Infrared thermal imaging (IRI) is a contact-less technology able to monitor human skin temperature for biomedical applications and in real-life contexts . Its capacity to detect fever was exploited for mass screening during past epidemic emergencies as well as for the current COVID-19 pandemic . However, the only assessment of fever may not be selective for the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection . Hence, novel approaches for IRI data analysis have been investigated . The present review aims to describe how IRI have been employed during the last epidemics, highlighting the potentialities and the limitations of this technology to contain the contagions . Specifically, the methods employed for automatic face recognition and fever assessment and IRI ’ s performances in mass screening at airports and hospitals are reviewed . Moreover, an overview of novel machine learning methods for IRI data analysis, aimed to identify respiratory diseases, is provided . In addition, IRI-based smart technologies developed to support the healthcare during the COVID-19 pandemic are described . Finally, relevant guidelines to fully exploit IRI for COVID-19 identification are defined, to improve the effectiveness of IRI in the detection of the SARS-CoV-2 infection.