Using artificial intelligence for early detection of potential epidemic and pandemic outbreaks after COVID-19 in Argentina

The COVID-19 pandemic continues to be severe in Argentina. By mid-September 2020, there were 565,000 cases and 11,700 deaths due to the disease. This project seeks to lay the foundations for incorporating artificial intelligence (AI) and data science into the early detection of epidemic outbreaks like COVID-19. It will generate evidence-based preventive public health decision-making, including gendered perspectives, at the national, sub-national, and local levels. The initiative seeks to generate quality data and create the conditions for the progressive implementation of electronic health records at the provincial level.

This initiative is structured in four activities. The first aims to develop AI solutions for the early detection of infectious diseases based on existing electronic health record databases. The second activity seeks to expand the functionalities of the electronic health records system in the National Ministry of Health, which is still at an early stage of development. The third activity will implement a pilot of an expanded version of the national electronic health record system in local health centres and hospitals in vulnerable neighbourhoods, with training for health centre staff and a user awareness campaign to secure the success of the strategy. Finally, the project will focus on planning, monitoring, evaluating, disseminating, and documenting the experience. The mitigation of gender biases will be addressed through the development of models that consider fairness strategies in AI.

This work will be carried out as part of the COVID-19 Global South Artificial Intelligence and Data Innovation Program, funded by IDRC and the Swedish International Development Cooperation Agency.