According to the World Health Organization, Tuberculosis (Mycobacterium tuberculosis or TB) will kill two million people this year, with the projected number of new infections over the next twenty years reaching a billion. A rapidly moving, constantly mutating disease, TB’s effects are made worse by its ability to quickly react to new drug treatments, becoming resistant to antibiotics. Searching for a way to improve treatment, a group of researchers from the University of Tennessee developed a model to determine the most effective way of managing the bacteria’s resistance.
Drug cycling is one of many drug use policies that can be applied to treat illness and manage the resistance of viruses and bacteria. Depending on when a person becomes infected, they are placed in a group to receive a particular drug treatment. Groups infected later or earlier are treated with different drugs. Mathematical model results support that cycling is potentially useful as a tool for controlling the resistance of pathogens such as Tuberculosis.
“Tuberculosis resistance is not just an issue to minimize locally; it’s a global concern,” says Scott Duke-Sylvester, one of the researchers who will present the group’s work at the Modeling session during the Ecological Society of America’s Annual Meeting.
Annie Drinkard | EurekAlert!
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