Checking tick activity in your phone

Box says ‘the tick activity for today in the Netherlands is minimal’

In 2016, we developed a model capable of predicting daily tick activity in Dutch forests. This model used observations collected by a citizen science initiative: a small group of dedicated volunteers monitored ticks once a month for over a decade, creating one of the most unique and long-term datasets of the field. I was lucky to put my hands on that dataset during my PhD, so we fitted a data-driven model to this data using a wide array of environmental variables. You can read a short description of that work here, or you can check the associated publication here.

Fortunately, this work didn’t end up in a drawer upon the conclusion of my PhD. My supervisor and our co-authors in Wageningen University & Research (WUR) got some support from the NWO’s Maps4Society cooperation programme to operationalize this model. Last week, students from HAS Hogeschool, WUR, and University of Twente finished the development of this service, which was integrated within the ecology app Nature Today so it can reach a wider audience.

As you can see in the featured image, the app shows the predicted daily tick activity in forests. One of the main new functionalities of this service, is that by coupling the existing tick activity model with a weather one (Harmonie weather forecast system) we can provide an estimation of the tick activity for tomorrow. The ability of creating these GeoHealth indicators for the general public is important to increase the awareness about health threats, which might lead into a more protective behavior while in nature. In addition, the capacity of predicting the tick activity up to several days in the future, might help public health specialists at designing prevention campaigns.

So, long story short: the tick activity research model we developed, is today a service include in a nature-related app. How cool and nerdy is that?

Irene Garcia-Marti
Irene Garcia-Marti
PhD Data Scientist

I have a keen interest in applying machine learning methods in the field of spatio-temporal analytics.