| Literature DB >> 36034090 |
Lorenzo Cappello1, Jaehee Kim2, Sifan Liu3, Julia A Palacios4.
Abstract
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.Entities:
Keywords: Bayesian nonparametrics; Phylodynamics; SIR models; birth-death processes; coalescent; genetic epidemiology
Year: 2022 PMID: 36034090 PMCID: PMC9409356 DOI: 10.1214/22-sts853
Source DB: PubMed Journal: Stat Sci ISSN: 0883-4237 Impact factor: 4.015