As members of the E4Warning consortium, Gina Tsarouchi, Quillon Harpham (HR Wallingford), Lyra Tyson (UPF), and Remy Hoek Spaans (BSC) traveled to Sri Lanka in November to participate in a workshop organized by Dr. Lahiru Kodithuwakku and Gina Tsarouchi. The event, in collaboration with the National Dengue Control Unit (NDCU) and the Ministry of Health, focused on enhancing innovative tools for dengue prediction and control.

The workshop aimed to train participants in using the D-MOSS platform, a live dengue forecasting system combining satellite earth observation data, climate models, and statistical tools to provide probabilistic forecasts of dengue outbreaks. It also served as a valuable opportunity to adapt the methods to Sri Lanka’s unique public health context, informed by input from local professionals.

Bringing Together Experts from Across Sri Lanka

The workshop attracted over 80 participants from districts across the country, including entomologists, regional epidemiologists, medical officers of health, academics, NGOs, and representatives from the NDCU. This diverse group ensured that the discussions were enriched with practical insights and multidisciplinary expertise.

Dr. Preshila Samaraweera kicked off the workshop with an informative presentation on Sri Lanka’s progress in dengue control, highlighting current research projects and interventions. This set the stage for the D-MOSS training sessions, where participants had hands-on opportunities to test the system and provide feedback.

Training, Feedback, and Collaboration

The D-MOSS platform was well-received, with participants exploring its ability to visualize past, current, and forecasted dengue trends. One participant noted:

“These elements collectively offer a comprehensive view of past, present, and predicted dengue trends, supporting proactive planning and response.”

Following a lunch break, attendees learned about the statistical modeling methods used in E4Warning, with a focus on interpreting probabilistic forecasts. A group discussion then explored ways to enhance the dengue early warning system, including the integration of new data sources such as mobility patterns and socio-economic data. The day concluded with a presentation on the Mosquito Alert platform, sparking a lively conversation about how citizen science could contribute to vector control in Sri Lanka.

Lessons Learned and Next Steps

Reflecting on two intensive days of learning, several valuable lessons emerged from the experience. As highlighted during the workshop discussions, effective dengue control—particularly larval source management—requires a multi-sectoral approach. For example, Aedes mosquitoes often breed in artificial containers that fall under the responsibility of different sectors, such as road maintenance crews for potholes or port authorities for harbor areas.

Another critical area for improvement is the integration of entomological data into a digital infrastructure. Currently, much of this data is collected on paper, limiting its accessibility and use for coordinated control efforts. Digitizing these records would enhance monitoring, analysis, and intervention strategies.

Additionally, dengue prediction models could be further refined by incorporating mobility patterns and socio-economic census data, offering a more comprehensive understanding of how the disease spreads and where interventions could be most effective.

By continuously enhancing the digital tools developed through the E4Warning project, we aim to support the Sri Lankan National Dengue Control Unit (NDCU) in achieving its ambitious goals for dengue control and prevention.