Exploring the roles of seasonality and demography in tick borne disease dynamics

Abstract

Pathogens in nature provide a fascinating lens for studying connections in an ecosystem. Tracing the movement of a pathogen between species and populations is like following a thread that ties together pieces of a tapestry. Lyme disease, a bacterial infection spread by tick bites, is a particularly interesting study system because it is very complex. The ticks that spread Lyme disease feed on a broad diversity of wildlife, many of which can be hosts for disease-causing bacteria. Recent changes in climate, land use, and wildlife communities have resulted in a rapid increase both in the number and geographic spread of Lyme disease cases. The rapid spread of disease presents both a pressing environmental and public health concern. In my research, I used surveillance data to explore Lyme disease trends. I found that children and youth get sick about four weeks earlier than adults. I also found that the timing of Lyme disease cases is now around six weeks earlier than 25 years ago. To understand why cases are happening earlier, I developed a mathematical model that simulates bacteria transmission between ticks and bank voles. This model can help us understand how wildlife population dynamics influence disease outcomes.