The Impact of Host-Based Early Warning on Disease Outbreaks

Mark Hernandez; Lauren E Milechin; Shakti K Davis; Rich DeLaura; Kajal T Claypool; Albert Swiston

The detection of communicable pathogens responsible for major outbreaks often relies on health care professionals' recognition of symptoms manifesting in infectious individuals. Early warning of such communicable diseases before the onset of symptoms can potentially improve both patient care and public health responses. An example of such an early warning system is the PRESAGED (Presymptomatic Agent Exposure Detection) system [1] which uses host-based physiological signals to detect an individual's exposure to pathogens, such as viruses and bacteria, before overt symptoms emerge and infectiousness is peak. In animal models, the PRESAGED algorithm has been shown to provide two to three days of early warning before the onset of incipient symptoms (e.g., fever), independent of the particular pathogen, exposure route, pathogen dose, or animal species [1] . These results are consistent with findings of Speranza et al. that show presymptomatic upregulation in biomarkers potentially linked to pathogen exposure around the same time in non-human primates exposed to Ebola [2] . Numerous efforts have evaluated epidemiological models to characterize the disease transmission dynamics and the effectiveness of public health interventions of past outbreaks [9] [10] [11] [12] [13] , including effort by Chowell et al [14] that examines the impact of a hypothetical early diagnostic capability (based on advancements in bioassay tests) for containing the spread of Ebola. We posit that a comprehensive simulation capability is essential for assessing the potential impact of a host-based early warning system.