Replication Data for: Infection patterns of endemic human coronaviruses in rural households in coastal Kenya

Version 2.1
Replication Data for: Infection patterns of endemic human coronaviruses in rural households in coastal Kenya
Nyaguthii, Dickson Machira; Otieno, Grieven P.; Kombe, Ivy K.; Koech, Dorothy; Mutunga, Martin; Medley, Graham F.; Nokes, David James; Munywoki, Patrick K., 2020, "Replication Data for: Infection patterns of endemic human coronaviruses in rural households in coastal Kenya", https://doi.org/10.7910/DVN/CPJ9B4, Harvard Dataverse, V2
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Description

This is a replication dataset for the manuscript "Infection patterns of endemic human coronaviruses in rural households in coastal Kenya" submitted to Wellcome Open Research journal.

This dataset is part from a cohort study conducted in rural coastal Kenya between December 2009 and June 2020. The study recruited 47 households, each with an infant, containing 483 members. nasopharyngeal samples were taken from study participants every 3-4 days and screened for 3 hCoVs (OC43, NL63 and 229E) and several other respiratory viral pathogens using real-time polymerase chain reaction (RT-PCR).

Subject Medicine, Health and Life Sciences
Related Publication Munywoki PK, Koech DC, Agoti CN, Cane PA, Medley GF, Nokes DJ. Continuous Invasion by Respiratory Viruses Observed in Rural Households During a Respiratory Syncytial Virus Seasonal Outbreak in Coastal Kenya. Clin Infect Dis Off Publ Infect Dis Soc Am. 2018; 67(10):1559–1567doi: 10.1093/cid/ciy313
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GPOtieno_hCoV_WAIFW_codebook.pdf
GPOtieno_hCoV_WAIFW_codebook.pdf
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Contains variable descriptions and value labels
DocumentationVariable Codebook/Data Dictionary
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GPOtieno_HCoV_WAIFW_Readme.txt
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Contains data description, file listing and terms of use
DocumentationReadme
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GPOtieno_HCoV_WAIFW_data.zip
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Published Dec 8, 2020
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Analysis datasets (STATA v13.1)
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GPOtieno_HCoV_WAIFW_scripts.zip
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Analysis code (STATA v13.1)
CodeSTATA
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Supplementary Tables and figures.pdf
Supplementary Tables and figures.pdf
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Published Dec 10, 2020
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MD5: f8a71a7bbb5fec3c7a91a517a1470511
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This data is licensed under the Creative Commons Attribution 4.0 International

For more information on these data, please contact the author via Grieven P. Otieno [grievenoti@gmail.com],Patrick Munywoki [pmunywoki@gmail.com], D. James Nokes [JNokes@kemri-wellcome.org] or the data governance office via this email address: dgc@kemri-wellcome.org.

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