EpiInvert, an R application to restore, analyze, compare and forecast epidemiological time series
Morel, J.-D.; Morel, J.-M.; Alvarez, L. M.
Show abstract
The Covid-19 pandemic produced regional time series of incidence, hospital, ICU admission and death. The EpiInvert package estimates the incidence trend and the daily reproduction number Rt of any infectious disease, compares related time series such as incidence and death, and provides incidence forecasts. EpiInvert is an R package with the following features: (1) EpiInvert inputs raw daily incidence time series and the pandemic time serial interval. It outputs a weekly seasonality, an incidence trend and its reproduction number. (2) EpiIndicators inputs two related epidemiological time series such as daily incidence and death count. It outputs a daily ratio and delay between both time series. (3) EpiInvertForecast inputs an incidence trend obtained by EpiInvert and a database of past observed time series. Using the most similar past series, it forecasts the incidence in the next four weeks. EpiInvert is in the CRAN repository https://cran.r-project.org/web/packages/EpiInvert/index.html.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Characterizing Two Outbreak Waves of COVID-19 in Spain Using Phenomenological Epidemic Modelling 96%
- Current forecast of COVID-19: a Bayesian and Machine Learning approaches 96%
- Prediction of Covid-19 spreading and optimal coordination of counter-measures: From microscopic to macroscopic models to Pareto fronts 96%
Similar papers in this journal
Similar papers in this journal
- An ensemble n -sub-epidemic modeling framework for short-term forecasting epidemic trajectories: Application to the COVID-19 pandemic in the USA 96%
- Improving Probabilistic Infectious Disease Forecasting Through Coherence 95%
- Novel travel time aware metapopulation models and multi-layer waning immunity for late-phase epidemic and endemic scenarios 95%
Similar papers in this journal
Similar papers in this journal
- Analysis of the early Covid-19 epidemic curve in Germany by regression models with change points 96%
- Estimating lengths-of-stay of hospitalized COVID-19 patients using a non-parametric model: a case study in Galicia (Spain) 94%
- Estimating the Case Fatality Ratio for COVID-19 using a Time-Shifted Distribution Analysis 93%
"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.