Recognition of the EM rash is crucial to early diagnosis and treatment. Improved rash recognition using deep learning methodology to prescreen patient rash photos may help prevent later serious manifestations of Lyme disease.
To our knowledge, this is the first study to explore factors which may contribute to a delay in diagnosis and treatment of Lyme disease. We identified distinct, potentially modifiable risk factors between onset of first Lyme disease symptoms and treatment. Targeting these drivers may reduce time to diagnosis and treatment and reduce the occurrence of late-stage Lyme disease complications.