AIMS Network

Malaria Modeling in Africa

Malaria Modeling in Africa

Building the next generation of malaria modelers in Africa for sustainable public health policies


Despite the widespread efforts to prevent and treat the disease, sustained reductions in the Malaria burden remain challenging. Globally, there has been a decrease in malaria incidence and mortality since 2000, but advances have stalled recently. The disease disproportionately affects children, and pregnant women impede socio-economic development and decreases their quality of life. Integrated measures including case management with artemisinin combination therapy, insecticide-treated bed nets, mosquito larval source elimination, and vaccine development efforts are beset by challenges including a lack of adequate surveillance data. National malaria control programs (NMCPs) are continuously improving systems to gather critical data on malaria surveillance, coverage, and effectiveness of preventive and treatment interventions. Mathematical modeling and geospatial analyses are opportunities to leverage existing data sources, extracting epidemiological and intervention data to inform national and regional decision-making. In recent years, modeling has gained the attention of African health authorities for stratification and subnational tailoring of interventions, however opportunities to institutionalize modeling into program planning and implementation remain elusive.

African Institute for Mathematical Science (AIMS) is partnering with universities, research institutions, operational partners, and NMCPs from Rwanda, Benin, Senegal, Burkina Faso, Mozambique, Côte d’Ivoire, Switzerland, Australia, Kenya, and Ghana, under BMGF, to build the Next Generation of Malaria Modelers in Africa for Sustainable Public Health Policies. This project funded by BMGF will work on three main objectives.


Increase the number of academically trained malaria modelers in sub-Saharan Africa. 

In this consortium, we will strengthen existing MSc programs via project supervision, pre-doctoral courses, and thematic workshops. Our diverse membership will add relevant, practical expertise to the existing mathematical modeling curriculum at AIMS to ensure that students are ready to address operationally relevant questions in the malaria field upon graduation. Consortium members will teach courses and jointly supervise student projects. Existing, high-quality online learning opportunities will be collated and transformed into program admission criteria. We will pilot to assure our learners are prepared to succeed. MaModAfrica learners will complete fellowships embedded within our consortia NMCPs, where possible twinned with relevant staff and policy makers in a mutually beneficial relationship.

Bridging the gap between academic modeling and operational needs. 

Conceptual and methodological gaps between modeling and public health are significant barriers to successfully developing transdisciplinary programs, inspiring reciprocal curiosity and mutually critical thinking. To overcome these barriers, MaModAfrica will deliver targeted trainings including:

  1. high-level principles of mathematical and geo-spatial modeling, aimed at promoting NMCP appreciation of analytical techniques
  2. basic principles of malaria epidemiology, biology and operational activities aimed at sensitizing modelers to real-world needs and challenges associated with the implementation of existing and new interventions.
  3. NMCP presentation and inputs to identify and prioritize key modeling questions.

Create an open, collaborative, sustainable, and transnational ecosystem of mathematical and geospatial modelers, translational scientists and decision-makers

Leveraging the experience of Malaria Consortium (MC) and Clinton Health Access Initiative (CHAI) who have worked at the intersection between implementers and modelers, we will establish a network of African disease modelers to share expertise and experience between countries. African institutes (e.g., AIMS) will collaborate with non-African partners to develop mathematical and geospatial modeling curricula and teaching resources.


The deliverables of MaModAfrica can is classified into three categories Translational Academic training, NMCP support, and Networking as described below

Translational Academic training

  • Recruit and train 8 PhD & 30 Master students
  • Curriculum in applied infectious disease modelling
  • Sandwich programs for PhD students in modelling groups from various institutions
  • Malaria training for modelers
  • Collation of existing training material
  • Online training material in 3 languages
  • Developing methodology to equip individuals with different skill sets and interests with a set of malaria modeling tools
  • Operational partners facilitating links between academics and NMCPs

NMCP support

  • Identification of NMCPs programmatic needs
  • Analytical training for NMCPs
  • PhD students seconded to NMCPs
  • Master thesis supporting NMCPs


  • Regular meetings between NMCPs and modelers within each country
  • Conference for consortium members
  • Satellite meeting with all winning consortia & others showcasing added value of modelling
  • Communication platform (eg Slack)

During year 1 we will develop curricula and administrative capacity for applied mathematical modeling divisions within AIMS that will train 30 MSc students during years 2 and 3. Within the 3-year project lifespan, we will train at least 10 PhDs in the partner countries via fellowships building on the consortium’s varied expertise (including methods such as agent-based models/Open Malaria, differential equations, spatio-temporal statistics and quantitative epidemiology applied to operational questions).

Students, experienced academic researchers and NMCP staff and partners will participate in a series of audience-specific skill development workshops with support from Center for Impact, Innovation and Capacity building for Health Information Systems and Nutrition (CIIC-HIN) (Rwanda) Malaria Consortium (MC) and Clinton Health Access Initiative (CHAI). NMCP partners will learn to critically assess modeling assumptions, input parameters, and model outputs for the purpose of policy planning and evaluation. In dialoguing with NMCP staff and partners, modelers will be exposed to operationally relevant, real-world, country-specific problems, and challenged to formalize those into modeling scenarios.

Building on existing AIMS MSc programs, we will scope the expansion of the program to other participating universities in co-creation with other bid-winning consortia. MaModAfrica will internally promote academic exchange within the consortium through online collaboration platforms, mini-conferences, academic workshops, and regular teleconference seminar series.

<strong>Training Programs</strong> 

In recent years, modeling has gained the attention of African health authorities for stratification and subnational tailoring of interventions, however opportunities to institutionalize modeling into program planning and implementation remain elusive. The contributing factors include

  1. Limited expertise in applied mathematical modeling among African academic institutions.
  2. Communication barriers between NMCPs and academics that limit application of knowledge.
  3. Lack of a network of strong academic partners based in Africa closely working with NMCPs.

We will develop transdisciplinary masters (MSc) and doctoral (PhD) academic programs, capitalizing on existing infrastructure including AIMS, independent research institutes and other universities. Notably, we will reach beyond academic training, to incite a cultural shift in educational approaches that will teach NMCPs to speak the language of data scientists while teaching academics to dissect practical, operationally relevant questions in English, French and Portuguese speaking countries.

Masters program

PhD Program

<strong>Scientific Events</strong> 

In bridging the gap between academic modeling and operational needs, we will organize various scientific events including conferences, workshops, and training schools.

<strong>Training Material</strong>