2 September 2021, Rome- Rift Valley fever (RVF) is a severe zoonotic, viral, vector-borne disease representing a threat to human health, animal health and livestock production. Especially in East Africa, this epidemic is worsened during the warm phase of the El Niño/Southern Oscillation phenomenon, when heavy rainfall and flooding cause mass hatching of infected mosquito eggs, thus influencing the risk of disease emergence, transmission and spread.

To strengthen capacities of veterinary services staff in RVF environmental monitoring and forecasting, FAO, in collaboration with the Veterinary Services of Kenya, Uganda and the United Republic of Tanzania, carried out an online training on the RVF  Decision Support Tool (DST) . As a practical web-based tool, the RVF DST integrates near real-time RVF risk maps with geospatial data, RVF historical and current disease events and expert knowledge on RVF eco-epidemiology.

“The Early Warning Decision Support Tool allows us to monitor the evolution of RVF in any part of a country that joins the initiative, and this with just a mouse click, enabling RVF affected countries to take pre-emptive decisions to mitigate RVF risk and save lives,” highlighted Jeffrey Gilbert, the Coordinator for FAO’s Emergency Centre for Transboundary Animal Diseases (ECTAD).

Improving national capacities for better RVF preparedness

Attended by 14 national experts responsible for animal and public health surveillance and six FAO epidemiologists from the three participating countries (with Ethiopia attending as an observer), the training included a wide range of components such as interactive discussions and the experts' comprehensive presentations that aimed at strengthening countries’ capacities for early warning and improving and real-time information sharing for RVF. RVF poses a serious threat in many parts of the globe, including the Near East and potentially in Europe and other regions. However, given the current impact of the disease and its severe implications in Africa, it was important that the continent was the first target of this training.  

Therefore, the objectives of the training were threefold, including: initiating knowledge transfer on how to use the tool to the national experts on the RVF DST sharing practical field experience and ideas among experts involved in RVF risk mitigation, including preparedness and response activities and promoting technical cooperation among the trainees at the regional and country levels. The training also provided all the participants with an opportunity to spot areas for improvement to ensure more accurate and efficient forecasting of RVF outbreaks.

About the Rift Valley Fever Early Warning Decision Support Tool

Monitoring, detecting and forecasting climate anomalies using near real-time satellite-based climate and vegetation data constitute useful solutions to control RVF and other emerging infectious diseases. Given this context, FAO has harnessed the potential of these new approaches, and technologies to improve early detection and forecasting of disease threats. The RVF DST generates real-time RVF risk maps using historical and current disease events from the EMPRES Global Animal Disease Information System (EMPRES-i), expert knowledge on RVF eco epidemiology and  geospatial data accessed from the online FAO Hand-in-Hand (HIH) geospatial data platform. This enables rapid decision support for improved preparedness and early response. ´´The integration of geospatial data is key to provide decision-makers with near real-time data to produce comprehensive RVF risk maps and assessments´´ says Karl Morteo, FAO Information Technology officer from the Digitalization and Informatics Division. In July 2020, the RVF DST was piloted in three RVF endemic countries in East Africa – Kenya, Uganda and the United Republic of Tanzania. ´´With the RVF-DST, the Veterinary Services in the region have attained a milestone in the fight against the disease’’ adds S.J. Muchina Munyua, Director from the Intergovernmental Authority on Development (IGAD)/ICPALD (Centre for Pastoral Areas and Livestock Development) in Nairobi.

The way forward

Leveraging the experience of this first training, the next steps will be to conduct trainings at country level, involving national and subnational experts involved in animal and public health surveillance, having meetings at country level to provide more data and information that can help to improve the precision of the RVF DST and finally looking to expand the tool to Ethiopia, Mozambique, South Sudan and the Sudan, with more trainings planned at the country level from October.