Mapping Lyme disease out west: Human Lyme disease infections linked to ecological factors across California

Tick bites transmit Lyme disease. But even knowing where these ticks live doesn’t necessarily mean you can predict the disease in humans. It’s only one part of a broader picture which includes human behavior and the habits of the parasite’s carriers.

Researchers at UC Santa Barbara have discovered that the ecology of the small mammals upon which ticks feed can explain rates of human Lyme disease, at least in California. As a result, scientists and health officials may be able to predict future disease risk by studying the response of these animals, and their tick parasites, to changing climate and land use. The findings appear in the journal Environmental Research Letters.

“This study is unique because it tries to quantify the links connecting climate to mammals to ticks to humans, which requires different types of data, research techniques and academic backgrounds,” said co-author Sam Sambado, a doctoral student in the Department of Ecology, Evolution, and Marine Biology.

Lyme disease is primarily caused by the bacterium Borrelia burgdorferi by way of tick bites. However, the western blacklegged tick isn’t born with the bacterium. It can only contract the pathogen by feeding on an infected host, which serves as a reservoir for the microbe.

The ecology of the tick’s hosts should affect the distribution of the disease in humans, but the connection isn’t always straightforward. “It’s challenging to link the ecology to the epidemiology — or where people get sick — because humans change their behavior based on risk,” said first author Andy MacDonald, an assistant professor at the Bren School of Environmental Science & Management. Where people go, how they interact with the landscape, and whether they take precautions against tick bites all influence where people contract Lyme disease.

The researchers had two questions in mind. First, what environmental factors affect the infection rate in tick populations? Second, can this knowledge be used to predict human infections?

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