Using maths to combat bacterial infections 🦠

Let’s suppose you eat some undercooked meat 🍗 or drink some contaminated water🥛 by mistake. You might be fine, you might feel a bit sick for a few days but get better, but (if you are unlucky) you might have to go to the hospital and have a course of antibiotics 💊.

Let’s talk about what happens inside your body when you get a bacterial infection. Your body recognises the bacteria as an ‘enemy’ and so produces chemicals that attract cells called white blood cells. Once white blood cells reach the bacteria, they engulf (eat) the bacteria until the infection is defeated (cleared). If the white blood cells can’t do this on their own, then antibiotics can help by either killing the bacteria or preventing them from replicating. Many types of bacteria, however, have some tricks up their sleeves to prevent such an easy defeat👊🏼. For example, certain types of E. coli are able to hide from the immune system. The details of how the immune system interacts with bacteria is not always well understood…this is where maths comes to the rescue!🎉

We can model an infection by writing mathematical equations and algorithms (rules) that describe what happens in the infection, based on what we already know about the biology 🧬. For example, we could say that white blood cells move around randomly until some of those chemicals show up, and then the white blood cells would move in the general direction of the bacteria. Once we have made our model, we then ‘press play▶️’ to watch a simulation of the infection. Incorporating the impact of different antibiotic strategies on the rate of infection clearance in these simulations, can help us to decide which strategies are best.

These models can even be used to test the ability of made up drugs and strategies to clear infections (which is clearly much safer than testing these on people!). Using maths also saves on much of the money 💵 and time ⏰ that would be spent in doing physical experiments 🧫.

Research on this topic was undertaken by James Preston during his PhD at the University of Nottingham🙌🏻

#appliedmathematics #bacteria #mathmodeling #mathsinlife #antibiotics #scicomm

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