vrcmort

Last updated on Feb 17, 2026 R, humanitarian
Code
Model schematic from vrcmort

vrcmort implements hierarchical Bayesian models for estimating mortality from partial and under-reported registration data.

This tool supports ongoing humanitarian and crisis-mortality workstreams, including rapid assessment settings where reporting completeness is uncertain.

rpackage humanitarian other
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OJ Watson
Associate Professor

I’m an Associate Professor at Imperial College London, supported by an Eric and Wendy Schmidt AI in Science Fellowship. I’m based within Imperial’s AI Initiative, I-X, and the MRC Centre for Global Infectious Disease Analysis.

I develop open, reproducible methods at the intersection of infectious disease modelling, mortality estimation, and AI for public health — supporting decision-making and improving data equity. Recent applications include malaria and COVID-19.

Previously, I was a Schmidt Science Fellow at the London School of Hygiene and Tropical Medicine, and held postdoctoral positions at Brown University and Imperial College London.

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