William Elson

My research focuses on using primary care electronic health records (EHRs) to support timely public health surveillance of acute respiratory infections

I develop and evaluate analytical methods to quantify population level severity, aiming to detect changes that may indicate emerging threats and to support preparedness for future epidemics and pandemics. I also build and validate digital phenotypes (algorithms that translate routine clinical data into reproducible case definitions for surveillance and observational research). My work directly supports UK Health Security Agency through its real time syndromic surveillance team and the long standing partnership with the Oxford based RCGP Research and Surveillance Centre.

Alongside this, my work focuses on how we measure the quality of EHR data and what this means for the reliability of surveillance outputs and observational research. This includes quantifying completeness and timeliness, checking internal consistency, and characterising variation in clinical coding, then setting out the implications for bias, misclassification, and uncertainty. 

Previously, I worked for four years within a longstanding community based epidemiological surveillance system for dengue and Zika in the Peruvian Amazon, including mosquito repellent trials and clinical studies describing dengue symptomatology and its impact on quality of life. I hold an MSc in Health Data Science and practise as a GP in Southwark, London.