84 citations · 110 across the 8 of their papers we have counts for
5 papers · 1 filter
Gaussian Process Nowcasting: Application to COVID-19 Mortality Reporting
Iwona Hawryluk, Henrique Hoeltgebaum, Swapnil Mishra +7
Updating observations of a signal due to the delays in the measurement process is a common problem in signal processing, with prominent examples in a wide range of fields. An impor…
Semi-Mechanistic Bayesian Modeling of COVID-19 with Renewal Processes
Samir Bhatt, Neil Ferguson, Seth Flaxman +3
We propose a general Bayesian approach to modeling epidemics such as COVID-19. The approach grew out of specific analyses conducted during the pandemic, in particular an analysis c…
Referenced Thermodynamic Integration for Bayesian Model Selection: Application to COVID-19 Model Selection
Iwona Hawryluk, Swapnil Mishra, Seth Flaxman +2
Model selection is a fundamental part of the applied Bayesian statistical methodology. Metrics such as the Akaike Information Criterion are commonly used in practice to select mode…
A unified machine learning approach to time series forecasting applied to demand at emergency departments
Michaela A. C. Vollmer, Ben Glampson, Thomas A. Mellan +7
There were 25.6 million attendances at Emergency Departments (EDs) in England in 2019 corresponding to an increase of 12 million attendances over the past ten years. The steadily r…
Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in European countries: technical description update
Seth Flaxman, Swapnil Mishra, Axel Gandy +20
Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics. In response, many European countries have imple…