@article{DBLP:journals/ploscb/BrockhausWSOMLKKHHHHFAB23,
title = {Why are different estimates of the effective reproductive number so different? A case study on COVID-19 in Germany},
author = {Elisabeth K. Brockhaus and Daniel Wolffram and Tanja Stadler and Michael Osthege and Tanmay Mitra and Jonas M. Littek and Ekaterina A. Krymova and Anna J. Klesen and Jana S. Huisman and Stefan Heyder and Laura Marie Helleckes and Matthias Heiden and Sebastian Funk and Sam Abbott and Johannes Bracher},
url = {https://doi.org/10.1371/journal.pcbi.1011653},
doi = {10.1371/JOURNAL.PCBI.1011653},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
journal = {PLoS Comput. Biol.},
volume = {19},
number = {11},
abstract = {The effective reproductive number Rt has taken a central role in the scientific, political, and public discussion during the COVID-19 pandemic, with numerous real-time estimates of this quantity routinely published. Disagreement between estimates can be substantial and may lead to confusion among decision-makers and the general public. In this work, we compare different estimates of the national-level effective reproductive number of COVID-19 in Germany in 2020 and 2021. We consider the agreement between estimates from the same method but published at different time points (within-method agreement) as well as retrospective agreement across eight different approaches (between-method agreement). Concerning the former, estimates from some methods are very stable over time and hardly subject to revisions, while others display considerable fluctuations. To evaluate between-method agreement, we reproduce the estimates generated by different groups using a variety of statistical approaches, standardizing analytical choices to assess how they contribute to the observed disagreement. These analytical choices include the data source, data pre-processing, assumed generation time distribution, statistical tuning parameters, and various delay distributions. We find that in practice, these auxiliary choices in the estimation of Rt may affect results at least as strongly as the selection of the statistical approach. They should thus be communicated transparently along with the estimates.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
