Citizen Science Tick Observations Serve as an Early Warning System for Tick-Borne Diseases

Area of Science:

• Public Health Surveillance
• Epidemiology
• Citizen Science

Background:

• Citizen science tick data is used to map infection risk indirectly.
• Direct associations between tick observations and Lyme borreliosis (LB) cases are understudied.
• This study investigates the predictive power of tick observations for LB cases in Finland.

Purpose of the Study:

• To determine if tick observations precede LB cases predictably.
• To assess if tick observations can predict peaks in LB cases.
• To evaluate the utility of citizen science data for LB surveillance.

Main Methods:

• Utilized nationwide weekly citizen science tick observation data (2021-2023).
• Analyzed Lyme borreliosis (LB) data from the Finnish Institute for Health and Welfare.
• Employed negative binomial models to assess the relationship between tick observations and LB cases.

Main Results:

• LB cases followed tick observations with a 3-4 week lag.
• Tick observations explained variation in LB cases beyond seasonality.
• Models using human-derived tick observations showed the best predictive performance.

Conclusions:

• Citizen science tick data can effectively predict LB cases.
• This enables targeted public health awareness campaigns for early LB detection and treatment.
• The findings support the establishment of tick observation services and citizen participation for early warning systems.