COVID vs. COVID (part 3)
Predictive models for the incidence of COVID-19 amongst adult in-hospital deaths are used to assess diagnostic bias in the EPR of an unknown NHS Trust
In part 2 of this series I stumbled upon a tasty finding, this being a substantial mismatch between incidence of observed and predicted COVID-19 diagnoses for the first 10 weeks of 2021 as vaccination got into its stride. If we assume that the machine learning technique employed (multilayer perceptron) has done a decent job of predicting the likelihood of a COVID diagnosis from a matrix of symptoms then we need to ask why this 10-week period is characterised by a substantial surplus of diagnoses declared in the EPR for 19,457 deceased in-patients. Thorny questions we might ask include:
Was the PCR cycle threshold cranked up to yield a bevy of false positives?
Was the mRNA vaccine inducing false positive test results?
Was the mRNA vaccine resulting in COVID-like illness?
Was the mRNA vaccine wrecking natural immunity?
But we could equally ask if machine learning has produced numerical garbage! I decided to rule this possibility out by repeating the exercise using classic multivariate logist…