PhD Defence: Improving National Surveillance of Wildlife and Vector‑Borne Diseases Using Spatial Data‑Science

Summary of dissertation

Wild animals and ticks can carry pathogens that affect animals, humans and the natural environment. However, it is often not known exactly where these pathogens occur, what conditions favour their spread, and where further research is needed. This thesis investigates how spatial models can help to answer these questions.

To this end, data on wild animals, pathogens, landscape and climate were combined. Among other things, infections in roe deer, hares and red squirrels were investigated. Roe deer were found to be regularly infected with various tick-borne pathogens. In hares, several pathogens were detected, some of which were found more frequently in areas with intensive agriculture or lower temperatures. In red squirrels, infection with the parasite Toxoplasma gondii was found to cause severe inflammation and mortality. Rain and warm days appeared to increase the risk of infection.

Research was also carried out into which factors are associated with the presence of rats and mice in urban gardens. Domestic cats and the amount of green space proved to be particularly important. In addition, a map was drawn up showing where in the Netherlands the tick-borne encephalitis virus could potentially become established. This map can help to carry out targeted monitoring. Finally, research was conducted into which Dutch mammals may be most vulnerable to climate change.

The research shows that spatial models can make better use of existing data, highlight areas of risk and identify gaps in knowledge. In this way, they can contribute to smarter and more targeted monitoring of diseases in wild animals and vectors.

The ceremony will begin with a short layman’s talk. The livestream will therefore start fifteen minutes earlier.