EGU25-19944, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-19944
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Co-creating a trigger model for cholera anticipatory action in Cameroon
Marc van den Homberg1,2, Mélanie Drooglever Fortuyn1, Jacopo Margutti1, Mathilde Duchemin3, Gaoussou Drame3, Cyrille Ewane Ngando4, Anne-Laure Maillard5, and Pascal Crépey5
Marc van den Homberg et al.
  • 1510 an initiative of the Netherlands Red Cross, Rotterdam, Netherlands (mvandenhomberg@redcross.nl)
  • 2Faculty of Geo-Information Science and Earth Observation/ITC, University of Twente
  • 3Croix-Rouge française
  • 4Croix-Rouge camerounaise
  • 5EHESP, Université de Rennes, CNRS

Anticipatory action (AA) refers to actions taken by humanitarian actors and governments to reduce the humanitarian impacts of a forecasted hazard before it occurs. To date, most AA initiatives have focused on hydrometeorological events, but initiatives for in particular climate-sensitive diseases are gaining traction. Acting ahead of a disease outbreak or controlling an epidemic early on can significantly reduce the impacts. Cameroon has experienced recurrent cholera epidemics since 1971. The Cameroon Red Cross has been working with the French Red Cross, technical partners (510 an initiative of the Netherlands Red Cross and EHESP), and in-country actors such as the Ministry of Health to co-create an Early Action Protocol (EAP) for cholera.  An EAP contains a model that triggers early actions once a certain forecast or observation reaches a threshold that indicates there could be severe negative impacts corresponding to a one-in-five-year return period. Cholera is a water-borne disease, where climatic, environmental, and socio-economic factors contribute to its risk. The development of a trigger model requires historical data on these factors, but this data is often difficult to obtain or not available with sufficient spatial and temporal resolution. Also, for an operational trigger model, the input data of the trigger model has to be available in near-real time. A data-sharing agreement with the Ministry of Health was put in place to get access to the sensitive cholera incidence data. Correlation analyses between daily rainfall (as floods impact WASH infrastructure) and cholera case data were done for delays between 7 to 14 days, as it is known from the literature that the first cholera cases usually occur after a few days of flooding. However, only very weak correlations were found. A moving average of rainfall over 50 mm/day for four consecutive days did correspond to a significant number of cholera cases. The trigger model proposed relies only on observed data and consists of two parts. Trigger 1 is a climatic trigger that triggers when a district experiences flooding with over 2000 people affected or when it experiences 4 days with an average daily rainfall of at least 50 mm. Trigger 2 goes off whenever at least 5 suspected cases or 1 confirmed cholera case are identified through community-based or national surveillance systems. To activate trigger 2, trigger 1 must already have been activated. The next steps will include gaining experience with activations with this protocol, while also, from a research point of view, evolving the trigger model once more data on the cholera risk factors becomes available.

How to cite: van den Homberg, M., Drooglever Fortuyn, M., Margutti, J., Duchemin, M., Drame, G., Ewane Ngando, C., Maillard, A.-L., and Crépey, P.: Co-creating a trigger model for cholera anticipatory action in Cameroon, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19944, https://doi.org/10.5194/egusphere-egu25-19944, 2025.