects which we will make freely available on a dedicated website of the programme. For the specific identified applications, we expect that the knock-on impact on policy-development will be realised within one year following completion of the training programme. The time-scale for the wider benefits will be longer, owing to the need to publish case-study reports and build new collaborations both within and outside the countries involved in the programme.
Organisations
Publications
Macharia PM
(2022)
Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens.
in BMC pregnancy and childbirth