Imagine trying to stop a fire by tracking not just the flames, but also the wind and the dry grass that spreads it. This work tracks how Mpox moves between people, animals, and even the air and water in border regions. By mapping these hidden paths, it helps health teams predict where the next outbreak will hit before it happens.
Public health agencies lack precise data on how Mpox spreads between animals and humans in border regions. This gap makes it impossible to predict outbreaks or deploy targeted interventions effectively.
A surveillance system combining RT-PCR diagnostics, metagenomic sequencing, and spatiotemporal risk models. It includes a database of human, animal, and environmental samples to map transmission routes.
If you are a test kit manufacturer dealing with low detection rates in remote areas — this project developed new diagnostics and sampling methods that identified 54 positive human cases and 9 positive air samples. This provides a blueprint for high-sensitivity field tests.
If you are an insurer dealing with unpredictable epidemic costs — this project developed spatiotemporal risk and transmission models. These tools allow for better prediction of future outbreaks to manage risk and resource allocation.
If you are a monitoring firm dealing with the need for early warning systems — this project analyzed 75 wastewater samples to trace virus spread. This proves the viability of using sewage as a non-invasive early warning system for Mpox.
Based on available project data, there is no information regarding the specific cost or pricing of the diagnostics developed.
The project demonstrates scalability by collecting samples from 2,366 people and various environmental sources across two countries, suggesting the methods can be expanded to larger regional scales.
Based on available project data, there is no mention of patents or specific licensing terms for the spatiotemporal risk models.
The project focuses on strengthening public health response and sharing surveillance data with health workers in DRC and RoC to support official public health initiatives.
The project period runs from 2024-10-01 to 2026-09-30, indicating that the final models and data will be fully available by September 2026.
The consortium consists of 5 partners across 4 countries (CD, CG, ES, IT). It is heavily weighted toward non-commercial entities, with 1 university, 2 research organizations, and 2 other organizations. There are 0 industry partners and 0 SMEs, indicating the project is currently driven by academic and public health goals rather than immediate commercialization.
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