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Friday, June 14, 2024

Antibiotic 'weather' maps predict antibiotic effectiveness

Radar maps are a key feature in the weather forecast industry, used for displaying weather data in specific regions, utilizing color and symbols to do so. At the UW-Madison School of Pharmacy, they are repurposing the elegant concept of the weather map to soon provide vital information for healthcare providers.

The atmosphere changes rapidly and simple indicators on a map can communicate weather progression. Laurel Legenza, a Comparative Health Systems Global Pharmacy Fellow, has found that antibiotic resistance can be communicated the same way.

“We’re collecting antibiotic resistance data. The idea is that we want this data to be more easy to read. Currently it’s usually accessed in the form of a table where it just shows numbers and percents,” Legenza said, who started the project at the beginning of her fellowship in 2015 with the School of Pharmacy, along with associate professors Warren Rose and Susanne Barnett.

Much like how a weather map shows the percent chance that it might rain, these antibiotic resistance maps will show the percent chance that an antibiotic will be effective.

Microbes are continuously developing resistance to current treatments, and this mapping project will soon be an important element for doctors treating patients with infection. Healthcare professionals will be able to look at the maps and judge which antibiotics will work and which might not, based on where the patient is from. The first featured bacterium will be E. coli, but more infectious agents will be added in the future to treat a wider range of illnesses.

Antibiotic resistance maps will also provide more insight into factors affecting antibiotic resistance activity, as well as shed light on future movement patterns of antibiotic resistance. To do this, Legenza is asking more than just where antibiotic resistance is.

“Where is it changing? And then the next question is why is it changing? Can we use those three different factors to build a predictive model that might help a provider make a decision?”

These maps could also reveal phenomena such as geographical correlations that researchers could benefit from. For example, a socioeconomic landscape could have an influence on resistance against antibiotics. Rural versus urban areas or communities near bodies of water could exhibit varied behaviors of microbes and determine how quickly they are able to adapt to medical treatments.

“Currently we’re building partnerships with health systems in Wisconsin to create an environment where we can share a higher resolution of data to make more specific mapping. Right now, we have data that’s aggregated at a county level, but we want to look at it more detailed to be able to see variations even in a large city,” Legenza said.

These maps will be an engaging visual to explain the science behind microbes and antibiotics, while creating a promising solution to make resistance against antibiotics easier to interpret. Soon enough, personalizing medicine in this way will help improve patient outcomes by pinpointing the best course of action to treat infection.

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