National workshop promotes integrated early warning for Rift Valley Fever in Tanzania
31/07/2025
From 14 to 18 July 2025, a national technical training and consultation workshop on the Rift Valley Fever (RVF) Early Warning Decision Support Tool (DST) was held in Bagamoyo, United Republic of Tanzania. Organized by the Food and Agriculture Organization of the United Nations (FAO) in collaboration with the Veterinary Services of the United Republic of Tanzania and national partners, the five-day event aimed to strengthen national capacities in early warning, surveillance, and coordinated response for RVF. The workshop brought over 25 experts and technical officers from public and animal health sectors, environmental and wildlife authorities, disaster management institutions, and academia.
RVF remains a significant public and animal health concern in Tanzania and across East Africa, with outbreaks closely associated with climate anomalies such as heavy rainfall and flooding. In response to this challenge, FAO developed the RVF DST—a web-based geospatial platform that integrates near real-time climate data, historical outbreak records, and expert knowledge to generate dynamic risk maps and early warning alerts. First introduced in Tanzania in 2022, the tool has supported the country’s risk-based surveillance activities, including the confirmation of RVF virus circulation in northern Tanzania in 2024 following a DST-generated risk alert.
The Bagamoyo workshop provided intensive, hands-on training on the structure, functionalities, and operational use of the RVF DST. Participants engaged in live demonstrations, practical exercises, and group simulations using Tanzania-specific datasets to analyze historical outbreaks, monitor environmental indicators, forecast future risk, and interpret DST outputs for decision-making. The training also featured a field visit to a livestock farm in the Bagamoyo area, where participants validated the DST’s current risk prediction and collected livestock samples for laboratory analysis. Samples from cattle, sheep, and goats were submitted to the Tanzania Veterinary Laboratory Agency (TVLA) for IgG and IgM diagnostic testing, illustrating the link between digital risk forecasting and on-the-ground surveillance.
The final part of the workshop transitioned into a national consultation designed to foster institutional ownership of the RVF DST. Stakeholders worked together to develop a roadmap for integrating the tool into existing surveillance and response frameworks. Discussions emphasized the need for stronger cross-sectoral data sharing under the One Health approach and proposed enhancements such as offline access, mobile compatibility, better user support materials, and expanded coverage to include other priority zoonoses like anthrax, rabies, and brucellosis. Participants also agreed on the importance of establishing a Community of Practice and conducting quarterly virtual trainings to sustain momentum and strengthen national capacities.
Participants also discussed the integration of FAO–Intergovernmental Authority on Development (IGAD) joint alerts, interoperability with national data platforms, and institutionalization of the DST within ministries, training curricula, and emergency preparedness plans. Feedback gathered during the workshop informed recommendations for tool improvement.
The workshop demonstrated how near real-time modelling, risk forecasting and digital innovation can enhance preparedness and anticipatory actions.
RVF remains a significant public and animal health concern in Tanzania and across East Africa, with outbreaks closely associated with climate anomalies such as heavy rainfall and flooding. In response to this challenge, FAO developed the RVF DST—a web-based geospatial platform that integrates near real-time climate data, historical outbreak records, and expert knowledge to generate dynamic risk maps and early warning alerts. First introduced in Tanzania in 2022, the tool has supported the country’s risk-based surveillance activities, including the confirmation of RVF virus circulation in northern Tanzania in 2024 following a DST-generated risk alert.
The Bagamoyo workshop provided intensive, hands-on training on the structure, functionalities, and operational use of the RVF DST. Participants engaged in live demonstrations, practical exercises, and group simulations using Tanzania-specific datasets to analyze historical outbreaks, monitor environmental indicators, forecast future risk, and interpret DST outputs for decision-making. The training also featured a field visit to a livestock farm in the Bagamoyo area, where participants validated the DST’s current risk prediction and collected livestock samples for laboratory analysis. Samples from cattle, sheep, and goats were submitted to the Tanzania Veterinary Laboratory Agency (TVLA) for IgG and IgM diagnostic testing, illustrating the link between digital risk forecasting and on-the-ground surveillance.
The final part of the workshop transitioned into a national consultation designed to foster institutional ownership of the RVF DST. Stakeholders worked together to develop a roadmap for integrating the tool into existing surveillance and response frameworks. Discussions emphasized the need for stronger cross-sectoral data sharing under the One Health approach and proposed enhancements such as offline access, mobile compatibility, better user support materials, and expanded coverage to include other priority zoonoses like anthrax, rabies, and brucellosis. Participants also agreed on the importance of establishing a Community of Practice and conducting quarterly virtual trainings to sustain momentum and strengthen national capacities.
Participants also discussed the integration of FAO–Intergovernmental Authority on Development (IGAD) joint alerts, interoperability with national data platforms, and institutionalization of the DST within ministries, training curricula, and emergency preparedness plans. Feedback gathered during the workshop informed recommendations for tool improvement.
The workshop demonstrated how near real-time modelling, risk forecasting and digital innovation can enhance preparedness and anticipatory actions.