Remodelling Selection: from a vision to a method

Prof. Gabriela Gomes (University of Strathclyde)

Thursday 17th October 14:00-15:00 Maths 311B

Abstract

“Selective Depletion Bias” is a new term that applies when the population mean value of a trait changes over time or across environments due to selective depletion of frail individuals, and this is misinterpreted as individuals (rather than population composition) changing. This demographic phenomenon was identified and formulated mathematically in the 1970s (when the related “frailty variation” term was introduced), and since applied in econometrics, demography, biostatistics, epidemiology, ecology and evolution. There is growing evidence that the phenomenon is more widespread than initially thought, but still frequently neglected due to the challenges of identifying distributions of individual traits that are under selection. 

In this context, I propose that identifiability can be achieved by collecting data at different points of a selection gradient and fitting a model that includes the distribution of interest - “Remodelling Selection”. I have applied this approach to estimate the efficacy of vaccines and to model the initial waves of the COVID-19 pandemic. I am currently applying it to a very different system where bacterial populations grow in laboratory environments under different levels of stress and models are fitted to estimate distributions of individual division rates.

I envision the elimination of selective depletion biases in scientific research by remodelling selection in study design and analysis.

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