Fourier transform infrared spectroscopy (FTIR) for human infectious disease diagnosis, microbial identification and strain discrimination: a systematic review (2015–2025)

Infectious diseases remain a persistent and evolving public health challenge, driven by factors such as antimicrobial resistance, emerging pathogens and environmental changes. In this context, this systematic review aims to analyze the analytical performance of Fourier Transform Infrared Spectroscopy (FTIR) for the microbiological identification, strain discrimination and diagnosis of human infectious diseases, based on studies published between 2015 and 2025. The review followed PRISMA guidelines and included 50 articles selected from PubMed, Scopus, and ScienceDirect databases. The findings demonstrate that FTIR is a promising analytical tool for microbial discrimination, identification, and diagnosis, particularly in studies involving cultured microorganisms combined with chemometric modelling. Most studies focused on bacteria (42%) and fungi (32%), with fewer addressing viruses (20%) and protozoa (6%). Chemometric analysis played a central role in enabling FTIR applications, particularly through the integration of unsupervised methods, such as Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA), with supervised techniques like Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), and Artificial Neural Networks (ANN). Most studies aimed at microbial identification (58%) or diagnosis (14%), while 28% focused on discrimination without proposing predictive models. Overall, FTIR shows strong potential as a complementary tool for rapid diagnosis and screening of infectious diseases. However, its clinical implementation still depends on further standardization, robust validation, and the development of reliable spectral databases.