In contrast to traditional approaches, the project uses drone imagery to identify habitats in which ticks—and thus potential infection hotspots—are particularly likely to occur. In collaboration with experts in entomology, insights into the spread of vectors and pathogens are refined in order to improve model accuracy. Machine-learning algorithms are used for modelling, and weather data are integrated to account for the effects of climate on tick populations.

In a model region considered a hotspot for tick-borne encephalitis (TBE) and Lyme disease, voluntary participants will be invited in later project phases to take part in a blood test (serological study). Dried blood spot (DBS) self-tests will be used to determine how many people already have antibodies against the pathogens. This makes it possible to identify previously undetected infections and improve the available data. At the same time, predictions about the locations of infection hotspots will be validated through field studies.

“At its core, HABITRACK focuses on a pipeline for pandemic preparedness. TBE and Lyme disease serve as proof-of-concept,” summarizes researcher Prof. Dr. Noemi Castelletti.

The MONID-HABITRACK project is funded by the Federal Ministry of Research, Technology and Space (BMFTR) under the funding code 031L0326A and is also part of the BMFTR-funded research network MONID (Modeling Network for Major Infectious Diseases).