RelRe: A command-line tool to predict the trajectory of variant replacement in an epidemic using relative instantaneous reproduction numbers

During the SARS-CoV-2 pandemic, we have witnessed the emergence and disappearance of variants. When random mutations generate a new variant capable of infecting more individuals than existing variants, such a variant poses a public health threat due to the virus’s increased transmissibility. Therefore, it is essential to know how transmissible a new variant is compared to existing ones. In this paper, we introduce a computer program called RelRe, which allows users to estimate the relative instantaneous reproduction numbers among variants as well as the relative generation time using time series data of variant counts. Based on the estimated parameters, one can predict future variant replacements. The program was implemented with the Julia language, and its source code is available on our GitHub page (https://github.com/KimihitoIto/RelRe).

Authors

Publication Details

Journal
SoftwareX
Published
2025-11-08
DOI
https://doi.org/10.1016/j.softx.2025.102440
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
0.00
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article

RelRe: A command-line tool to predict the trajectory of variant replacement in an epidemic using relative instantaneous reproduction numbers

Chayada Piantham, Kimihito Ito, Michael Zeller, Richard Musonda
SoftwareX
Genomics and Rare Diseases
article

RelRe: A command-line tool to predict the trajectory of variant replacement in an epidemic using relative instantaneous reproduction numbers

Chayada Piantham, Kimihito Ito, Michael Zeller, Richard Musonda
article en

Abstract

During the SARS-CoV-2 pandemic, we have witnessed the emergence and disappearance of variants. When random mutations generate a new variant capable of infecting more individuals than existing variants, such a variant poses a public health threat due to the virus’s increased transmissibility. Therefore, it is essential to know how transmissible a new variant is compared to existing ones. In this paper, we introduce a computer program called RelRe, which allows users to estimate the relative instantaneous reproduction numbers among variants as well as the relative generation time using time series data of variant counts. Based on the estimated parameters, one can predict future variant replacements. The program was implemented with the Julia language, and its source code is available on our GitHub page (https://github.com/KimihitoIto/RelRe).

SoftwareXVol. 32
Openalex Percentile: Top 65%
Genomics and Rare Diseases
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