Modelling the distribution of the tick Ixodes ricinus in England and Wales using passive surveillance data from citizen science reports
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.
Authors
- Kayleigh M. Hansford (ORCID: https://orcid.org/0000-0002-2460-6301)
- Julie Day (ORCID: https://orcid.org/0000-0003-1035-2117)
- Thomas Ward (ORCID: https://orcid.org/0000-0001-8801-747X)
- William Wint (ORCID: https://orcid.org/0000-0003-0916-0847)
- Jolyon M. Medlock (ORCID: https://orcid.org/0009-0008-9822-3697)
- Nyall Jamieson (ORCID: https://orcid.org/0009-0004-1491-6885)
- Mark Gideon Burdon (ORCID: https://orcid.org/0009-0001-0354-4332)
- Maximilian Ayling
Institutions
- University of Manchester (GB)
- University of Oxford (GB)
- UK Health Security Agency (GB)
Publication Details
- Journal
- PLoS neglected tropical diseases
- Published
- 2025-10-09
- DOI
- https://doi.org/10.1371/journal.pntd.0013520
- Citations
- 1
- Primary Topic
- Vector-borne infectious diseases
- Type
- article
- Field-Weighted Citation Impact
- 2.05