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Human rhinovirus spatial-temporal epidemiology in rural coastal Kenya, 2015-2016, observed through outpatient surveillance
Background: Human rhinovirus (HRV) is the predominant cause of upper respiratory tract infections, resulting in a significant public health burden. The virus circulates as many different types (168), each generating strong homologous, but weak heterotypic, immunity. The influence of these features o...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234744/ https://www.ncbi.nlm.nih.gov/pubmed/30483602 http://dx.doi.org/10.12688/wellcomeopenres.14836.2 |
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author | Morobe, John Mwita Nyiro, Joyce U. Brand, Samuel Kamau, Everlyn Gicheru, Elijah Eyase, Fredrick Otieno, Grieven P. Munywoki, Patrick K. Agoti, C.N. Nokes, D.J. |
author_facet | Morobe, John Mwita Nyiro, Joyce U. Brand, Samuel Kamau, Everlyn Gicheru, Elijah Eyase, Fredrick Otieno, Grieven P. Munywoki, Patrick K. Agoti, C.N. Nokes, D.J. |
author_sort | Morobe, John Mwita |
collection | PubMed |
description | Background: Human rhinovirus (HRV) is the predominant cause of upper respiratory tract infections, resulting in a significant public health burden. The virus circulates as many different types (168), each generating strong homologous, but weak heterotypic, immunity. The influence of these features on transmission patterns of HRV in the community is understudied. Methods: Nasopharyngeal swabs were collected from patients with symptoms of acute respiratory infection (ARI) at nine out-patient facilities across a Health and Demographic Surveillance System between December 2015 and November 2016. HRV was diagnosed by real-time RT-PCR, and the VP4/VP2 genomic region of the positive samples sequenced. Phylogenetic analysis was used to determine the HRV types. Classification models and G-test statistic were used to investigate HRV type spatial distribution. Demographic characteristics and clinical features of ARI were also compared. Results: Of 5,744 NPS samples collected, HRV was detected in 1057 (18.4%), of which 817 (77.3%) were successfully sequenced. HRV species A, B and C were identified in 360 (44.1%), 67 (8.2%) and 390 (47.7%) samples, respectively. In total, 87 types were determined: 39, 10 and 38 occurred within species A, B and C, respectively. HRV types presented heterogeneous temporal patterns of persistence. Spatially, identical types occurred over a wide distance at similar times, but there was statistically significant evidence for clustering of types between health facilities in close proximity or linked by major road networks. Conclusion: This study records a high prevalence of HRV in out-patient presentations exhibiting high type diversity. Patterns of occurrence suggest frequent and independent community invasion of different types. Temporal differences of persistence between types may reflect variation in type-specific population immunity. Spatial patterns suggest either rapid spread or multiple invasions of the same type, but evidence of similar types amongst close health facilities, or along road systems, indicate type partitioning structured by local spread. |
format | Online Article Text |
id | pubmed-6234744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-62347442018-11-26 Human rhinovirus spatial-temporal epidemiology in rural coastal Kenya, 2015-2016, observed through outpatient surveillance Morobe, John Mwita Nyiro, Joyce U. Brand, Samuel Kamau, Everlyn Gicheru, Elijah Eyase, Fredrick Otieno, Grieven P. Munywoki, Patrick K. Agoti, C.N. Nokes, D.J. Wellcome Open Res Research Article Background: Human rhinovirus (HRV) is the predominant cause of upper respiratory tract infections, resulting in a significant public health burden. The virus circulates as many different types (168), each generating strong homologous, but weak heterotypic, immunity. The influence of these features on transmission patterns of HRV in the community is understudied. Methods: Nasopharyngeal swabs were collected from patients with symptoms of acute respiratory infection (ARI) at nine out-patient facilities across a Health and Demographic Surveillance System between December 2015 and November 2016. HRV was diagnosed by real-time RT-PCR, and the VP4/VP2 genomic region of the positive samples sequenced. Phylogenetic analysis was used to determine the HRV types. Classification models and G-test statistic were used to investigate HRV type spatial distribution. Demographic characteristics and clinical features of ARI were also compared. Results: Of 5,744 NPS samples collected, HRV was detected in 1057 (18.4%), of which 817 (77.3%) were successfully sequenced. HRV species A, B and C were identified in 360 (44.1%), 67 (8.2%) and 390 (47.7%) samples, respectively. In total, 87 types were determined: 39, 10 and 38 occurred within species A, B and C, respectively. HRV types presented heterogeneous temporal patterns of persistence. Spatially, identical types occurred over a wide distance at similar times, but there was statistically significant evidence for clustering of types between health facilities in close proximity or linked by major road networks. Conclusion: This study records a high prevalence of HRV in out-patient presentations exhibiting high type diversity. Patterns of occurrence suggest frequent and independent community invasion of different types. Temporal differences of persistence between types may reflect variation in type-specific population immunity. Spatial patterns suggest either rapid spread or multiple invasions of the same type, but evidence of similar types amongst close health facilities, or along road systems, indicate type partitioning structured by local spread. F1000 Research Limited 2019-03-27 /pmc/articles/PMC6234744/ /pubmed/30483602 http://dx.doi.org/10.12688/wellcomeopenres.14836.2 Text en Copyright: © 2019 Morobe JM et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Morobe, John Mwita Nyiro, Joyce U. Brand, Samuel Kamau, Everlyn Gicheru, Elijah Eyase, Fredrick Otieno, Grieven P. Munywoki, Patrick K. Agoti, C.N. Nokes, D.J. Human rhinovirus spatial-temporal epidemiology in rural coastal Kenya, 2015-2016, observed through outpatient surveillance |
title | Human rhinovirus spatial-temporal epidemiology in rural coastal Kenya, 2015-2016, observed through outpatient surveillance |
title_full | Human rhinovirus spatial-temporal epidemiology in rural coastal Kenya, 2015-2016, observed through outpatient surveillance |
title_fullStr | Human rhinovirus spatial-temporal epidemiology in rural coastal Kenya, 2015-2016, observed through outpatient surveillance |
title_full_unstemmed | Human rhinovirus spatial-temporal epidemiology in rural coastal Kenya, 2015-2016, observed through outpatient surveillance |
title_short | Human rhinovirus spatial-temporal epidemiology in rural coastal Kenya, 2015-2016, observed through outpatient surveillance |
title_sort | human rhinovirus spatial-temporal epidemiology in rural coastal kenya, 2015-2016, observed through outpatient surveillance |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234744/ https://www.ncbi.nlm.nih.gov/pubmed/30483602 http://dx.doi.org/10.12688/wellcomeopenres.14836.2 |
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