Anticipating Lyme disease hotspots can help public health officials direct resources and proactive messages to the public. But the disease environment is complex, involving many host animals, black-legged ticks that act as disease vectors, the causative agent itself, and bacteria Borrelia burgdorferiand the environment in which they all live.
The study published in Journal of Applied Ecology, untangles the relationship between two of these players in the Lyme disease environment: bacteria and the environment. Led by Tam Tran, who holds a Ph.D. in the Pennsylvania Department of Biology in the College of Arts and Sciences, and with mentors Dustin Bryson, professor in the department, Shane Jensen of The Wharton School, along with colleagues from the New York State Department of Health, the research looks at how Influence of variables such as landscape disturbance and climate on distribution and abundance B. burgdorferi. The result is a powerful analytical model that can accurately predict the prevalence and distribution of Lyme disease bacteria over landscapes, potentially a useful public health tool to help mitigate disease transmission.
“We know that Lyme disease is a growing public health threat, yet we haven’t found great ways to treat it,” says Tran, now a medical student at Virginia Commonwealth University. “The number of cases is growing.” “What’s exciting here is that by knowing how the environment affects both the tick and bacteria system, we can predict where and when there will be greater amounts of pathogens in the landscape.”
In the current study, Tran, Bryson, Jensen and colleagues focused primarily on factors that influenced B. burgdorferi, the prevalence rate that they measured by determining which part of the blacklegged tick they sampled was infected with the bacteria. Tran says that early attempts to link Lyme disease to environmental variables have yielded mixed, unclear, or sometimes even contradictory results, in part because the contributions of heavily written “environment” can be multifaceted.
To build their models, the research team took data collected from nearly 19,000 black-legged ticks between 2009 and 2018 across hundreds of sites within New York state. They assessed how numbers of infected and uninfected ticks in hundreds of sites over more than a decade matched local ecological features that fall into four broad categories:
1) landscape factors such as elevation, fire history, and distance to infrastructure such as roads;
2) numbers of vertebrate hosts, including humans, bears, birds, and deer;
3) the monitoring conditions including the local temperature and humidity at the time of collection as well as the effort devoted to sample collection; And the
4) Climate measures such as monthly averages of temperatures, precipitation, and days when temperatures are below freezing.
By running different combinations of these variables through powerful computer models, researchers can determine which of them were most influential in determining infection rates.
“The main finding was that climate was an overwhelming feature of the model,” Tran says. “Habitat disturbance was also important, and we found the opposite in some cases from previous studies.”
Whereas previous analyzes found that increases in perturbations-; Things like fires, roads cutting through forests, and fragmented habitat areas—have led to increases in B. burgdorferi By the numbers, the Pennsylvania-led team found that less disturbed and safer habitats were more often associated with greater numbers of ticks infected with the bacteria.
After developing a model with data collected in 2009-18, they then tested to see how well the model predicted the prevalence and distribution found in data collected from 2019.
“We found it was very accurate,” Tran says. “And the cool thing is that a lot of the data we used to create the model is free, which means that other sites may be able to replicate these results to help predict Lyme disease risk, especially in areas where the climate and new landscapes are similar to York.”
Tran says the interventions could be public health messages warning park visitors, for example about the risk of disease, to “remind them to get tick checks.” The findings could also help guide future land management, harnessing the power of the environment to reduce Lyme disease risk.