Predictive modelling and forecasting of the transmission of COVID-19 in Africa using artificial intelligence

Different phases of the COVID-19 pandemic present governments and decision-makers across low- and middle-income countries with distinct challenges. While lockdowns and containment strategies show relative success in curbing the spread of COVID-19, the crippling socioeconomic impacts have put pressure on African governments to relax these public health measures. Integrating the power of artificial intelligence, predictive modelling, and simulations, this project supports data-driven decision-making to prevent and control the COVID-19 pandemic in Africa. It builds on a COVID-19 dashboard and transmission models that have been widely adopted by governments and international organizations. The project will develop modelling tools and simulation dashboards relevant to local health authorities to mitigate the impact of subsequent waves of infection. In addition, these tools will enable the researchers to evaluate the relative effectiveness and potential biases of public health interventions while accounting for local feasibility, cost, and socio-economic impact. Equity considerations are central to both project design and implementation, including active engagement with local communities and high-resolution indicators that incorporate the disproportionate impact of the pandemic on marginalized populations like women, rural communities, and informal workers. Communication strategies with local stakeholders will address dis- and misinformation about COVID-19 prevention and treatment. 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. 'ÄÉ