Beyond the tip of the iceberg - integrating multiple disease measures to understand population-level disease dynamics

Yearly, seasonal outbreaks of Leptospira interrogans serovar Pomona occur in the California sea lion (Zalophus californianus) population. We applied field, laboratory, and analytic methods to study Leptospira dynamics in sea... [ view full abstract ]

Yearly, seasonal outbreaks of Leptospira interrogans serovar Pomona occur in the California sea lion (Zalophus californianus) population. We applied field, laboratory, and analytic methods to study Leptospira dynamics in sea lions. Our aim was to integrate multiple measures of disease, using longitudinal data to create a framework that goes beyond binary categories of seropositivity, illness and infection, and to use this framework to interpret cross-sectional data and understand population-level disease dynamics. We collected data from stranded and wild-caught sea lions on disease severity (serum chemistry), infection status (PCR) and prior exposure (MAT). We used longitudinal data from stranded animals at The Marine Mammal Center to characterize the time-course of infection and, using principal components analysis of serum chemistry results, created a disease-severity index. We used the time course and disease-severity index to interpret cross-sectional data from wild-caught and stranded animals. Despite a high case-fatality rate in stranded animals, we found mild and/or subclinical infections in wild-caught and stranded sea lions, and we identified chronic, subclinical shedding of at least 8 weeks duration. Antibody titers in recovering animals declined systematically, exhibiting early rapid decline (half-life 17 days) and later slow decline (half-life > 400 days). Using longitudinal MAT, disease-severity and PCR data, we mapped the progression of clinical disease, antibody titer decline and urinary shedding over time, enabling us to visualize the course of infection for this host-pathogen relationship. This map provided a framework to interpret cross-sectional samples and observe, on a population scale, the range of disease experienced, associations between disease severity, antibody titer and state of infection; and to identify possible chronic infections. By integrating multiple disease measures we created a mapping system that provides insights into individual- and population-level Leptospira dynamics in a wild host population, enabling us to characterize the host-pathogen relationship.