Illingworth, C. J.R. et al. (2022) A2B-COVID: a tool for rapidly evaluating potential SARS-CoV-2 transmission events. Molecular Biology and Evolution, 39(3), msac025. (doi: 10.1093/molbev/msac025) (PMID:35106603) (PMCID:PMC8892943)
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Abstract
Identifying linked cases of infection is a critical component of the public health response to viral infectious diseases. In a clinical context, there is a need to make rapid assessments of whether cases of infection have arrived independently onto a ward, or are potentially linked via direct transmission. Viral genome sequence data are of great value in making these assessments, but are often not the only form of data available. Here, we describe A2B-COVID, a method for the rapid identification of potentially linked cases of COVID-19 infection designed for clinical settings. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and evolutionary analysis of genome sequences to assess whether data collected from cases of infection are consistent or inconsistent with linkage via direct transmission. A retrospective analysis of data from two wards at Cambridge University Hospitals NHS Foundation Trust (CUH) during the first wave of the pandemic showed qualitatively different patterns of linkage between cases on designated COVID-19 and non-COVID-19 wards. The subsequent real-time application of our method to data from the second epidemic wave highlights its value for monitoring cases of infection in a clinical context.
| Item Type: | Articles |
|---|---|
| Additional Information: | This work was funded by COG-UK, which is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute; We also acknowledge the support from the Wellcome (Senior Clinical Fellowship to MPW (ref: 108070/Z/15/Z), Senior Research Fellowship to SB (ref: 215515/Z/19/Z), Senior Fellowship to IG (ref: 207498/Z/17/Z); Collaborative Grant to CJH (ref: 204870/Z/16/Z); the Academy of Medical Sciences & the Health Foundation (Clinician Scientist Fellowship to MET), the NIHR Cambridge Biomedical Research Centre (to BW, MET) and the NIHR Clinical Research Network Greenshoots award (to EGK). CJRI was supported by Deutsche Forschungsgemeinschaft (DFG) Grant SFB 1310 and by UKRI through the JUNIPE modelling consortium [grant number MR/V038613/1]. We acknowledge MRC funding (ref: MC_UU_00002/11). |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Illingworth, Dr Chris |
| Creator Roles: | Illingworth, C.Conceptualization, Formal analysis, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review and editing |
| Authors: | Illingworth, C. J.R., Hamilton, W. L., Jackson, C., Warne, B., Popay, A., Meredith, L., Hosmillo, M., Jahun, A., Fieldman, T., Routledge, M., Houldcroft, C. J., Caller, L., Caddy, S., Yakovleva, A., Hall, G., Khokhar, F. A., Feltwell, T., Pinckert, M. L., Georgana, I., Chaudhry, Y., Curran, M., Parmar, S., Sparkes, D., Rivett, L., Jones, N. K., Sridhar, S., Forrest, S., Dymond, T., Grainger, K., Workman, C., Gkrania-Klotsas, E., Brown, N. M., Weekes, M. P., Baker, S., Peacock, S. J., Gouliouris, T., Goodfellow, I., De Angelis, D., and Török, M. E. |
| College/School: | College of Medical Veterinary and Life Sciences > School of Infection & Immunity College of Medical Veterinary and Life Sciences > School of Infection & Immunity > Centre for Virus Research |
| Journal Name: | Molecular Biology and Evolution |
| Publisher: | Oxford University Press |
| ISSN: | 0737-4038 |
| ISSN (Online): | 1537-1719 |
| Published Online: | 02 February 2022 |
| Copyright Holders: | Copyright © 2022 The Authors |
| First Published: | First published in Molecular Biology and Evolution 39(3):msac025 |
| Publisher Policy: | Reproduced under a Creative Commons License |
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