OCTOPUS

The challenge

Constant vigilance is essential in East Africa to detect and respond to emerging infections. Multiple outbreaks of Ebola virus, for example, have been detected over the past decade, alongside other haemorrhagic fever viruses and emerging infections. Due to factors such as population movements, land-use changes and climate change, there is a growing risk of zoonotic infections. In addition, the subregion is badly affected by antimicrobial resistance, which is undermining the ability of health systems to treat many infectious diseases. Importantly, infections can readily spread between countries, emphasising the need for a coordinated cross-country approach.

These issues highlight the critical need for strong surveillance systems to detect clusters of cases with the potential to develop into epidemics, as well as rapid and efficient response mechanisms to nip nascent outbreaks in the bud. In addition, with resources inevitably limited, evidence-based approaches need to be adopted to optimise the impact of control activities.

As well as comprehensive systems for data collection, countries also need the capacity to analyse these data, to understand likely hotspots, outbreak dynamics and the potential impact of control measures, informing prevention and response strategies. However, capacity to analyse data, particularly to apply mathematical modelling techniques, is limited in many countries. A recent survey of ministries of health found that half of epidemiologists had used only one database (the standard DHIS-2 platform), while experience with programming languages was limited (half of respondents had used R but only 15% Python). Just 6% had experience of machine learning/AI.

The project

The OCTOPUS project is addressing this skills gap through a training programme designed to have a catalytic effect by enabling trainees to become additional trainers and pass on their expertise to others.

The project is establishing a two-year Master’s programme for participants from six countries in the greater East African subregion – Burundi, the Democratic Republic of the Congo (DRC), Kenya, Rwanda, Tanzania and Uganda. OCTOPUS will also provide short-term technical training opportunities for Africa. These countries vary significantly in their infectious disease modelling and outbreak response capabilities, providing opportunities for South–South exchange of knowledge and experience.

The Master’s programme will be a hybrid two-year programme, targeting early to mid-career researchers. The first year will be spent on academic coursework at a globally recognised training site in Denmark. The second year will be dedicated to practical research within a ministry of health, a national public health institute, a research institute, or a university in sub-Saharan Africa. Ten fellows will be enrolled, two each from Burundi, DRC, Kenya and Uganda and one each from Rwanda and Tanzania (based on capacity-building needs and recent history of zoonotic outbreaks).

In addition, a range of workshops, short courses and seminars will be organised to enhance the awareness and knowledge of public health professionals from participating countries. Five participants will attend from each country.

Both forms of training will have a strong focus on practical application of data science tools and modelling. Trainees will work with real-world datasets and tools shared by project partners. They will develop actionable knowledge products, such as data dashboards, geospatial maps and outbreak prediction models.

The impact of these activities will be amplified by the subsequent training activities undertaken by participants. Country staff participating in short-term training events will share their new knowledge with colleagues in their home countries. Once a quarter, Master’s graduates will each host a week-long workshop for 25 participants. This will extend the project’s reach from 45 direct trainees to an estimated 4,500 beneficiaries.

In addition, the project is also creating a data catalogue and a cross-border data-sharing and public health data analytics platform. This will integrate surveillance data from multiple countries, enabling subregional analyses, including AI-enabled predictive models.

The project will also implement a comprehensive mentorship scheme and work with ministries of health and national public health institutes on a career development framework and progression pathways. Consultations will be undertaken to identify key barriers and career roadblocks, which will inform the design of a continuing professional development programme.

Impact

The OCTOPUS project will make a major contribution to public health workforce skills development in East Africa. It will:

• Train a new cohort of early to mid-career researchers in the latest data science and machine learning/AI technologies.
• Ensure that theoretical learning is backed up by experience of practical application to address public health challenges.
• Amplify impact by ensuring that each trainee passes on knowledge to colleagues through a structured secondary training programme.
• Create a cross-border data analytics platform that will enable countries to share data and collaborate on subregional analyses.

The OCTOPUS project is pioneering a subregional approach to promote collaboration on outbreak response, recognising the need for countries to work together to address the challenges posed by emerging infections.