84 citations · 107 across the 7 of their papers we have counts for
9 papers
Cox-Hawkes: doubly stochastic spatiotemporal Poisson processes
Xenia Miscouridou, Samir Bhatt, George Mohler +2
Hawkes processes are point process models that have been used to capture self-excitatory behavior in social interactions, neural activity, earthquakes and viral epidemics. They can…
Epidemia: An R Package for Semi-Mechanistic Bayesian Modelling of Infectious Diseases using Point Processes
James A. Scott, Axel Gandy, Swapnil Mishra +4
This article introduces epidemia, an R package for Bayesian, regression-oriented modeling of infectious diseases. The implemented models define a likelihood for all observed data w…
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…
Inference of COVID-19 epidemiological distributions from Brazilian hospital data
Iwona Hawryluk, Thomas A. Mellan, Henrique H. Hoeltgebaum +8
Knowing COVID-19 epidemiological distributions, such as the time from patient admission to death, is directly relevant to effective primary and secondary care planning, and moreove…