placestats

HIV prevalence vs. Unemployment

Fades after adjusting for income

Across 144 countries, HIV prevalence and Unemployment rise and fall together at r = +0.55 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) leaves r = +0.56, which could easily be chance (q = 0.28, allowing for the many pairs tested, and allowing for countries in the same region being alike). Caution: correlation moves sharply once outliers are trimmed.

Comparing countries across the middle half of unemployment, 3.17% to 8.89% of labor force, hiv prevalence is worse by 1.8% of adults aged 15-49 at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1.78% of adults aged 15-49.

Link before adjusting (r)+0.548p = 1.2e-12 · 144 countries
After adjusting for national income+0.557p = 5.1e-13 · likely range [+0.43, +0.66]
p, allowing for regions0.000standard error 0.063 · 7 regions
Check for luck (q)0.283across 12,497 pairs

How to read these.r runs from −1 (one goes up as the other goes down) to +1 (they rise together), and 0 means no link. Adjusting for national income means comparing countries with the same GDP per person, so differences in wealth can’t explain the link. Income is used in percentage terms, since an extra $1,000 means more to a poor country than to a rich one. p is how likely a link this strong would be if there were really none. Below 0.05 means it is unlikely to be chance. Very small values are written in short form: 1.1e-32 means a decimal point followed by 31 zeros and then 11, so very close to zero. The likely range is where the true figure probably lies, and a range that crosses zero means the link could easily be chance. Countries in the same region tend to resemble each other, so the third figure allows for that, which gives a fairer p. The standard error is the typical size of the error in r. Finally, testing this many pairs means some will look strong by luck alone. A q below 0.05 means this link is unlikely to be one of those.

HIV prevalence · % of adults aged 15-49link with income -0.40 · moderate
Unemployment · % of labor forcelink with income -0.00 · independent

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

HIV prevalence · % of adults aged 15-49 →Unemployment · % of labor force →0.1%23.4%0.13%34.2%Afghanistan: 0.1% of adults aged 15-49, 13.4% of labor forceAngola: 1.6% of adults aged 15-49, 14.1% of labor forceAlbania: 0.1% of adults aged 15-49, 10.9% of labor forceUnited Arab Emirates: 0.1% of adults aged 15-49, 2.17% of labor forceArgentina: 0.4% of adults aged 15-49, 7.14% of labor forceArmenia: 0.4% of adults aged 15-49, 12.9% of labor forceAustralia: 0.1% of adults aged 15-49, 4.09% of labor forceAzerbaijan: 0.1% of adults aged 15-49, 5.46% of labor forceBurundi: 0.8% of adults aged 15-49, 0.922% of labor forceBelgium: 0.2% of adults aged 15-49, 5.91% of labor forceBenin: 0.7% of adults aged 15-49, 1.59% of labor forceBurkina Faso: 0.5% of adults aged 15-49, 3.48% of labor forceBangladesh: 0.1% of adults aged 15-49, 3.78% of labor forceBulgaria: 0.1% of adults aged 15-49, 3.54% of labor forceBahrain: 0.1% of adults aged 15-49, 1.1% of labor forceBahamas, The: 1.1% of adults aged 15-49, 9.21% of labor forceBelize: 1.2% of adults aged 15-49, 8.86% of labor forceBolivia: 0.4% of adults aged 15-49, 2.97% of labor forceBrazil: 0.7% of adults aged 15-49, 5.97% of labor forceBarbados: 1% of adults aged 15-49, 6.52% of labor forceBhutan: 0.2% of adults aged 15-49, 3.23% of labor forceBotswana: 15.7% of adults aged 15-49, 24.5% of labor forceCentral African Republic: 2.4% of adults aged 15-49, 6.25% of labor forceCanada: 0.1% of adults aged 15-49, 6.91% of labor forceSwitzerland: 0.2% of adults aged 15-49, 4.87% of labor forceChile: 0.7% of adults aged 15-49, 8.97% of labor forceCote d'Ivoire: 1.7% of adults aged 15-49, 2.32% of labor forceCameroon: 2.5% of adults aged 15-49, 3.6% of labor forceCongo, Dem. Rep.: 0.7% of adults aged 15-49, 4.43% of labor forceCongo, Rep.: 3.2% of adults aged 15-49, 19.9% of labor forceColombia: 0.6% of adults aged 15-49, 8.29% of labor forceComoros: 0.1% of adults aged 15-49, 3.82% of labor forceCabo Verde: 0.9% of adults aged 15-49, 11.9% of labor forceCosta Rica: 0.6% of adults aged 15-49, 6.84% of labor forceGermany: 0.2% of adults aged 15-49, 3.71% of labor forceDjibouti: 0.9% of adults aged 15-49, 26% of labor forceDenmark: 0.1% of adults aged 15-49, 5.53% of labor forceDominican Republic: 1% of adults aged 15-49, 5.09% of labor forceAlgeria: 0.1% of adults aged 15-49, 11.6% of labor forceEcuador: 0.4% of adults aged 15-49, 3.31% of labor forceEgypt, Arab Rep.: 0.1% of adults aged 15-49, 6.78% of labor forceSpain: 0.3% of adults aged 15-49, 10.4% of labor forceEstonia: 0.7% of adults aged 15-49, 8.31% of labor forceEthiopia: 0.7% of adults aged 15-49, 3.32% of labor forceFiji: 1% of adults aged 15-49, 5.35% of labor forceFrance: 0.3% of adults aged 15-49, 7.54% of labor forceGabon: 2.8% of adults aged 15-49, 20.2% of labor forceUnited Kingdom: 0.2% of adults aged 15-49, 4.75% of labor forceGeorgia: 0.4% of adults aged 15-49, 12.1% of labor forceGhana: 1.5% of adults aged 15-49, 2.98% of labor forceGuinea: 1.3% of adults aged 15-49, 5.16% of labor forceGambia, The: 1.3% of adults aged 15-49, 6.52% of labor forceGuinea-Bissau: 2.2% of adults aged 15-49, 2.67% of labor forceGreece: 0.3% of adults aged 15-49, 8.54% of labor forceGuatemala: 0.2% of adults aged 15-49, 2.6% of labor forceGuyana: 1.6% of adults aged 15-49, 12% of labor forceHonduras: 0.2% of adults aged 15-49, 4.92% of labor forceCroatia: 0.1% of adults aged 15-49, 5% of labor forceHaiti: 1.6% of adults aged 15-49, 14.9% of labor forceIndonesia: 0.4% of adults aged 15-49, 3.24% of labor forceIndia: 0.2% of adults aged 15-49, 4.22% of labor forceIreland: 0.2% of adults aged 15-49, 4.63% of labor forceIraq: 0.1% of adults aged 15-49, 15.5% of labor forceIceland: 0.1% of adults aged 15-49, 3.63% of labor forceItaly: 0.3% of adults aged 15-49, 6.39% of labor forceJamaica: 1.1% of adults aged 15-49, 3.29% of labor forceJordan: 0.1% of adults aged 15-49, 16.5% of labor forceKazakhstan: 0.3% of adults aged 15-49, 4.77% of labor forceKenya: 3% of adults aged 15-49, 5.45% of labor forceKyrgyz Republic: 0.3% of adults aged 15-49, 3.53% of labor forceCambodia: 0.5% of adults aged 15-49, 0.263% of labor forceKuwait: 0.1% of adults aged 15-49, 2.18% of labor forceLao PDR: 0.4% of adults aged 15-49, 1.19% of labor forceLebanon: 0.1% of adults aged 15-49, 11% of labor forceLiberia: 0.9% of adults aged 15-49, 2.88% of labor forceLibya: 0.1% of adults aged 15-49, 18.8% of labor forceSt. Lucia: 0.4% of adults aged 15-49, 9.45% of labor forceSri Lanka: 0.1% of adults aged 15-49, 4% of labor forceLesotho: 17.1% of adults aged 15-49, 16.3% of labor forceLithuania: 0.2% of adults aged 15-49, 6.73% of labor forceLuxembourg: 0.3% of adults aged 15-49, 6.34% of labor forceLatvia: 0.5% of adults aged 15-49, 6.57% of labor forceMorocco: 0.1% of adults aged 15-49, 9% of labor forceMoldova: 0.9% of adults aged 15-49, 1.5% of labor forceMadagascar: 0.5% of adults aged 15-49, 3.04% of labor forceMaldives: 0.1% of adults aged 15-49, 4.51% of labor forceMexico: 0.5% of adults aged 15-49, 2.67% of labor forceNorth Macedonia: 0.1% of adults aged 15-49, 12.3% of labor forceMali: 0.8% of adults aged 15-49, 2.83% of labor forceMalta: 0.3% of adults aged 15-49, 2.9% of labor forceMyanmar: 0.9% of adults aged 15-49, 3.05% of labor forceMontenegro: 0.1% of adults aged 15-49, 13.6% of labor forceMongolia: 0.1% of adults aged 15-49, 5.23% of labor forceMozambique: 11.5% of adults aged 15-49, 6.63% of labor forceMauritania: 0.1% of adults aged 15-49, 10.3% of labor forceMalawi: 6.2% of adults aged 15-49, 5.07% of labor forceMalaysia: 0.3% of adults aged 15-49, 3.76% of labor forceNamibia: 9% of adults aged 15-49, 19.3% of labor forceNiger: 0.2% of adults aged 15-49, 0.394% of labor forceNigeria: 1.2% of adults aged 15-49, 3.06% of labor forceNetherlands: 0.1% of adults aged 15-49, 3.87% of labor forceNorway: 0.1% of adults aged 15-49, 4.64% of labor forceNepal: 0.1% of adults aged 15-49, 10.5% of labor forceNew Zealand: 0.1% of adults aged 15-49, 5.08% of labor forceOman: 0.1% of adults aged 15-49, 3.25% of labor forcePakistan: 0.2% of adults aged 15-49, 5.42% of labor forcePanama: 1.1% of adults aged 15-49, 8.36% of labor forcePeru: 0.4% of adults aged 15-49, 5.12% of labor forcePhilippines: 0.3% of adults aged 15-49, 2.23% of labor forcePapua New Guinea: 1.5% of adults aged 15-49, 2.57% of labor forcePortugal: 0.5% of adults aged 15-49, 6.16% of labor forceParaguay: 0.5% of adults aged 15-49, 4.8% of labor forceQatar: 0.1% of adults aged 15-49, 0.13% of labor forceRomania: 0.2% of adults aged 15-49, 5.99% of labor forceRwanda: 2% of adults aged 15-49, 11.4% of labor forceSaudi Arabia: 0.1% of adults aged 15-49, 3.04% of labor forceSudan: 0.2% of adults aged 15-49, 7.53% of labor forceSenegal: 0.3% of adults aged 15-49, 2.73% of labor forceSingapore: 0.1% of adults aged 15-49, 2.82% of labor forceSolomon Islands: 0.1% of adults aged 15-49, 1.43% of labor forceSierra Leone: 1.4% of adults aged 15-49, 3.15% of labor forceEl Salvador: 0.4% of adults aged 15-49, 3.3% of labor forceSomalia, Fed. Rep.: 0.1% of adults aged 15-49, 18.9% of labor forceSerbia: 0.1% of adults aged 15-49, 7.12% of labor forceSuriname: 1.6% of adults aged 15-49, 7.83% of labor forceSlovak Republic: 0.1% of adults aged 15-49, 5.36% of labor forceSlovenia: 0.1% of adults aged 15-49, 3.17% of labor forceSweden: 0.1% of adults aged 15-49, 8.69% of labor forceEswatini: 23.4% of adults aged 15-49, 34.2% of labor forceSyrian Arab Republic: 0.1% of adults aged 15-49, 13.6% of labor forceChad: 0.9% of adults aged 15-49, 1.06% of labor forceTogo: 1.6% of adults aged 15-49, 2% of labor forceThailand: 1% of adults aged 15-49, 0.781% of labor forceTajikistan: 0.2% of adults aged 15-49, 6.93% of labor forceTimor-Leste: 0.2% of adults aged 15-49, 1.59% of labor forceTunisia: 0.1% of adults aged 15-49, 15.1% of labor forceTanzania: 3.5% of adults aged 15-49, 1.57% of labor forceUganda: 4.9% of adults aged 15-49, 2.75% of labor forceSt. Vincent and the Grenadines: 0.8% of adults aged 15-49, 18% of labor forceViet Nam: 0.4% of adults aged 15-49, 1.52% of labor forceVanuatu: 0.1% of adults aged 15-49, 5.07% of labor forceSouth Africa: 17.2% of adults aged 15-49, 32.4% of labor forceZambia: 9.4% of adults aged 15-49, 5.92% of labor forceZimbabwe: 9.8% of adults aged 15-49, 9.29% of labor forceBWADJIKHMLBYLSOMOZNERQATSOMSWZZAFZMB

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5481.2e-12144
By rank (Spearman), not adjusted+0.0460.583144
Standard (Pearson), adjusted for national income+0.5575.1e-13144
By rank (Spearman), adjusted for national income+0.0880.295144

The rank version uses only each country’s place in line, from lowest to highest, so a few extreme countries count for less. The adjusted and unadjusted versions use the same 144 countries: those that report both measures and GDP per person. So the gap between them comes from the adjustment, not from a change in which countries are counted. Drop in the size of r after adjusting: -0.009 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.448 (without SWZ) to +0.585 (without DJI). The bar above shows that range on a scale from −1 to +1, with the solid line at the full result. The single country that moves r most: SWZ (-0.109).

Fragile: this link may not hold up.
  • correlation moves sharply once outliers are trimmed
  • direction is not consistent across regions

Within each region

Countries are not separate, unrelated cases, and neighbors share a lot. A link that holds inside each region is far more believable than one that shows up only when comparing regions.

nr
East Asia & Pacific17-0.11
Europe & Central Asia35-0.07
Latin America & Caribbean24+0.54
Middle East, North Africa, Afghanistan & Pakistan19+0.53
Sub-Saharan Africa42+0.67

By income third

If the link shows up only in the richest third of countries, it is a feature of rich countries, not a general pattern.

nr
Poorest third48+0.21
Middle third48+0.77
Richest third48+0.40

By largest religious group

Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.

nr
Christians89+0.73
Muslims42-0.31

By last european coloniser

Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.

nr
France25+0.34
Never a European colony14-0.46
Spain16-0.04
United Kingdom47+0.71

Without outliers (countries far outside the middle half of countries on either measure, by more than one and a half times the width of that middle half): r = +0.018 after dropping 20 countries.

Two series, one country

Both measures over the years for one country you pick. The two charts are stacked so they share only the years along the bottom.

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Over time, within countries

Everything above compares countries with each other at one moment. This section compares each country only with itself over 34years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Within countries over time, there is no link that is clearly more than chance (r = +0.032, comparing each country only with itself over the years, and each year only with the same year elsewhere). Whatever the cross-country picture shows, countries whose hiv prevalence moved did not tend to see their unemployment move with it.

Across countries (adjusted)+0.557for comparison
Within countries+0.046each country vs itself
…and vs the same year elsewhere+0.032q = 0.690 · 148 countries
Year-on-year changes-0.009q = 0.736
Read with care.
  • Almost all of the second indicator's variation is between countries, so the within-country estimate rests on a small part of the data.

4,977 country-years (one country in one year), 148 countries, 1991–2024, about 34 years each on average. Share of the variation that happens within countries over time: 14% for HIV prevalence, 9% for Unemployment. The margins of error allow for each country appearing many times, and for each year’s value being close to the year before.

Year-to-year changes are a cautious test, not a final answer. Looking only at changes from one year to the next removes each country’s own trends. But it also makes measurement mistakes louder, which pulls the results toward zero. A near-zero result here is weak evidence of no link, not proof.

With one measure years behind the other

0.10−0.1-100+10years Unemployment trails HIV prevalence →lag -10: r = 0.043 (n = 3,521)lag -9: r = 0.045 (n = 3,667)lag -8: r = 0.042 (n = 3,813)lag -7: r = 0.037 (n = 3,959)lag -6: r = 0.032 (n = 4,105)lag -5: r = 0.027 (n = 4,251)lag -4: r = 0.026 (n = 4,397)lag -3: r = 0.025 (n = 4,543)lag -2: r = 0.024 (n = 4,689)lag -1: r = 0.027 (n = 4,834)lag +0: r = 0.032 (n = 4,977)lag +1: r = 0.039 (n = 5,120)lag +2: r = 0.043 (n = 4,977)lag +3: r = 0.048 (n = 4,831)lag +4: r = 0.052 (n = 4,683)lag +5: r = 0.057 (n = 4,535)lag +6: r = 0.061 (n = 4,383)lag +7: r = 0.064 (n = 4,236)lag +8: r = 0.067 (n = 4,089)lag +9: r = 0.068 (n = 3,942)lag +10: r = 0.063 (n = 3,795)

Same year (lag 0): +0.032. A peak away from zero does not show which comes first. These series change slowly — this year’s value is close to last year’s. That makes the curve smooth and nearly symmetric, whatever produced the data. Even a sharp peak at one lag (a gap of some years) would not prove that one measure changes the other.

The data


% of adults aged 15-49
% of labor force		Years
Eswatini SWZ23.4%34.2%2024, 2025
South Africa ZAF17.2%32.4%2024, 2025
Lesotho LSO17.1%16.3%2024, 2025
Botswana BWA15.7%24.5%2024, 2025
Mozambique MOZ11.5%6.63%2024, 2025
Zimbabwe ZWE9.8%9.29%2024, 2025
Zambia ZMB9.4%5.92%2024, 2025
Namibia NAM9%19.3%2024, 2025
Malawi MWI6.2%5.07%2024, 2025
Uganda UGA4.9%2.75%2024, 2025
Tanzania TZA3.5%1.57%2024, 2025
Congo, Rep. COG3.2%19.9%2024, 2025
Kenya KEN3%5.45%2024, 2025
Gabon GAB2.8%20.2%2024, 2025
Cameroon CMR2.5%3.6%2024, 2025

World Bank, World Development Indicators
World Bank, World Development Indicators

Sources

HIV prevalence

Prevalence of HIV, total (% of population ages 15-49)

UNAIDS · CC BY 4.0 · updated quarterly

Estimates from a statistical model. Very lopsided: a few southern African countries sit about ten times higher than everyone else. So a link with this is largely a link with them, and the "leave one out" check on each pair page shows by how much.

Unemployment

Unemployment, total (% of total labor force) (modeled ILO estimate)

International Labour Organization · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2022–2025. To adjust for income, each measure is first predicted from GDP per person (in percentage terms, on a log scale) with a straight-line fit. Only what is left over is then compared. This is called a partial correlation. The line is drawn the standard way (ordinary least squares), which picks the line that comes closest to all the countries at once. The error margins allow for countries in the same region resembling each other, using 7 World Bank regions. The q-value corrects for testing all 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore HIV prevalence and Unemployment

This page shows that two measures go together. It does not show that HIV prevalence changes Unemployment, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with HIV prevalence or Unemployment