Replication Data for: Revealing the extent of the COVID-19 pandemic in Kenya based on serological and PCR-test data

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Replication Data for: Revealing the extent of the COVID-19 pandemic in Kenya based on serological and PCR-test data
Ojal, John; Brand, Samuel P. C.; Were, Vincent; Okiro, Emelda A.; Kombe, Ivy K.; Mburu, Caroline; Aziza, Rabia; Ogero, Morris; Agweyu, Ambrose; Warimwe, George M.; Uyoga, Sophie; Adetifa, Ifedayo M. O.; Scott, J. Anthony G.; Otieno, Edward; Ochola-Oyier, Lynette Isabella; Agoti, Charles N.; Kasera, Kadondi; Amoth, Patrick; Mwangangi, Mercy; Aman, Rashid; Ng’ang’a, Wangari; Tsofa, Benjamin; Bejon, Philip; Barasa, Edwine; Keeling, Matt. J.; Nokes, David James, 2020, "Replication Data for: Revealing the extent of the COVID-19 pandemic in Kenya based on serological and PCR-test data", https://doi.org/10.7910/DVN/RXAIPS, Harvard Dataverse, V2, UNF:6:zpkOX7HPsfYNae1dhR7xqQ== [fileUNF]
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Description

This is a replication dataset for the submitted manuscript "Ojal, J., Brand, S.P., Were, V., Okiro, E.A., Kombe, I.K., Mburu, C., Aziza, R., Ogero, M., Agweyu, A., Warimwe, G.M. and Uyoga, S., 2020. Revealing the extent of the COVID-19 pandemic in Kenya based on serological and PCR-test data. medRxiv.".

The related study was conducted to estimate the SARS-CoV-2 pandemic peak and COVID-19 disease burden including reported severe cases and deaths in the major urban counties in Kenya. National surveillance PCR tests, serological surveys, and mobility data were used to develop and fit a county-specific transmission model in the country.

These datasets presented contain the number of positive PCR-confirmed swab tests for each county by date of sample collection (21st Feb to 6th August), the number of positive and negative serological results for each county by date of sample collection (21st Feb to 6th August), number of deaths with a PCR-confirmed swab test for each county by recorded date of death (21st Feb to 6th August), the total number of swab samples collected in Mombasa county, and analyzed at Kemri-Wellcome Research Program testing center (21st Feb – 27th June), and summary data of Kenyan epidemic, including reported total number of test performed. The datasets are used for COVID-19 forecasts.

Subject Medicine, Health and Life Sciences
Related Publication Ojal, J., Brand, S.P., Were, V., Okiro, E.A., Kombe, I.K., Mburu, C., Aziza, R., Ogero, M., Agweyu, A., Warimwe, G.M. and Uyoga, S., 2020. Revealing the extent of the COVID-19 pandemic in Kenya based on serological and PCR-test data. medRxiv.doi: 10.1101/2020.09.02.20186817
Notes Data Analysis Code Avaialbility

The code used to simulate transmission in Kenyan counties and is fitted to the data provided here is available in the open access Github repository https://github.com/ojal/KenyaSerology . This includes a sequence of notebooks which outline each step of the analysis to aid reproducibility.

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OJAL_BRAND_KENYANCOVIDFIRSTWAVE_Codebook.pdf
OJAL_BRAND_KENYANCOVIDFIRSTWAVE_Codebook.pdf
Adobe PDF - 239.8 KB
Published Mar 15, 2021
13 Downloads
MD5: a32b9a82d570e0c4f3b46cb9bef8cc53
A codebook describing each field of the datafiles DataS1.csv - DataS7.csv
DocumentationData Dictionary/Variable Codebook
Preview "OJAL_BRAND_KENYANCOVIDFIRSTWAVE_Codebook.pdf"
OJAL_BRAND_KENYANCOVIDFIRSTWAVE_Readme.txt
Plain Text - 6.5 KB
Published Mar 15, 2021
10 Downloads
MD5: f7b63362d930be377e812b7ed44a6237
DocumentationData Readme
Preview "OJAL_BRAND_KENYANCOVIDFIRSTWAVE_Readme.txt"
supp_material.docx
MS Word - 896.4 KB
Published Mar 15, 2021
12 Downloads
MD5: c6134d0357b243e8f2dc2ce53614b9c2
contains extensive extra description of the mathematical/statistical assumptions underlying the transmission model
DocumentationSupplementary File
DataS1.tab
Tabular Data - 10.5 KB
Published Mar 15, 2021
33 Downloads
11 Variables, 47 Observations UNF:6:eHeoX3dijRNsdcwBk7+NcQ==
Inferred model parameters, IFR and posterior predictive P-value for each Kenyan county where the effective contact rates were inferred jointly with other parameters
DataCSV
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DataS2.tab
Tabular Data - 10.5 KB
Published Mar 15, 2021
14 Downloads
11 Variables, 47 Observations UNF:6:j7v/dGWBms50IcrmRlcHnQ==
Inferred model parameters, IFR and posterior predictive P-value for each county where the effective contact rates were assumed to follow Google mobility trends
DataCSV
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DataS3.tab
Tabular Data - 4.4 KB
Published Mar 15, 2021
17 Downloads
9 Variables, 47 Observations UNF:6:/5o/WWrmsCd7Vnje4t1tXQ==
Model comparison scores between Google and fitted effective contact rate models, Deviance information criteria (DIC), log-predictive density of daily death incidence (LPD) and posterior predictive P value of daily deaths
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DataS4.tab
Tabular Data - 55.1 KB
Published Mar 15, 2021
16 Downloads
95 Variables, 223 Observations UNF:6:AQqhWe/1c2MQOePGS8jQ6A==
Daily reported swab test results (maximum one per person) with test result
DataCSV
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DataS5.tab
Tabular Data - 22.6 KB
Published Mar 15, 2021
15 Downloads
61 Variables, 168 Observations UNF:6:yBVY6SpnBY9YcjVNXP7Bfg==
Daily reported serological test results (maximum one per person) with test result
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DataS6.tab
Tabular Data - 24.8 KB
Published Mar 15, 2021
24 Downloads
48 Variables, 240 Observations UNF:6:LPYkqFZtiBDLDa+6twMYcQ==
Daily reported deaths with positive test result
DataCSV
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DataS7.tab
Tabular Data - 30.3 KB
Published Mar 15, 2021
14 Downloads
34 Variables, 151 Observations UNF:6:pxnpKG+3OMP7c0wTdQdyZw==
Summary data sourced from ourworldindata.org, only new_tests field was used to scale the detection rate of PCR positives when total tests per county per day was unavailable.
DataCSV
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