AutoAI-Pandemics
Building accessible AutoML tools that let researchers across the Global South analyze, study, and respond to epidemics and pandemics without needing specialized machine learning expertise.
Lead: André Ponce de Leon Ferreira de Carvalho
Machine learning has real potential to strengthen epidemic and pandemic response, but in practice, the expertise needed to build and validate ML models is concentrated in a small number of well-resourced institutions. That imbalance means the countries and regions that are often hit hardest by outbreaks have the least direct access to the tools built to fight them.
AutoAI-Pandemics is part of the Global South AI4PEP Network, an international initiative developing automated machine learning (AutoML) tools that democratize this capability: letting epidemiologists and public health researchers build, validate, and apply ML models for outbreak analysis and control without requiring a machine learning specialist on every team. The project draws directly on LABORA's own epidemiological modeling work, including COMORBUSS, to ground these tools in realistic disease dynamics rather than generic prediction tasks.
The project is led by André Ponce de Leon Ferreira de Carvalho (ICMC-USP), with LABORA as part of the Brazilian hub of the network, contributing epidemiological modeling expertise to the collaboration.
Funding: IDRC (International Development Research Centre, Canada) and UK FCDO