Key Takeaways
- In 2023, 7.4 million people were living with HIV in sub-Saharan Africa, and women and girls (15+) accounted for 58% of people living with HIV in the region.
- In 2023, globally, 29.8 million people were living with HIV, and 18.6 million were women (including adolescent girls) as reported by UNAIDS.
- In 2023, new HIV infections among adults (15+) were 1.3 million globally, and 44% of new infections among adults (15+) were among women.
- In the US, females accounted for about 30% of new HIV diagnoses in 2022.
- In the US, 11% of people with HIV were undiagnosed in 2020, with women contributing to the undiagnosed population.
- In 2022 in the US, 87% of people with HIV knew their status; for women this varies by age group but overall status knowledge is reflected in CDC cascade reporting.
- In the US HIV care continuum (2021), 84% of women were on ART (among those diagnosed with HIV).
- In the US HIV care continuum (2021), 72% of women achieved viral suppression.
- In the US, 59% of women with HIV had viral suppression in 2018 per CDC estimates.
- In 2022, global new HIV infections among women and girls were concentrated in age group 15–24, with adolescent girls and young women at higher risk.
- In 2023, women accounted for 55% of new HIV infections in sub-Saharan Africa among all ages.
- In 2022, nearly half of new HIV infections in sub-Saharan Africa occurred among women and adolescent girls.
- In the US, in 2021, women represented 23% of persons diagnosed with HIV who received ART.
- In the US, women accounted for 23% of those with diagnosed HIV in care in 2021 per CDC care continuum reporting.
- In CDC surveillance, in 2022 females accounted for 27% of new diagnoses (all transmission categories).
Women and girls account for most HIV burden globally, with disproportionate new infections and AIDS deaths.
Epidemiology & Burden
Epidemiology & Burden Interpretation
Testing, Diagnosis & Linkage
Testing, Diagnosis & Linkage Interpretation
Prevention, Risk & Mother-to-Child
Prevention, Risk & Mother-to-Child Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Samuel Norberg. (2026, February 13). Women Hiv Statistics. Gitnux. https://gitnux.org/women-hiv-statistics
Samuel Norberg. "Women Hiv Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/women-hiv-statistics.
Samuel Norberg. 2026. "Women Hiv Statistics." Gitnux. https://gitnux.org/women-hiv-statistics.
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