4 papers
Tree statistics improve neural simulation-based inference of epidemiological parameters over case counts alone
Zena Lapp, Emma E. Goldberg, John R. Tipton +3
During an infectious disease outbreak, accurate estimates of epidemiological parameters such as the reproduction number and infection duration can inform the public health response…
Transfer Learning using 66 Diseases for Disease Forecasting Applications
Lauren J Beesley, Alexander C Murph, Dave Osthus +1
Disease forecasting models typically rely on a single data stream, making models brittle when histories are short or noisy. Recent top-performing models have shown that synthesizin…
Leveraging Synthetic and Genetic Data to Improve Epidemic Forecasting
Dave Osthus, Alexander C. Murph, Emma E. Goldberg +4
Forecasting infectious disease outbreaks is hard. Forecasting emerging infectious diseases with limited historical data is even harder. In this paper, we investigate ways to improv…
Mapping Incidence and Prevalence Peak Data for SIR Forecasting Applications
Alexander C. Murph, G. Casey Gibson, Lauren J. Beesley +4
Infectious disease modeling and forecasting have played a key role in helping assess and respond to epidemics and pandemics. Recent work has leveraged data on disease peak infectio…