Projecting A Mature Epidemic: A Simple Tool With An Application To COVID-19 Deaths
Artzrouni, M.; Wykoff, R.
Show abstract
We describe a new statistical model for the spread of a mature epidemic, i.e. one characterized by an exponentially decaying growth rate of the cumulative number of cases/deaths - the speed of this decay being measured by the growth rates half-life. If such a pattern is observed during the recent past, then it can be extrapolated. A spreadsheet is made available that allows users to input weekly cumulative numbers of deaths and obtain an estimate of the growth rates baseline half-life and the corresponding projections. These projections can be compared to those with a larger half-life (if a protracted epidemic is expected, e.g. due to second wave), or with a smaller one (if successful therapies or mitigation efforts reduce transmission). The model is applied to deaths due to COVID-19 in California in May-June 2020.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Data-Driven Prediction of COVID-19 Cases in Germany for Decision Making 95%
- Over- and under-estimation of vaccine effectiveness 92%
- Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: Case study of COVID-19 in Alberta, Canada and Philadelphia, USA 92%
Similar papers in this journal
- Covid-19 Belgium: Extended SEIR-QD model with nursing homes and long-term scenarios-based forecasts 94%
- Modeling the early phase of the Belgian COVID-19 epidemic using a stochastic compartmental model and studying its implied future trajectories 94%
- An R t - based model for predicting multiple epidemic waves in a heterogeneous population 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.