Co-developing a climate-driven Meningitis Early Warning System for Africa

Oral Presentation 

Approximately 300 million people in sub-Saharan Africa are vulnerable to dry-season meningitis outbreaks. Such outbreaks are favoured during hot, dry and dusty conditions. During the GCRF African SWIFT project, sub-seasonal atmospheric forecasts of these conditions were used to collaboratively co-produce a climate-driven Meningitis Early Warning System (MEWS) for Africa with in-region institutions (ACMAD, WHO/AFRO). Through iterative dialogue within these existing collaborative partnerships, the environmental conditions used to predict Meningitis outbreaks have been revisited and co-defined to ensure they are appropriate. By moving beyond the ensemble mean forecast of these conditions, this work will show the impact of incorporating probabilistic information about forecast uncertainty. Specifically, we explore the relative sensitivity of the different meteorological variables to their thresholds, as well as assess the ability of multiple subseasonal forecasting systems to effectively reproduce and predict these key atmospheric conditions. 

The aim is to improve the underlying climate information being applied to produce a more reliable and actionable early warning system which addresses both impact and likelihood of Meningitis outbreaks. Crucially, the visualisation and communication of these products is being co-developed with in-region partner institutions to ensure they are useful, usable and used and can be sustainably operationalised to support improved decision-making that will lead to better distribution of medical resources across sub-Saharan Africa, and ultimately save lives and support resilient livelihoods for all.