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Respiratory syncytial virus (RSV) causes significant burden of disease during infancy and childhood. This study examined the genetic relatedness of RSV positive samples from child inpatients and outpatients and a birth cohort from a rural coastal district of Kenya and also the distribution of strains between these three groups. Clinical samples were collected over a 4-year period in Kilifi District, Kenya from community and hospital surveillance. Three hundred ninety seven of 1,044 nasal specimens from children (under 5 years old) attending Kilifi District Hospital, and from community-monitored infants, were positive for RSV by multiplex RT-PCR. Of these, 376 samples were analysed further by restriction fragment length polymorphisms (RFLP) of the nucleocapsid (N) and attachment (G) protein genes. The G gene was sequenced for 109 samples and phylogenetic analysis carried out. The group A samples from Kilifi fell into two clusters based on G gene sequences, while only one group B cluster was observed. One RSV-B sample from 2003 demonstrated the presence of a 60-nucleotide duplication within the G gene, clustering with similar isolates from Buenos Aries from 1999. All had similar sequences to isolates from the UK, USA, Spain, or Uruguay. The Kilifi District samples showed greater than 97% homology to isolates from South Africa and Mozambique and 91-94% homology to isolates from The Gambia. Samples from different sources, clearly differing in disease severity, did not differ in genotype characteristics, suggesting that disease causing variants are a general reflection of infections within this community.

Original publication





Journal of medical virology

Publication Date





344 - 354


Division of Immunity and Infection, University of Birmingham, Birmingham, United Kingdom.


Humans, Respiratory Syncytial Virus, Human, Respiratory Syncytial Virus Infections, Cohort Studies, Sequence Alignment, Sequence Analysis, DNA, Phylogeny, Amino Acid Sequence, Polymorphism, Restriction Fragment Length, Molecular Sequence Data, Infant, Infant, Newborn, Rural Population, Kenya, Molecular Epidemiology