There is a newer version of the record available.

Published August 8, 2022 | Version These data correspond to the report dated 2022-08-03 (https://www.nicd.ac.za/wp-content/uploads/2022/08/SARS%C2%ADCoV%C2%AD2-Reinfection-Trends-in-South-Africa-03082022.pdf)
Dataset Open

Data for SARS­-CoV-­2 Reinfection Trends in South Africa: Monthly Report (2022-08-03)

Authors/Creators

  • 1. South African DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, South Africa
  • 2. South African DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, South Africa; McMaster University, Canada
  • 3. National Institute for Communicable Diseases, Division of the National Health Laboratory Service, South Africa
  • 4. National Institute for Communicable Diseases, Division of the National Health Laboratory Service, South Africa; School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
  • 5. National Health Laboratory Service, South Africa; School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, South Africa; Centre for the AIDS Programme of Research in South Africa (CAPRISA), South Africa

Description

This version contains a single file, with time series data for the most recent monthly report on SARS­-CoV-­2 Reinfection Trends in South Africa:

  • ts_data.csv - national daily time series of newly detected putative primary infections (cnt), suspected second infections (reinf), suspected third infections (third), and suspected fourth infections (fourth) by specimen receipt date (date)

Note: There may be some inconsistencies with the numbers of infections through time in earlier versions of this data set due to back-filling of late-arriving data.

 

Note: The previous version of this data set included data files for Pulliam, JRC, C van Schalkwyk, B Lombard, N Govender, A von Gottberg, C Cohen, MJ Groome, J Dushoff, K Mlisana, and H Moultrie. Increased risk of SARS-CoV-2 reinfection associated with emergence of Omicron in South Africa. DOI: 0.1126/science.abn4947

For code and more details see: https://github.com/jrcpulliam/reinfections/releases/tag/v3.0 or 10.5281/zenodo.6108448

The previous version of this data set (available via the links above) included the following files:

  • ts_data.csv - national daily time series of newly detected putative primary infections (cnt), suspected second infections (reinf), suspected third infections (third), and suspected fourth infections (fourth) by specimen receipt date (date)
  • demog_data.csv - counts of individuals eligible for reinfection (total), who have 0 suspected reinfections (no_reinf) or >0 suspected reinfections (reinf) by province (province), age group (5-year bands, agegrp5), and sex (M = Male, F = Female, U = Unknown, sex)
  • posterior_90_null.RData - posterior samples from the MCMC fitting procedure (as used in the manuscript)
  • sim_90_null.RDS - simulation results (as used in the manuscript)
  • emp_haz_sens_an.RDS - output of sensitivity analysis of relative empirical hazard estimation to assumed observation probabilities (as used in the manuscript)

Notes

The data provided here cover the period from 2021-03-04 to 2022-07-27.

Files

ts_data.csv

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Additional details

Related works

Is published in
Report: https://www.nicd.ac.za/wp-content/uploads/2022/08/SARS%C2%ADCoV%C2%AD2-Reinfection-Trends-in-South-Africa-03082022.pdf (URL)
Is supplement to
Software: https://github.com/jrcpulliam/reinfections (URL)
Journal article: https://www.science.org/doi/10.1126/science.abn4947 (URL)
Dataset: 10.5281/zenodo.6108448 (DOI)

Funding

Wellcome Trust
Characterization of SARS-CoV-2 transmission dynamics, clinical features and disease impact in South Africa, a setting with high HIV prevalence 221003