Exploring Early Pre-Symptomatic Detection of Influenza Using Continuous Monitoring of Advanced Physiological Parameters during a Randomized Controlled Trial

Abstract

Early detection of influenza may improve responses against outbreaks. This study was part of a clinical study assessing the efficacy of a novel influenza vaccine, aiming to discover distinct, highly predictive patterns of pre-symptomatic illness based on changes in advanced physiological parameters using a novel wearable sensor. Participants were frequently monitored 24 h before and for nine days after the influenza challenge. Viral load was measured daily, and self-reported symptoms were collected twice a day. The Random Forest classifier model was used to classify the participants based on changes in the measured parameters. A total of 116 participants with ~3,400,000 data points were included. Changes in parameters were detected at an early stage of the disease, before the development of symptomatic illness. Heart rate, blood pressure, cardiac output, and systemic vascular resistance showed the greatest changes in the third post-exposure day, correlating with viral load. Applying the classifier model identified participants as flu-positive or negative with an accuracy of 0.81 ± 0.05 two days before major symptoms appeared. Cardiac index and diastolic blood pressure were the leading predicting factors when using data from the first and second day. This study suggests that frequent remote monitoring of advanced physiological parameters may provide early pre-symptomatic detection of flu.

Ultrasound Neuromodulation of the Spleen Has Time-Dependent Anti-Inflammatory Effect in a Pneumonia Model

“…Furthermore, ultrasound stimulation did not result in further reduction of these circulating cytokines from this low baseline level in ultrasound ( Figure 3B ) or sham-treated cohorts ( Figure 3C ) . Methods of presymptomatic or asymptomatic identification of infection in the absence of detectable changes in systemic markers, such as cytokines, is an active area of research and desirable to aid in infectious disease monitoring and control ( 54 , 55 ). Circulating concentration of the chemokine KC/GRO (i.e., rodent equivalent of CXCL1; a neutrophil chemokine) was elevated 4-hours post-infection, further elevated at 16-hours, and returned towards baseline (i.e., levels measured in the no bacteria controls) at 48 hours following infection ( Figure 3D ) .…”

Assessing the Usability of a Novel Wearable Remote Patient Monitoring Device for the Early Detection of In-Hospital Patient Deterioration: Observational Study

“…However, it seems that by further improving these EWS systems, sensitivity could be kept high, while specificity would be higher. This was not achieved yet, but preliminary data from various studies implementing big data analysis of multiple physiologic parameters collected automatically and frequently already show promise in early detection of clinically significant changes, and this could eventually result in the desired combination for future EWSs [24,31].…”

The WE SENSE study protocol: A controlled, longitudinal clinical trial on the use of wearable sensors for early detection and tracking of viral respiratory tract infections

“…Activity and physiological trackers are increasingly used globally to monitor an individual's health through continuous or frequent measurement of body functions (physiology) such as heart rate, heart rate variability (HRV), skin temperature, peripheral capillary oxygen saturation (SpO 2 ), physical activity, and indices of sleep quality. Evidence suggests that use of wearable biosensor technology may permit detection of VRTIs, and assist in medical diagnosis in the early stages of disease development - even before the onset of clinical symptoms [ [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] ] - or in state-level real-time surveillance of influenza [ 20 ]. Both of these capabilities are vital to enact timely outbreak response measures and to halt or minimize ongoing transmission.…”

“…Both of these capabilities are vital to enact timely outbreak response measures and to halt or minimize ongoing transmission. Despite promising results, previous studies of wearables for early detection of VRTIs have been mostly based on biometric data from consumer grade wearables, meaning data collection has been mostly limited to heart rate, HRV, and body temperature [ [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] ]. Prior studies have also relied heavily on patient reported symptoms and could not address asymptomatic or minimally symptomatic infections [ [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] ].…”

“…Despite promising results, previous studies of wearables for early detection of VRTIs have been mostly based on biometric data from consumer grade wearables, meaning data collection has been mostly limited to heart rate, HRV, and body temperature [ [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] ]. Prior studies have also relied heavily on patient reported symptoms and could not address asymptomatic or minimally symptomatic infections [ [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] ]. Failure to identify such infections has important public health implications in as much some SARS-CoV-2 outbreak investigations have reported that asymptomatic individuals were the source of up to 69% of infections [ 21 ].…”