Trajectories of senescence through Markov models
Lead Research Organisation:
University of Oxford
Department Name: Statistics
Abstract
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People |
ORCID iD |
| David Steinsaltz (Principal Investigator) |
Publications
Steinsaltz D
(2011)
Derivatives of the stochastic growth rate.
in Theoretical population biology
Steinsaltz D
(2012)
Markov models of aging: theory and practice.
in Experimental gerontology
Kolb M
(2012)
Quasilimiting behavior for one-dimensional diffusions with killing
in The Annals of Probability
Catalano RA
(2015)
Hormonal evidence of selection in utero revisited.
in American journal of human biology : the official journal of the Human Biology Council
| Description | • We have a new formula for computing the sensitivity of population growth in age-structured natural populations to environmental changes. This has practical implications for studying ecological response to climate change and other environmental shifts, and theoretical implications for the evolution of ageing. • The patterns of total movement through the life course among flies were too variable to analysed with the basic monotone-ageing hidden diffusion model that had initially been proposed. This work helped to inspire a new dynamical generalised linear model, that is now being made operational, and will be applied to a cleaner and larger set of data. • We were able in principle to "filter" the individual pattern of ageing for flies on the basis of patterns of behaviour other than movement, in this case the frequency of eating. On the other hand, the individual trajectories were too variable to be demonstrably useful for predicting remaining lifespan. • We have new theorems giving general conditions for the stabilisation over the life course ("convergence to quasistationarity") of diffusion models for ageing. • We have drawn up a classification of statistical models of ageing in terms of the way the models treat random variation. • We have shown how information measures can be used to evaluate the theoretical utility of features of mathematical models that purport to describe the ageing process. |
| Exploitation Route | We have now produced software for computing the algorithms we developed for analysing the growth of ageing populations in random environments, and these are now being tested by groups in the US working in applied and theoretical population ecology. The approach that we developed for analysing survival with longitudinal covariates has led us to procedures for studying longitudinal data sets for the impact of variability of blood pressure. We are working on extending these to general procedures for medical monitoring. |
| Sectors | Healthcare,Pharmaceuticals and Medical Biotechnology |
| URL | http://steinsaltz.me.uk/agingpage.html |
| Description | NCRM Methodological Research Projects |
| Amount | £485,000 (GBP) |
| Funding ID | ES/N011856/1 |
| Organisation | Economic and Social Research Council |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2016 |
| End | 12/2018 |
| Title | Stochastic growth software |
| Description | Software package for computing changes in population growth rates in changing environments. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2014 |
| Provided To Others? | Yes |
| Impact | None yet. |