The number of human cases of tick-borne diseases has been increasing dramatically in the last decade. While researchers in the Northeast United States (US) have developed methods to predict when and where the risk will be high, those methods are specific to only a few diseases and to only the Northeast US. We plan to develop a way to predict the risk of tick-borne diseases in the upper Midwest US, but using a method that can be applied to all tick-borne diseases and that can be adapted to new locations. First, we will use a combination of publically available data, data collected by the Midwest Center of Excellence in Vector-Borne Disease, and new data collections to predict where the ticks will be present and where the ticks will be infected. Next, we will use data from the state departments of public health to predict where people are infected by ticks. Finally, we will combine our predictions to create a single model that can predict the impact of control and prevention programs. We will repeat this process for a wide range of tick-borne diseases so that predictions can be tailored to each of the tick-borne diseases threatening human health. This addresses the fiscal year 2018 Tick-Borne Disease Research Program's Focus Area of "Prevention," specifically identification, validation, and/or improvement of tick-targeted prevention and control interventions.

Rebecca Smith has extensive experience in building these types of epidemiologic models, but she is new to the field of tick-borne diseases. This award would allow her to devote sufficient time to learn the background necessary for this type of research. She has the support of the Midwest Center of Excellence in Vector-Borne Disease and particularly the mentorship of a wide range of experts in tick-borne disease for that purpose. She will then be able to apply her experience to developing uniquely useful predictive tools.

The tools that will be produced by this research will be immediately applicable to public health professionals. We are currently developing a web-based vector-borne disease prediction platform to allow public health policy makers to view data and forecasts in real time across the Midwest. The tools produced by this research will be incorporated into this system. In addition, all the models and modeling methods will be freely available for use. That means that military and other public health professionals will be able to adapt them to new regions and new diseases. This flexible, generalizable output will have an enormous impact on the speed at which a response to tick-borne disease outbreaks can be developed.

Importantly, the results of this project will enable decision makers to improve their tick-borne disease prevention programs. The prediction models will be useful for calculating the benefit possible from any combination of control and prevention program. This is essential to decrease the risk of tick-borne diseases.