Abstract

Infrared thermographs (IRTs) implemented according to standardized best practices have shown strong potential for detecting elevated body temperatures (EBT), which may be useful in clinical settings and during infectious disease epidemics. However, optimal IRT calibration methods have not been established and the clinical performance of these devices relative to the more common non-contact infrared thermometers (NCITs) remains unclear. In addition to confirming the findings of our preliminary analysis of clinical study results, the primary intent of this study was to compare methods for IRT calibration and identify best practices for assessing the performance of IRTs intended to detect EBT. A key secondary aim was to compare IRT clinical accuracy to that of NCITs. We performed a clinical thermographic imaging study of more than 1000 subjects, acquiring temperature data from several facial locations that, along with reference oral temperatures, were used to calibrate two IRT systems based on seven different regression methods. Oral temperatures imputed from facial data were used to evaluate IRT clinical accuracy based on metrics such as clinical bias (), repeatability, root-mean-square difference, and sensitivity/specificity. We proposed several calibration approaches designed to account for the non-uniform data density across the temperature range and a constant offset approach tended to show better ability to detect EBT. As in our prior study, inner canthi or full-face maximum temperatures provided the highest clinical accuracy. With an optimal calibration approach, these methods achieved a between ±0.03 °C with standard deviation () less than 0.3 °C, and sensitivity/specificity between 84% and 94%. Results of forehead-center measurements with NCITs or IRTs indicated reduced performance. An analysis of the complete clinical data set confirms the essential findings of our preliminary evaluation, with minor differences. Our findings provide novel insights into methods and metrics for the clinical accuracy assessment of IRTs. Furthermore, our results indicate that calibration approaches providing the highest clinical accuracy in the 37–38.5 °C range may be most effective for measuring EBT. While device performance depends on many factors, IRTs can provide superior performance to NCITs.

Highlights

  • Fever is a key symptom of many infectious diseases that have produced epidemics, including Severe Acute Respiratory Syndrome (SARS) in 2003, Influenza A (H1N1) in 2009, Ebola Virus Disease (EVD) in 2014, and Coronavirus (COVID-19) in 2019–present [1,2,3,4,5,6].While fever screening alone is not an effective method to stop an epidemic, it is likely that for many infectious diseases it can be part of a larger approach to risk management

  • In our recent prior article [41], we provided an initial analysis of our clinical study data, focusing on the 596 subjects measured within the room temperature range of 20–24 ◦ C

  • Current findings on Infrared thermographs (IRTs) diagnostic performance were generally consistent with our prior analysis of results from 500 subjects, indicating IRTs have a strong potential for achieving high sensitivity and specificity in the detection of elevated body temperatures (EBT)

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Summary

Introduction

Fever is a key symptom of many infectious diseases that have produced epidemics, including Severe Acute Respiratory Syndrome (SARS) in 2003, Influenza A (H1N1) in 2009, Ebola Virus Disease (EVD) in 2014, and Coronavirus (COVID-19) in 2019–present [1,2,3,4,5,6].While fever screening alone is not an effective method to stop an epidemic, it is likely that for many infectious diseases it can be part of a larger approach to risk management. Fever screening has been used in high-traffic areas and at the entrances of high-risk sites, such as public transportation hubs, hospitals, and assisted living facilities, yet there is little evidence that this approach has made a significant impact [7]. This may be due in part to the implementation of ineffective instrumentation and calibration algorithms, as well as a lack of viable, consistently applied standard procedures for deployment and screening. Body temperature can be measured at different body sites. The site where the temperature is acquired is called the measurement site, whereas the site to which the device output temperature refers is called the reference site

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