Dynamics of temperature change during experimental respiratory virus challenge: Relationships with symptoms, stress...

Thermoregulation is a complex, dynamic process involving coordination between multiple autonomic, endocrine, and behavioral mechanisms. In the context of infection, this intricate machinery generates fever, a process believed to serve vital functions in the body's defense against pathogens. In addition to increasing core temperature, infection can lead to changes in the dynamic fluctuations in body temperature over time. The patterns of these deviations may convey information about the health of the body and the course of illness. Here, we utilized dynamic structural equation modeling to explore patterns of body temperature change following an experimental respiratory virus challenge in an aggregated, archival dataset of human participants (N = 1,412). We also examined whether temperature dynamics during infection were related to symptom severity, as well as individual differences in biomarkers of inflammation and stress. We found that individuals meeting the criteria for infection exhibited higher but less stable body temperatures over time compared to those not meeting criteria of infection. While temperature parameters did not reliably predict symptom severity, higher levels of nasal proinflammatory cytokines were associated with lower, more consistent temperatures during the study period. Further, levels of salivary cortisol and urinary catecholamines measured at the beginning of the study appeared to have disparate effects on temperature change. In sum, this research highlights the utility of dynamic time series modeling as a framework for studying body temperature change and lends novel insights into how stress may interact with infection to influence patterns of thermoregulation.