tetano
Editor, Senior Moderator
mSphere
. 2023 Jan 25;e0054422.
doi: 10.1128/msphere.00544-22. Online ahead of print.
Low Viral Diversity Limits the Effectiveness of Sequence-Based Transmission Inference for SARS-CoV-2
Mireille Farjo[SUP] 1 [/SUP], Christopher B Brooke[SUP] 1 2 [/SUP]
Affiliations
Abstract
Tracking the spread of infection amongst individuals within and between communities has been a major challenge during viral outbreaks. With the unprecedented scale of viral sequence data collection during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, the possibility of using phylogenetics to reconstruct past transmission events has been explored as a more rigorous alternative to traditional contact tracing; however, the reliability of sequence-based inference of transmission networks has yet to be directly evaluated. E. E. Bendall, G. Paz-Bailey, G. A. Santiago, C. A. Porucznik, et al. (mSphere 7:e00400-22, 2022, https://doi.org/10.1128/mSphere.00400-22) evaluate the potential of this technique by applying best practices sequence comparison methods to three geographically distinct cohorts that include known transmission pairs and demonstrate that linked pairs are often indistinguishable from unrelated samples. This study clearly establishes how low viral diversity limits the utility of genomic methods of epidemiological inference for SARS-CoV-2.
Keywords: SARS-CoV-2; genomic epidemiology; transmission networks.
. 2023 Jan 25;e0054422.
doi: 10.1128/msphere.00544-22. Online ahead of print.
Low Viral Diversity Limits the Effectiveness of Sequence-Based Transmission Inference for SARS-CoV-2
Mireille Farjo[SUP] 1 [/SUP], Christopher B Brooke[SUP] 1 2 [/SUP]
Affiliations
- PMID: 36695609
- DOI: 10.1128/msphere.00544-22
Abstract
Tracking the spread of infection amongst individuals within and between communities has been a major challenge during viral outbreaks. With the unprecedented scale of viral sequence data collection during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, the possibility of using phylogenetics to reconstruct past transmission events has been explored as a more rigorous alternative to traditional contact tracing; however, the reliability of sequence-based inference of transmission networks has yet to be directly evaluated. E. E. Bendall, G. Paz-Bailey, G. A. Santiago, C. A. Porucznik, et al. (mSphere 7:e00400-22, 2022, https://doi.org/10.1128/mSphere.00400-22) evaluate the potential of this technique by applying best practices sequence comparison methods to three geographically distinct cohorts that include known transmission pairs and demonstrate that linked pairs are often indistinguishable from unrelated samples. This study clearly establishes how low viral diversity limits the utility of genomic methods of epidemiological inference for SARS-CoV-2.
Keywords: SARS-CoV-2; genomic epidemiology; transmission networks.