Signature of SARS-CoV-2 Vaccine Response From 3D Cartography of Heart Rate Variability

Digital Health Technologies (DHT) enable continuous measurement of physiological data like heart rate, skin temperature (SkT), and activity levels. DHT-based characterization of SARS-CoV-2 vaccine-induced inflammatory response and systemic reactogenicity (fever, malaise, chills, joint pain) might allow assessment of vaccine safety and efficacy. Our objective: is to compare DHT-derived vaccine response patterns between participants demonstrating a post-vaccine increase in temperature and experiencing systemic reactogenicity (group-1) to those reporting no systemic reactogenicity and/or exhibiting limited temperature change (group-2) after receiving the second dose of SARS-CoV-2 mRNA vaccines. Data: Electrocardiogram, SkT and activity data were collected using a chest-worn wireless device (Vitalpatch RTM). In this abstract we report the results of two subsets of participants. Subset-1: five participants exhibiting post-vaccine elevation in SkT and reporting systemic reactions were chosen to be group-1 and five participants reporting no systemic reactions were selected as group-2. Subset-2: selected solely on skin temperature response post-vaccination, ten participants exhibiting post-vaccine elevation in SkT were chosen to be group-1 and ten participants exhibiting limited to no post-vaccine elevation in SkT were selected as group-2. Background and methods: Frequency domain metrics of heart rate variability (HRV), such as the peak power in the high frequency (0.15-0.4 Hz: HF), low frequency (0.04-0.15 Hz: LF), and very low frequency (0.0033-0.04 Hz: VLF) domain, non-invasively measures sympathetic and parasympathetic nervous system (SNS and PNS) dynamics. In addition, SNS and PNS play a crucial role in modulating inflammatory response with HF and LF powers exhibiting negative associations with pro-inflammatory biomarkers of blood 1 .We created a tool to evaluate three-dimensional post-vaccine trajectories of percentage change in cumulative mean relative to pre-vaccine baseline (of HF, LF and VLF power) for every hour from 1-72 hours post vaccine. This 3D trajectory of HF, LF and VLF power which we termed ‘3D HRV cartography’ demonstrated a net negative percentage change post-vaccine, showing a distinct shape for individuals exhibiting vaccine response. To further explore the differences in group-1 and group-2 we employed an unsupervised k-means clustering method with input vectors created from post-vaccine hour-1 to post-vaccine hour-72 of percentage change in cumulative mean relative of HF, LF, and VLF power and compare the labels assigned from clustering to known labels created from the groups. Results: Considering true positives to be group-1 individuals labeled correctly and true negatives to be group-2 individuals labeled correctly, we report the results for the two subsets - Subset-1 (n = 10) Accuracy: 80%, Sensitivity: 80%, Specificity: 80%; Subset-2 (n = 20) Accuracy: 75%, Sensitivity: 70%, Specificity: 80%. Conclusions: Our analysis suggests potential vaccine response signatures in both the subsets based on the mean trajectories calculated separately for group-1 and group-2. The unsupervised clustering also reveals some degree of separation between the two groups in both subsets, suggesting that 3D HRV cartography may aid in exploring distinct physiologic immune response profiles and optimizing individualized vaccine-induced immunity. Acknowledgments: physIQ Inc. (Chicago, IL) 1 .Alen, N. V., et al., Brain, Behavior, & Immunity – Health (2021). physIQ (Chicago, IL, USA, purchased by Prolaio, Scottsdale, AZ, USA) This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.