Infection dynamics of endemic malaria in a wild bird population: parasite species-dependent drivers of spatial and temporal variation in transmission rates.
Lachish S., Knowles SC., Alves R., Wood MJ., Sheldon BC.
1. Investigating the ecological context in which host-parasite interactions occur and the roles of biotic and abiotic factors in forcing infection dynamics is essential to understanding disease transmission, spread and maintenance. 2. Despite their prominence as model host-pathogen systems, the relative influence of environmental heterogeneity and host characteristics in influencing the infection dynamics of avian blood parasites has rarely been assessed in the wild, particularly at a within-population scale. 3. We used a novel multievent modelling framework (an extension of multistate mark-recapture modelling) that allows for uncertainty in disease state, to estimate transmission parameters and assess variation in the infection dynamics of avian malaria in a large, longitudinally sampled data set of breeding blue tits infected with two divergent species of Plasmodium parasites. 4. We found striking temporal and spatial heterogeneity in the disease incidence rate and the likelihood of recovery within this single population and demonstrate marked differences in the relative influence of environmental and host factors in forcing the infection dynamics of the two Plasmodium species. 5. Proximity to a permanent water source greatly influenced the transmission rates of P. circumflexum, but not of P. relictum, suggesting that these parasites are transmitted by different vectors. 6. Host characteristics (age/sex) were found to influence infection rates but not recovery rates, and their influence on infection rates was also dependent on parasite species: P. relictum infection rates varied with host age, whilst P. circumflexum infection rates varied with host sex. 7. Our analyses reveal that transmission of endemic avian malaria is a result of complex interactions between biotic and abiotic components that can operate on small spatial scales and demonstrate that knowledge of the drivers of spatial and temporal heterogeneity in disease transmission will be crucial for developing accurate epidemiological models and a thorough understanding of the evolutionary implications of pathogens.