Modelling the distribution of the tick Ixodes ricinus in England and Wales using passive surveillance data from citizen science reports

Abstract

Background Ticks are a significant cause of illness globally. The tick Ixodes ricinus is commonly found across Europe and is a significant vector of Tick-Borne Encephalitis virus (TBEv), Borrelia burgdorferi s.l. (causative agent of Lyme borreliosis), Babesia divergens, Anaplasma phagocytophilum, and several Rickettsia bacteria, among others. Methods The Tick Surveillance Scheme (TSS) administered by the UK Health Security Agency (UKHSA) contains validated reports from the general public of tick encounters over the last twenty years. We modelled the probability of I. ricinus tick presence across England and Wales using the locations of TSS reports from 2013 to 2023 and a combination of biotic and abiotic factors. An ensemble of statistical and machine learning models was trained to classify points as presence (true tick report locations) or background (points generated randomly and by target-group sampling). Results The ensemble model had a continuous Boyce index of 0.99 and area under the receiver-operator curve (ROC AUC) of 0.84 on out-of-sample 2024 data. Variables relating to roe deer (Capreolus capreolus) distribution and land cover type were most important. Most of southern England, as well as other areas with known tick populations such as the New Forest and the Lake District, are modelled as highly probable tick presence areas. Interpretation Unstructured citizen science data was suitable for creating a high-performing species distribution model for I. ricinus after addressing spatial and demographic biases. This model is now being used to inform local public health awareness showing the advantage of passive surveillance through to modelling and public health awareness.