STEAM-3D

The challenge

Most countries in sub-Saharan Africa face the recurring challenge of controlling infectious diseases, with each successive outbreak threatening population health, disrupting livelihoods, and impeding economic development.

Effective monitoring and control programmes depend on surveillance data to provide information on the presence and spread of key pathogens. Once detected, evidence-based approaches can reduce the risk of new outbreaks and rapidly bring outbreaks under control.

Infectious disease modelling can be pivotal to these activities, especially for the design and implementation of disease control programmes. Modelling can identify areas where outbreak risk is highest, enabling targeted prevention activities, providing insights into likely outbreak dynamics, guiding response planning and demonstrating the likely impact of different intervention strategies. 

A key barrier to the use of infectious disease modelling is the limited expertise and experience of modelling techniques in many sub-Saharan African countries. Surveillance and modelling played crucial roles during the COVID-19 pandemic, most notably in helping to identify emerging viral variants. There are now opportunities to leverage this expertise to advance epidemiology and infectious disease modelling in a wider range of countries.

The project

The STEAM-3D project is drawing on the expertise and experience gained during the COVID-19 pandemic to establish a regional training platform for building sub-Saharan African capacity in epidemiology and data science. 

Hosted by the South African Medical Research Council (SAMRC), which played a key role during the pandemic, the project is organising two intensive training workshops (one introductory, one advanced), each of which includes several training courses. These will cover key areas of epidemiology and data science, including: 

• Infectious disease modelling techniques
• Routine Health Data for Disease Monitoring and Excess Mortality Estimation
• Application of AI/machine learning technologies
• Evidence-to-policy methodologies
• Knowledge translation

In years one and two, each workshop will be offered to 10 participants from each partner country – Cameroon, Malawi, Mozambique and South Africa. Year two will also include a virtual workshop, building on previous workshops and a focus on advanced statistical modelling approaches. In year three, participation will be opened to all countries, with each partner site acting as host – enabling the workshops to be held in English (Malawi), French (in Cameroon) and Portuguese (in Mozambique).

Workshops will be one week in duration and will build technical skills, with a strong focus on use of evidence and scientific communication. Workshops will incorporate a course on dashboard development and how to create an e-platform for ongoing education and communication. Practical applications will also be promoted by use of real-world datasets during training exercises. 

In addition, two outstanding trainees will be identified in each country and provided with additional training and mentoring, including multiple international mentors. They will participate in a summer school in Europe and will be trained to deliver the devolved learning activities.

Sustainability will be further promoted by the involvement of multiple regional networks, and the creation of an infectious disease modelling working group, hosted by the SAMRC, to support networking, knowledge exchange and further ongoing professional development.

Impact

The STEAM-3D project will strengthen infectious disease modelling capacity in sub-Saharan Africa. It will:

• Facilitate the sharing of knowledge and experience held within a centre of excellence in South Africa
• Establish additional training hubs catering to researchers and public health professionals from anglophone, francophone and lusophone countries
• Create a community of practice to support ongoing development of the field and adoption within disease control programmes. 

The STEAM-3D project will build regional capacity in infectious disease modelling, with a strong emphasis on data use to inform decision-making, ensuring that this emerging technology enhances the ability of sub-Saharan African countries to effectively track and respond to outbreaks and minimise their impact.