Measurement Errors and Decisional Criteria to Detect Subjects Suspected Having SARS-CoV by Thermography

The COVID-19 pandemic was spread in the world. Diffusion started in China at the end of 2019 and has involved the whole planet on 2020. The world found itself unprepared to face the pandemic. Preliminary detection of subjects suspected of having Coronavirus was a peremptory task to counter the spread of the virus. Authorities, scientists and clinicians were challenging to define mass screening and diagnostic tools for early disease detection. Thermography was a wide-spreading technique used in airport, railway station and access points for mass detection of potential subjects affected by COVID-19 or, in general, by SARS-CoV. However, thermography, like any sensing technique, is affected by uncertainty contributions and measurement errors which are cause of poorly reliable results. Consequently, false-positive and falsenegative cases may occur. This manuscript aims to highlight the limitations of this technology by disclosing the experimental studies carried out about the most common errors due to the incorrect use of thermography. Quantitative evaluation of the effects of such errors on measurement results is here reported so to prove the topic relevance. Parameters definition and decisional criteria are here proposed to increase the detection accuracy of subjects suspected having SARS-CoV infection. An approach based on uncertainty evaluation is described to overcome the current limitations so to make the use of thermography reliable.