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estimateR: an R package to estimate and monitor the effective reproductive number
BACKGROUND: Accurate estimation of the effective reproductive number ([Formula: see text] ) 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 observatio...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10416499/ https://www.ncbi.nlm.nih.gov/pubmed/37568078 http://dx.doi.org/10.1186/s12859-023-05428-4 |
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author | Scire, Jérémie Huisman, Jana S. Grosu, Ana Angst, Daniel C. Lison, Adrian Li, Jinzhou Maathuis, Marloes H. Bonhoeffer, Sebastian Stadler, Tanja |
author_facet | Scire, Jérémie Huisman, Jana S. Grosu, Ana Angst, Daniel C. Lison, Adrian Li, Jinzhou Maathuis, Marloes H. Bonhoeffer, Sebastian Stadler, Tanja |
author_sort | Scire, Jérémie |
collection | PubMed |
description | BACKGROUND: Accurate estimation of the effective reproductive number ([Formula: see text] ) 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 include confirmed cases, hospitalizations or deaths. The package implements the methodology of Huisman et al. but modularizes the [Formula: see text] estimation procedure to allow easy implementation of new alternatives to the currently available methods. Users can tailor their analyses according to their particular use case by choosing among implemented options. RESULTS: The 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: estimateR yielded estimates comparable to alternative publicly available methods while being around two orders of magnitude faster. We then applied estimateR to empirical case-confirmation incidence data for COVID-19 in nine countries and for dengue fever in Brazil; in parallel, estimateR is already being applied (i) to SARS-CoV-2 measurements in wastewater data and (ii) to study influenza transmission based on wastewater and clinical data in other studies. In summary, this R package provides a fast and flexible implementation to estimate the effective reproductive number for various diseases and datasets. CONCLUSIONS: The estimateR R package is a modular and extendable 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 [Formula: see text] . SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05428-4. |
format | Online Article Text |
id | pubmed-10416499 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-104164992023-08-12 estimateR: an R package to estimate and monitor the effective reproductive number Scire, Jérémie Huisman, Jana S. Grosu, Ana Angst, Daniel C. Lison, Adrian Li, Jinzhou Maathuis, Marloes H. Bonhoeffer, Sebastian Stadler, Tanja BMC Bioinformatics Software BACKGROUND: Accurate estimation of the effective reproductive number ([Formula: see text] ) 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 include confirmed cases, hospitalizations or deaths. The package implements the methodology of Huisman et al. but modularizes the [Formula: see text] estimation procedure to allow easy implementation of new alternatives to the currently available methods. Users can tailor their analyses according to their particular use case by choosing among implemented options. RESULTS: The 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: estimateR yielded estimates comparable to alternative publicly available methods while being around two orders of magnitude faster. We then applied estimateR to empirical case-confirmation incidence data for COVID-19 in nine countries and for dengue fever in Brazil; in parallel, estimateR is already being applied (i) to SARS-CoV-2 measurements in wastewater data and (ii) to study influenza transmission based on wastewater and clinical data in other studies. In summary, this R package provides a fast and flexible implementation to estimate the effective reproductive number for various diseases and datasets. CONCLUSIONS: The estimateR R package is a modular and extendable 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 [Formula: see text] . SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05428-4. BioMed Central 2023-08-11 /pmc/articles/PMC10416499/ /pubmed/37568078 http://dx.doi.org/10.1186/s12859-023-05428-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Scire, Jérémie Huisman, Jana S. Grosu, Ana Angst, Daniel C. Lison, Adrian Li, Jinzhou Maathuis, Marloes H. Bonhoeffer, Sebastian Stadler, Tanja estimateR: an R package to estimate and monitor the effective reproductive number |
title | estimateR: an R package to estimate and monitor the effective reproductive number |
title_full | estimateR: an R package to estimate and monitor the effective reproductive number |
title_fullStr | estimateR: an R package to estimate and monitor the effective reproductive number |
title_full_unstemmed | estimateR: an R package to estimate and monitor the effective reproductive number |
title_short | estimateR: an R package to estimate and monitor the effective reproductive number |
title_sort | estimater: an r package to estimate and monitor the effective reproductive number |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10416499/ https://www.ncbi.nlm.nih.gov/pubmed/37568078 http://dx.doi.org/10.1186/s12859-023-05428-4 |
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