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Data for Human rhinovirus spatial-temporal epidemiology in rural coastal Kenya, 2015-2016, observed through outpatient surveillance
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Morobe, John Mwita, Nyiro, Joyce U., Brand, Samuel, Kamau, Everlyn, Munywoki, Patrick K., Agoti, Charles N. and Nokes, D. James (2018) Data for Human rhinovirus spatial-temporal epidemiology in rural coastal Kenya, 2015-2016, observed through outpatient surveillance. [Dataset]
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Official URL: https://doi.org/10.7910/DVN/DUQNDX
Abstract
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 (~160), 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.
| Item Type: | Dataset | |||||||||
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| Subjects: | Q Science > QR Microbiology > QR355 Virology | |||||||||
| Divisions: | Faculty of Science > Life Sciences (2010- ) | |||||||||
| Type of Data: | Observational data | |||||||||
| Library of Congress Subject Headings (LCSH): | Rhinoviruses -- Epidemiology -- Kenya, Respiratory infections -- Kenya, Rural health -- Kenya | |||||||||
| Publisher: | Harvard Dataverse | |||||||||
| Official Date: | 21 September 2018 | |||||||||
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| Status: | Not Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Media of Output: | .do .tab .fas .m .ows .xls | |||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||
| Copyright Holders: | University of Warwick | |||||||||
| Description: | Data record consists of 8 data files, in .do, .tab .fas, .m, .ows and .xls format, as well as a readme file, separate data codebook, and .tiff file showing workflow. |
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