Amber Smith, PhD, an assistant professor in the Department of Pediatrics and the Institute for the Study of Host – Pathogen Systems at the University of Tennessee Health Science Center, has received a $1.9 million grant from the National Institutes of Health (NIH) to continue to develop mathematical models to understand influenza and bacterial co-infections.
Influenza A virus is responsible for a significant number of deaths each year. What is often elusive in terms of therapy and research is the secondary infections associated with the illness, which routinely expedite the progression of the illness.
“Most people don’t think about the secondary infections that invade while someone has the flu,” Dr. Smith said. “A lot of the time, especially during influenza pandemics, people will get secondary bacterial pneumonia.”
Although first noted in the 1800’s, a retrospective study of the 1918 influenza pandemic that examined samples and historical commentary estimated that 95 percent of the people who succumbed to the illness died from a secondary infection. Among the infections discovered include pneumococcus, the bacteria responsible for conditions ranging from sinus infections to pneumonia, and Staphylococcus aureus, the bacterial cause of staph infections. These still impact influenza patients to this day, and 50 percent of the mortality during the 2009 influenza pandemic was due to bacterial co-infection. Therefore, the severity of the flu infection makes affected individuals more predisposed to other pathogens.
Dr. Smith’s project is titled “Predictive Modeling of Influenza-Pneumococcal Coinfection.”
“We use our models for a couple of things,” Dr. Smith said. “We want them to be predictive. We want to have a theoretical model on hand for when a flu pandemic occurs, so that we can predict what the chances are of developing a co-infection, how the secondary pathogens will interact with the host, how to intervene, and how successful a treatment will be.”
This methodology, which utilizes theoretical models, is frequently used in epidemiology to forecast what an epidemic might look like. Dr. Smith uses them to forecast what the infection is going to look like in each individual. They also use these models to help understand the mechanisms, specifically how the virus and the bacteria interact that make the combination so fatal.
“These two are quite difficult to tease apart in the lab,” Dr. Smith said. “You have the influenza virus doing things that the host is trying to fight, and then the bacteria come in and does other things while the host is trying to fight it. This creates an opportunity for interactions between the two pathogens.”
Dr. Smith emphasizes that the virus and bacteria can interact in ways that aren’t necessarily intuitive, making the search to find ways to control them all the more imperative.