estimateR: An R package to estimate and monitor the effective reproductive number

BackgroundThe accurate estimation of the effective reproductive number (Re) of epidemic outbreaks is of central relevance to public health policy and decision making. We present estimateR, an R package for the estimation of the reproductive number through time from delayed observations of infection events. Such delayed observations may for example be confirmed cases, hospitalizations or deaths. The Re estimation procedure is modularized which allows easy implementation of new alternatives to the already-available methods. Users can tailor their analyses according to their particular use cases by choosing among implemented variations. The package is based on the methodology of Huisman et al. developed as a response to the COVID-19 pandemic. ResultsThe estimateR R package allows users to estimate the effective reproductive number of an epidemic outbreak based on observed cases, hospitalization, death or any other type of event documenting past infections, in a fast and timely fashion. We validated the implementation with a simulation study, and by comparing results from estimateR to results from the Huisman et al. pipeline on empirical COVID-19 case-confirmation incidence. Compared to existing methods, estimateR implements unique features whose benefit we demonstrated with a simulation study. On simulated data, estimateR yielded estimates of similar, if not better, accuracy than compared alternative publicly available methods while being two to three orders of magnitude faster. In summary, this R package provides a fast and flexible implementation to estimate the effective reproductive number for various diseases and datasets. ConclusionsThe estimateR R package is a modular and extendible tool designed for outbreak surveillance and retrospective outbreak investigation. It extends the method developed for COVID-19 by Huisman et al. and makes it available for a variety of pathogens, outbreak scenarios, and observation types. Estimates obtained with estimateR can be interpreted directly or used to inform more complex epidemic models (e.g. for forecasting) on the value of Re.