Pathogen dynamics across the diversity of ageing
Cite this dataset
Clark, Jessica; McNally, Luke; Little, Tom (2021). Pathogen dynamics across the diversity of ageing [Dataset]. Dryad. https://doi.org/10.5061/dryad.8cz8w9gnh
Reproduction, mortality and immune function often change with age, but do not invariably deteriorate. Across the tree of life, there is extensive variation in age-specific performance and changes to key life-history traits. These changes occur on a spectrum from classic senescence, where performance declines with age, to juvenescence, where performance improves with age. Reproduction, mortality and immune function are also important factors influencing the spread of infectious disease, yet there exists no comprehensive investigation into how the ageing spectrum of these traits impacts epidemics.We used a model laboratory infection system to compile an ageing profile of a single organism, including traits directly linked to pathogen resistance, and those that should indirectly alter pathogen transmission by influencing demography. We then developed generalizable epidemiological models demonstrating that different patterns of ageing produce dramatically different transmission landscapes: in many cases ageing can reduce the probability of epidemics, but it can also promote severity. This work provides context and tools for use across taxa by empiricists, demographers and epidemiologists, advancing our ability to accurately predict factors contributing to epidemics, or the potential repercussions of senescence manipulation.
Data were collected and then entered into excel. They were double checked prior to commencing analysis. JC collected, entered and double checked data.
Statistical analysis was conducted in R.
Simulation model development and derivations were carried out in Mathematica and R.
controls_infected.csv is the file for the analysis of the force of mortality in infected and uninfected individuals.
mat.sen.old.mums.csv is the file for the analysis of reproduction in the maternal generation.
mat.effect.sen.data.csv is the file for the analysis of offspring performance.
pathogen.dynamics.ageing.R is the script for all experimental analysis, statistical model selection, visualisation and data manipulation of the above csv files. Packages necessary to carry this out are listed at the top of the file.
Next.Gen.Matrix.Method.nb is the Mathematica Notebook which includes the formulation and analysis of the NGM.
NERC, Award: E3 Doctoral Training Partnership Studentship