Integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission.
Kombe, Ivy K;
Agoti, Charles N;
Munywoki, Patrick K;
Baguelin, Marc;
Nokes, D James;
Medley, Graham F;
(2021)
Integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission.
Scientific reports, 11 (1).
1463-.
ISSN 2045-2322
DOI: https://doi.org/10.1038/s41598-021-81078-x
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Respiratory syncytial virus (RSV) is responsible for a significant burden of severe acute lower respiratory tract illness in children under 5 years old; particularly infants. Prior to rolling out any vaccination program, identification of the source of infant infections could further guide vaccination strategies. We extended a dynamic model calibrated at the individual host level initially fit to social-temporal data on shedding patterns to include whole genome sequencing data available at a lower sampling intensity. The study population was 493 individuals (55 aged < 1 year) distributed across 47 households, observed through one RSV season in coastal Kenya. We found that 58/97 (60%) of RSV-A and 65/125 (52%) of RSV-B cases arose from infection probably occurring within the household. Nineteen (45%) infant infections appeared to be the result of infection by other household members, of which 13 (68%) were a result of transmission from a household co-occupant aged between 2 and 13 years. The applicability of genomic data in studies of transmission dynamics is highly context specific; influenced by the question, data collection protocols and pathogen under investigation. The results further highlight the importance of pre-school and school-aged children in RSV transmission, particularly the role they play in directly infecting the household infant. These age groups are a potential RSV vaccination target group.