Changes in parasite traits, rather than intensity, affect the dynamics of infection under external perturbation

Experimental data for: Ghosh et al. 2018 PLOS Computational Biology. Abstract Understanding the mechanisms that generate complex host-parasite interactions, and how they contribute to variation between and within hosts, is important for predicting risk of infection and transmission, and for developing more effective interventions based on parasite properties. We used the T. retortaeformis (TR)-rabbit system and developed a state-space mathematical framework to capture the variation in intensity of infection and egg shedding in hosts infected weekly, then treated with an anthelminthic and subsequently re-challenged following the same infection regime. Experimental infections indicate that parasite intensity accumulates more slowly in the post-anthelminthic phase but reaches similar maximum numbers. By contrast, parasite EPG (eggs per gram of feces) shed from rabbits in the post-treatment phase is lower and less variable through time. Inference based on EPG alone suggests a decline in parasite intensity over time. Using a state-space model and incorporating all sources of cross-sectional and longitudinal data, we show that while parasite intensity remains relatively constant in both experimental phases, shedding of eggs into the environment is increasingly limited through changes in parasite growth. We suggest that host immunity directly modulates both the accumulation and the growth of the parasite, and indirectly affects transmission by limiting parasite length and thus fecundity. This study provides a better understanding of how within-host trophic interactions influence different components of a helminth population. It also suggests that heterogeneity in parasite traits should be addressed more carefully when examining and managing helminth infections in the absence of some critical data on parasite dynamics.



Work Title Changes in parasite traits, rather than intensity, affect the dynamics of infection under external perturbation
Open Access
  1. Isabella Cattadori
  2. Matthew Joseph Ferrari
  1. Gosh et al. 2018 PLOS Computational Biology. Experimental data
License Public Domain Mark 1.0
Work Type Dataset
DOI doi:10.18113/S19H0G
Deposited May 10, 2018




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  • Added Creator Isabella Cattadori
  • Added Creator Matthew Joseph Ferrari
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