Additional information about this study can be found through Grand Challenges Canada on this webpage.

In young babies, bacterial infections cause severe illness and are often life-threatening. To avoid a catastrophic outcome, doctors depend on their experience and blood tests to determine the type of infection, whether it is from a bacteria or not, but despite these tests identifying a critically ill baby can be challenging, especially given the lack of diagnostic and monitoring technologies in low- and middle-income countries.

Our goal is to develop a decision algorithm that integrates clinical data to identify which baby needs immediate antibiotic treatment when a severe infection is suspected, based on their chance of having a bacterial infection and of becoming imminently ill from that infection. To fine-tune our prediction model, we will use a customized blood test that has higher accuracy in confirming the type of infection. Our long-term goal is to use this prediction algorithm to develop a smart phone app that intelligently interprets clinical information including vital sign measures to help doctors make the right treatment decisions in babies with infections, promptly and while avoiding errors.