Epidemiologic data relating to age and gender specific HIV viral suppression in Rakai, Uganda, 2013-2019
Authors/Creators
-
Brizzi, Andrea
(Contact person)1
- Kagaayi, Joseph (Researcher)2
- Ssekubugu, Robert (Researcher)2
- Abeler-Dörner, Lucie (Researcher)3
- Blenkinsop, Alexandra (Researcher)1
- Bonsall, David (Researcher)3
- Chang, Larry W. (Researcher)4
- Fraser, Christophe (Researcher)3
- Galiwango, Ronald (Researcher)2
- Kigozi, Godfrey (Researcher)5
- Kyle, Imogen (Researcher)1
- Monod, Mélodie (Researcher)1
- Nakigozi, Gertrude (Researcher)2
- Nalugoda, Fred (Researcher)2
- Rosen, Joseph G. (Researcher)6
-
Laeyndecker, Oliver
(Researcher)7
- Quinn, Thomas (Researcher)4
- Graboswki, Kate (Contact person)2
- Reynolds, Reynolds (Contact person)2
- Ratmann, Oliver (Contact person)1
- Rakai Health Sciences Program (Research group)
-
1.
Imperial College London
-
2.
Rakai Health Sciences Program
- 3. Big Data Institute, University of Oxford
-
4.
Johns Hopkins Medicine
- 5. RHSP
- 6. Johns Hopkins Bloomberg School of Public Health
-
7.
National Institute of Allergy and Infectious Diseases
Description
This repository contains the data for the analyses presented in the paper "Age and gender profiles of HIV infection burden and viraemia: novel metrics for HIV epidemic control in African populations with high antiretroviral therapy coverage", soon available as a preprint.
We thank all contributors, program staff, and participants to the Rakai Community Cohort Study.
We also extend our gratitude to the Imperial College Research Computing Service for providing the computational resources to perform this study. Additionally, we thank the Office of Cyberinfrastructure and Computational Biology at the National Institute for Allergy and Infectious Diseases for data management support; and Zulip for sponsoring team communications through the Zulip Cloud Standard chat app.
All analysis code is available from https://github.com/MLGlobalHealth/longi_viral_loads.
Notes
This study was supported by the National Institute of Allergy and Infectious Diseases [U01AI075115 to RHG, R01AI087409 to RHG, U01AI100031 to RHG, ZIAAI001040 to TCQ]; the National Institute of Mental Health [F31MH095649 to Dr Jennifer Wagman, R01MH099733 to Ned Sacktor and MJW, R01MH107275 to LWC]; the Division of Intramural Research of the National Institute for Allergy and Infectious Diseases [TCQ, OL, SJR], NIAID [K01AA024068 to Dr Jennifer Wagman]; the Johns Hopkins University Center for AIDS Research [2P30AI094189 to Dr Richard Chaisson]; the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention [NU2GGH000817 to RHSP]; the Engineering and Physical Sciences Research Council through the EPSRC Centre for Doctoral Training in Modern Statistics and Statistical Machine Learning at Imperial and Oxford [EP/S023151/1 to Prof Axel Gandy]. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
Files
zenodo-longivl.zip
Files
(5.1 GB)
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Additional details
Software
- Repository URL
- https://github.com/MLGlobalHealth/longi_viral_loads
- Programming language
- R