![](/wp-content/uploads/2021/03/abstractheadergraphic2011.gif)
Meeting Abstract
S6.8 Wednesday, Jan. 5 Integrating Eco-Immunological Measurements into Disease Ecology Models DEARING, MD*; LEHMER, EM; University of Utah; Fort Lewis College dearing@biology.utah.edu
The simplest predictive models in disease ecology focus on two demographic groups: individuals that are susceptible to a pathogen and those that are infected with a pathogen. Recent studies on immune function suggest that there could be broad variation within the class of susceptibles with certain individuals being far more susceptible than others to particular pathogens. Moreover, the infectiousness of individuals may fluctuate over time. We have been monitoring the prevalence of Sin Nombre virus (a hantavirus) in several populations of deer mice () for the past nine years. While we have taken a classic disease ecology approach to generate predictive models of pathogen prevalence, we have also conducted eco-immunological studies that describe the variation in the immune responses of different demographic groups. Our results indicate that substantial variation occurs in the immune responses of deer mice that could influence infectiousness but not susceptibility. Infected individuals may become more infectious over winter as antibody titers decrease, perhaps as energy is shunted to defense of body mass. In contrast, the susceptibility (as estimated through a general inflammatory response) of males and females did not differ. Thus, the difference in infection rates between males and females may not be a function of the immune system. A challenge for these studies is to determine which eco-immunological assay is most relevant to a particular host-pathogen system. Nonetheless, the inclusion of information on the degree of susceptibility and infectiousness into disease models may be useful in explaining differential prevalence across populations.