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Maps of Ixodes ricinus distribution and maps depicting tick bite risk are essential for government and health organisations to target prevention and control strategies for tick-borne diseases. However, researchers often lack robust long-term and geographically extensive tick distribution data, and information about human exposure to ticks to measure risk. Citizen science projects, through the collective effort of many volunteers, have the potential to provide valuable data on tick bite risk and tick distribution, but are often based on opportunistic submission of reports. The overarching aim of this study was to assess methodologies to improve public health decision-making through distribution mapping of ticks and tick bite risk for Scotland. Research was undertaken to: compare the quality and robustness of predictive mapping with the three types of tick data most often used for predictive mapping; use statistical approaches to improve the quality of predictions of the distribution of I. ricinus in Scotland, including the predicted uncertainty; assess whether questing tick surveys reflect human-tick encounter risk; and finally, test the feasibility of a new citizen science approach to assess human risk of tick encounters. Analysis of the three existing datasets with I. ricinus distribution in Scotland showed that whereas data from questing tick surveys generate detailed predictive maps at local scale, at the country level, predictions were affected by poor data coverage. Additionally, dissimilarities in the predicted distribution pattern of I. ricinus between data from passive submission and from questing tick surveys were identified. This suggests the need for data from public submissions to gather information on absences and to account for volunteer effort. A predictive map of I. ricinus distribution in Scotland developed with a sophisticated Bayesian statistical technique (the stochastic partial differential equation (SPDE)) which accounted for several sources of variation was successful in improving the predictions in areas with poor data coverage, and the associated uncertainty. The relationship between questing tick surveys and human tick bite rate was then assessed. Questing tick surveys were carried out whilst collecting contemporaneous data on tick encounters from orienteers running the same areas in 11 events at world, national, regional and local orienteering events. This novel approach found that questing tick surveys are a good indicator of tick bite risk. Also, the number of people multiplied by the hours of exposure is the most meaningful denominator for human exposure to tick bites (correlation coefficient with questing tick abundance of 0.8, p=0.0052). From 340 reports from orienteers recorded across all events, a mean incidence of 409 tick bites per 1,000 person-hours exposure was recorded. Significant correlations were found between tick bite rate and temperature on the event day, the proportion of pastures around the track used by orienteers and the start time of the activity. A citizen science project was implemented in Scotland between May and November 2018 and again between March and November 2019. The project used a novel approach that included collection of denominator data (number of people exposed, and time spent) and additionally asked people to report both when they did, and importantly, when they did not encounter ticks. Tick bite and tick encounter rates calculated from participant reports were compared with predictions of questing tick abundance in two study areas, Lochaber and the Cairngorms using data collected from questing tick surveys. A total of 1,914 reports from 65 volunteers were received, with 231 and 118 reports received, respectively, from the Cairngorms and Lochaber areas. On average, the Cairngorms area registered 0.083 tick bites per person per hour of activity and 0.268 tick encounters per person per hour. Lochaber area registered 0.018 tick bites and 0.028 tick encounters per person per hour. Tick bite and tick encounter rates in the Cairngorms correlated better with predicted tick abundance in the area (correlation coefficient of 0.27 and 0.31, respectively) compared to Lochaber (correlation coefficient of 0.15 in both cases). Tick bite and tick encounter rates were found to depend both on questing tick abundance, and on factors related to human activity and behaviour. Type of human activity explained more variation in tick bite rate than questing tick abundance. Tick bite and tick encounter rates were quantified by activity type. These findings are valuable in identifying high risk activities and targeting public health messages. This study resulted in new methodologies to improve predictive mapping of ticks, and better understanding of tick bite risk and the factors that drive it, with the overall aim of improving control and prevention of tick-borne diseases.