By Dr. Francis Chukwuebuka Ihenetu, a Clinical Statistician and Lecturer in Microbiology.

Across Nigeria, more people are being treated for infections that just won’t go away. Not because they waited too long; but because the drugs stopped working. These are superbugs: bacteria that have become resistant to our strongest antibiotics.

It’s easy to assume this is a problem for other countries, or that it’s a future problem. But in truth, drug-resistant infections are already affecting patients here, today; from urban hospitals to rural clinics. And while this crisis is growing, Nigeria is sitting on a powerful tool we’re barely using: our own hospital data.
Every day, hospitals in Nigeria collect information like lab cultures and test results, patient records, treatment histories etc. Unfortunately, this data is often underused, mainly just stored for records instead of being put to work in predicting and preventing the next outbreak of drug resistance.

That’s where an approach called the “Bayesian modeling” comes into play. By using a method which has been effectively applied worldwide, we can use past information to improve present-day decisions. Think of it this way: if several patients in a certain ward had drug-resistant infections in recent weeks, and a new patient shows up with similar symptoms, the model uses that history to raise an alert fast.

Bayesian modeling is about updating your expectations based on new evidence. It’s something we all do instinctively. If it rained five days in a row, and the sky is grey again today, you’d probably grab an umbrella. That’s Bayesian thinking. Now imagine using that logic in medicine; helping doctors act earlier, even before lab results confirm what’s wrong.

The best part: This system doesn’t require fancy technology. It works with the data our hospitals already collect. And it doesn’t just benefit teaching hospitals; it can be applied in everyday clinics, even in resource-limited settings, where early decision-making can save lives.

Bayesian modeling is a global method for making better decisions using past information. While it wasn’t created specifically for Nigeria, applying it here could help predict and stop drug-resistant infections using existing hospital data. This approach is gaining attention in other countries, and if implemented in Nigeria, it could help shape global solutions, something the country can be proud of.

If we truly want to win the fight against superbugs, we must start using the information already in our hands. We don’t need to wait for expensive machines or imported systems. We need to believe in our own capacity to innovate – to collect, understand, and act on our data.

The answers may already be in the records. We just need to look, and act before it’s too late.