README.md

metadata

license: cc-by-4.0
task_categories:
  - tabular-classification
language:
  - en
tags:
  - laboratory
  - HIV
  - viral-load
  - CD4
  - ART-monitoring
  - synthetic
  - sub-saharan-africa
pretty_name: HIV Viral Load & CD4 Testing
size_categories:
  - 10K<n<100K
configs:
  - config_name: vl_accessible
    data_files: data/hiv_vl_cd4_vl_accessible.csv
  - config_name: vl_limited
    data_files: data/hiv_vl_cd4_vl_limited.csv
    default: true
  - config_name: no_vl_access
    data_files: data/hiv_vl_cd4_no_vl_access.csv
data_type: synthetic

⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference.

HIV Viral Load & CD4 Testing

Abstract

Synthetic dataset modeling HIV viral load and CD4 laboratory services across three SSA scenarios. Captures VL/CD4 test availability, platforms (conventional/POC/DBS), results, turnaround times, clinical actions (EAC, regimen switch), and quality indicators. Parameterized from WHO/UNAIDS guidelines and SSA implementation research.

Parameterization Evidence

Parameter	Value	Source	Year
VL coverage SSA	17% to 71% (2015-2019)	Lecher et al. MMWR	2021
VL suppression on ART	76% SSA	UNAIDS	2023
Conventional VL TAT	2-6 weeks	Jani et al. Lancet HIV	2016
POC VL TAT	1-3 hours	Jani et al.	2016
SSA PLHIV on ART	21M / 25.6M	UNAIDS	2023

Validation

Usage

from datasets import load_dataset
ds = load_dataset("electricsheepafrica/hiv-viral-load-cd4", name="vl_limited")
df = ds['train'].to_pandas()

References

1. WHO (2023). HIV treatment guidelines
2. UNAIDS (2023). Global HIV statistics
3. Lecher SL et al. (2021). VL monitoring scale-up. MMWR. DOI: 10.15585/mmwr.mm7034a2
4. Jani IV et al. (2016). POC CD4 and VL. Lancet HIV. DOI: 10.1016/S2352-3018(15)00236-X

License

CC-BY-4.0