“Wrong, but Useful”: Negotiating Uncertainty in Infectious Disease Modelling

“Wrong, but Useful”: Negotiating Uncertainty in Infectious Disease Modelling

For infectious disease dynamical models to inform policy for containment of infectious diseases the models must be able to predict; however, it is well recognised that such prediction will never be perfect. Nevertheless, the consensus is that although models are uncertain, some may yet inform effective action. This assumes that the quality of a model can be ascertained in order to evaluate suff...

Essentially all models are wrong, but some are useful.

Recent advances in high-throughput technologies, such as genome-wide SNP analysis and microarray gene expression profiling, have led to a multitude of ranked lists, where the features (SNPs, genes) are sorted based on their individual correlation with a phenotype. Multiple reviews have shown that most such rankings vary considerably across different studies, even in the case of subsampling from...

Infectious Disease Modelling

This is an author-created preprint of a book chapter to appear in the Handbook on Spatial Epidemiology edited by Andrew Lawson, Sudipto Banerjee, Robert Haining and Lola Ugarte, CRC Press. The final version of this text is to be found in this book – once available the ISBN number of the book will be given. The preprint is available as http://www.math.su.se/~hoehle/pubs/Hoehle_ SpaMethInfEpiMode...

Wrong way , go back ! Negotiating access in industry - based research

Infectious disease modelling and causal inference

When applying survival analysis, such as Cox regression, to data frommajor clinical trials or other studies, often only baseline covariates are used.This is typically the case even if updated covariates are available throughoutthe observation period, which leaves large amounts of information unused.The main reason for this is that such time-dependent covariates often areinte...