Your browser doesn't support javascript.
A generic method and software to estimate the transmission advantage of pathogen variants in real-time : SARS-CoV-2 as a case-study
Sangeeta Bhatia; Jack Wardle; Rebecca K Nash; Pierre Nouvellet; Anne Cori.
  • Sangeeta Bhatia; Imperial College London
  • Jack Wardle; Imperial College London
  • Rebecca K Nash; Imperial College London
  • Pierre Nouvellet; Imperial College London, University of Sussex
  • Anne Cori; Imperial College London
Preprint Dans Anglais | medRxiv | ID: ppmedrxiv-21266899
Recent months have demonstrated that emerging variants may set back the global COVID-19 response. The ability to rapidly assess the threat of new variants in real-time is critical for timely optimisation of control strategies. We extend the EpiEstim R package, designed to estimate the time-varying reproduction number (Rt), to estimate in real-time the effective transmission advantage of a new variant compared to a reference variant. Our method can combine information across multiple locations and over time and was validated using an extensive simulation study, designed to mimic a variety of real-time epidemic contexts. We estimate that the SARS-CoV-2 Alpha variant is 1.46 (95% Credible Interval 1.44-1.47) and 1.29, (95% CrI 1.29-1.30) times more transmissible than the wild type, using data from England and France respectively. We further estimate that Beta and Gamma combined are 1.25 (95% CrI 1.24-1.27) times more transmissible than the wildtype (France data). All results are in line with previous estimates from literature, but could have been obtained earlier and more easily with our off-the-shelf open-source tool. Our tool can be used as an important first step towards quantifying the threat of new variants in real-time. Given the popularity of EpiEstim, this extension will likely be used widely to monitor the co-circulation and/or emergence of multiple variants of infectious pathogens. Significance StatementEarly assessment of the transmissibility of new variants of an infectious pathogen is critical for anticipating their impact and designing appropriate interventions. However, this often requires complex and bespoke analyses relying on multiple data streams, including genomic data. Here we present a novel method and software to rapidly quantify the transmission advantage of new variants. Our method is fast and requires only routinely collected disease surveillance data, making it easy to use in real-time. The ongoing high level of SARS-CoV-2 circulation in a number of countries makes the emergence of new variants highly likely. Our work offers a powerful tool to help public health bodies monitor such emerging variants and rapidly detect those with increased transmissibility.
Texte intégral: Disponible Collection: Preprints Base de données: medRxiv Type de document: Preprint langue: Anglais Année: 2021

Documents relatifs à ce sujet




Texte intégral: Disponible Collection: Preprints Base de données: medRxiv Type de document: Preprint langue: Anglais Année: 2021