Estimating the elevated transmissibility of the B.1.1.7 strain over previously circulating strains in England using GISAID sequence frequencies
Piantham, C.; Linton, N. M.; Nishiura, H.; Ito, K.
10.1101/2021.03.17.21253775 medRxivShow abstract
The B.1.1.7 strain, also referred to as Alpha variant, is a variant strain of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The Alpha variant is considered to possess higher transmissibility compared to the strains previously circulating in England. This paper proposes a new method to estimate the selective advantage of a mutant strain over another strain using the time course of strain frequencies and the distribution of the serial interval of infections. This method allows the instantaneous reproduction numbers of infections to vary over calendar time. The proposed method also assumes that the selective advantage of a mutant strain over previously circulating strains is constant. Applying the method to SARS-CoV-2 sequence data from England, the instantaneous reproduction number of the B.1.1.7 strain was estimated to be 26.6-45.9% higher than previously circulating strains in England. This result indicates that control measures should be strengthened by 26.6-45.9% when the B.1.1.7 strain is newly introduced to a country where viruses with similar transmissibility to the preexisting strain in England are predominant.
Matching journals
The top 11 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Nonself Mutations in the Spike Protein Suggest an Increase in the Antigenicity and a Decrease in the Virulence of the Omicron Variant of SARS-CoV-2 89%
- Population-Based Estimation of the Fraction of Incidental COVID-19 Hospitalizations During the Omicron Wave in the United States 88%
- A general computational framework for COVID-19 modelling, with applications to testing varied interventions in education environments 88%
Similar papers in this journal
- Emerging strains of watermelon mosaic virus in Southeastern France: model-based estimation of the dates and places of introduction 95%
- Mathematical modelling of SARS-CoV-2 variant outbreaks reveals their probability of extinction 94%
- Modelling the interplay of SARS-CoV-2 variants in the United Kingdom 93%
Similar papers in this journal
- Incorporating the mutational landscape of SARS-COV-2 variants and case-dependent vaccination rates into epidemic models 95%
- Understanding the transmission pathways of Lassa Fever: a mathematical modeling approach 93%
- Estimate of the rate of unreported COVID-19 cases during the first outbreak in Rio de Janeiro 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.