Genomic analysis of respiratory syncytial virus infections in households and utility in inferring who infects the infant

Charles N. Agoti*, My V.T. Phan, Patrick K. Munywoki, George Githinji, Graham F. Medley, Patricia Cane, Paul Kellam, Matthew Cotten, D. James Nokes

*Corresponding author for this work

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    11 Citations (Scopus)


    Infants (under 1-year-old) are at most risk of life threatening respiratory syncytial virus (RSV) disease. RSV epidemiological data alone has been insufficient in defining who acquires infection from whom (WAIFW) within households. We investigated RSV genomic variation within and between infected individuals and assessed its potential utility in tracking transmission in households. Over an entire single RSV season in coastal Kenya, nasal swabs were collected from members of 20 households every 3–4 days regardless of symptom status and screened for RSV nucleic acid. Next generation sequencing was used to generate >90% RSV full-length genomes for 51.1% of positive samples (191/374). Single nucleotide polymorphisms (SNPs) observed during household infection outbreaks ranged from 0–21 (median: 3) while SNPs observed during single-host infection episodes ranged from 0–17 (median: 1). Using the viral genomic data alone there was insufficient resolution to fully reconstruct within-household transmission chains. For households with clear index cases, the most likely source of infant infection was via a toddler (aged 1 to <3 years-old) or school-aged (aged 6 to <12 years-old) co-occupant. However, for best resolution of WAIFW within households, we suggest an integrated analysis of RSV genomic and epidemiological data.

    Original languageEnglish
    Article number10076
    JournalScientific Reports
    Issue number1
    Publication statusPublished - 1 Dec 2019

    Bibliographical note

    Funding Information:
    We thank the study participants for providing the study samples. We thank members of the Virus Epidemiology and Control (VEC) Research Group in Kilifi whom were involved in this study especially in sample and data collection and laboratory screening for RSV. We thank the Illumina C team at the Wellcome Trust Sanger Institute (Hinxton, Cambridge, UK) for their help in deep sequencing. This work was funded by the Wellcome Trust (grant refs: 090853, 102975 and 203077/Z/16/Z). Dr Agoti is supported through the DELTAS Africa Initiative [DEL-15-003]. The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences (AAS)‘s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa’s Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust [107769/Z/10/Z] and the UK government. The views expressed in this publication are those of the author(s) and not necessarily those of AAS, NEPAD Agency, Wellcome Trust or the UK government.

    Publisher Copyright:
    © 2019, The Author(s).


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