Statistical vhallenges in tracking the evolution of SARS-CoV-2

Genomic surveillance of SARS-CoV-2 has been instrumental in tracking the spread and evolution of the virus during the pandemic. The availability of SARS-CoV-2 molecular sequences isolated from infected individuals, coupled with phylodynamic methods, have provided insights into the origin of the viru...

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Detalhes bibliográficos
Autores: Cappello, Lorenzo, Kim, Jaehee, Liu, Sifan, Palacios, Julia A.
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2022
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositório:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/59279
Acesso em linha:http://hdl.handle.net/10230/59279
http://dx.doi.org/10.1214/22-sts853
Access Level:Acceso aberto
Palavra-chave:Bayesian nonparametrics
birth-death processes
Coalescent
genetic epidemiology
phylodynamics
SIR models
Descrição
Resumo:Genomic surveillance of SARS-CoV-2 has been instrumental in tracking the spread and evolution of the virus during the pandemic. The availability of SARS-CoV-2 molecular sequences isolated from infected individuals, coupled with phylodynamic methods, have provided insights into the origin of the virus, its evolutionary rate, the timing of introductions, the patterns of transmission, and the rise of novel variants that have spread through populations. Despite enormous global efforts of governments, laboratories, and researchers to collect and sequence molecular data, many challenges remain in analyzing and interpreting the data collected. Here, we describe the models and methods currently used to monitor the spread of SARS-CoV-2, discuss long-standing and new statistical challenges, and propose a method for tracking the rise of novel variants during the epidemic.