Integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission
Abstract 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...
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doaj-2df357e5a0e044188c40732ca91038cf2021-01-17T12:46:15ZengNature Publishing GroupScientific Reports2045-23222021-01-0111111210.1038/s41598-021-81078-xIntegrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmissionIvy K. Kombe0Charles N. Agoti1Patrick K. Munywoki2Marc Baguelin3D. James Nokes4Graham F. Medley5KEMRI-Wellcome Trust Research Programme, KEMRI Centre for Geographical Medical Research-CoastKEMRI-Wellcome Trust Research Programme, KEMRI Centre for Geographical Medical Research-CoastKEMRI-Wellcome Trust Research Programme, KEMRI Centre for Geographical Medical Research-CoastCentre for Mathematical Modelling of Infectious Disease and Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical MedicineKEMRI-Wellcome Trust Research Programme, KEMRI Centre for Geographical Medical Research-CoastCentre for Mathematical Modelling of Infectious Disease and Department of Global Health and Development, London School of Hygiene and Tropical MedicineAbstract 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.https://doi.org/10.1038/s41598-021-81078-x |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ivy K. Kombe Charles N. Agoti Patrick K. Munywoki Marc Baguelin D. James Nokes Graham F. Medley |
spellingShingle |
Ivy K. Kombe Charles N. Agoti Patrick K. Munywoki Marc Baguelin D. James Nokes Graham F. Medley Integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission Scientific Reports |
author_facet |
Ivy K. Kombe Charles N. Agoti Patrick K. Munywoki Marc Baguelin D. James Nokes Graham F. Medley |
author_sort |
Ivy K. Kombe |
title |
Integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission |
title_short |
Integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission |
title_full |
Integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission |
title_fullStr |
Integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission |
title_full_unstemmed |
Integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission |
title_sort |
integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission |
publisher |
Nature Publishing Group |
series |
Scientific Reports |
issn |
2045-2322 |
publishDate |
2021-01-01 |
description |
Abstract 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. |
url |
https://doi.org/10.1038/s41598-021-81078-x |
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