placestats

HIV prevalence vs. Out-of-pocket health spending

Holds up after adjusting for income

Across 148 countries, HIV prevalence and Out-of-pocket health spending rise and fall together at r = -0.27 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = -0.39, q = 0.0093, allowing for the many pairs tested). Caution: correlation moves sharply once outliers are trimmed.

Comparing countries across the middle half of hiv prevalence, 0.1% to 1% of adults aged 15-49, out-of-pocket health spending is better by 1.33% of health spending at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1.84% of health spending.

Link before adjusting (r)-0.267p = 0.001 · 148 countries
After adjusting for national income-0.389p = 1.1e-6 · likely range [-0.52, -0.24]
p, allowing for regions0.000standard error 0.050 · 7 regions
Check for luck (q)0.009across 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
Out-of-pocket health spending · % of health spendinglink with income -0.34 · moderate

“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 →Out-of-pocket health spending · % of health spending →0.1%23.4%0.0446%80.5%Afghanistan: 0.1% of adults aged 15-49, 77.1% of health spendingAngola: 1.6% of adults aged 15-49, 32.5% of health spendingAlbania: 0.1% of adults aged 15-49, 48.3% of health spendingUnited Arab Emirates: 0.1% of adults aged 15-49, 9.67% of health spendingArgentina: 0.4% of adults aged 15-49, 24.5% of health spendingArmenia: 0.4% of adults aged 15-49, 80.5% of health spendingAntigua and Barbuda: 1.1% of adults aged 15-49, 20.8% of health spendingAustralia: 0.1% of adults aged 15-49, 15.8% of health spendingAzerbaijan: 0.1% of adults aged 15-49, 64.6% of health spendingBurundi: 0.8% of adults aged 15-49, 24.5% of health spendingBelgium: 0.2% of adults aged 15-49, 21.5% of health spendingBenin: 0.7% of adults aged 15-49, 42.4% of health spendingBurkina Faso: 0.5% of adults aged 15-49, 43.8% of health spendingBangladesh: 0.1% of adults aged 15-49, 79.3% of health spendingBulgaria: 0.1% of adults aged 15-49, 35.5% of health spendingBahrain: 0.1% of adults aged 15-49, 28.7% of health spendingBahamas, The: 1.1% of adults aged 15-49, 27.5% of health spendingBelize: 1.2% of adults aged 15-49, 26.8% of health spendingBolivia: 0.4% of adults aged 15-49, 27.3% of health spendingBrazil: 0.7% of adults aged 15-49, 26.2% of health spendingBarbados: 1% of adults aged 15-49, 49.5% of health spendingBhutan: 0.2% of adults aged 15-49, 25.5% of health spendingBotswana: 15.7% of adults aged 15-49, 4.26% of health spendingCentral African Republic: 2.4% of adults aged 15-49, 45% of health spendingCanada: 0.1% of adults aged 15-49, 15.3% of health spendingSwitzerland: 0.2% of adults aged 15-49, 22% of health spendingChile: 0.7% of adults aged 15-49, 39.1% of health spendingCote d'Ivoire: 1.7% of adults aged 15-49, 32% of health spendingCameroon: 2.5% of adults aged 15-49, 67.7% of health spendingCongo, Dem. Rep.: 0.7% of adults aged 15-49, 38% of health spendingCongo, Rep.: 3.2% of adults aged 15-49, 28% of health spendingColombia: 0.6% of adults aged 15-49, 14.7% of health spendingComoros: 0.1% of adults aged 15-49, 56.6% of health spendingCabo Verde: 0.9% of adults aged 15-49, 25.7% of health spendingCosta Rica: 0.6% of adults aged 15-49, 24.1% of health spendingGermany: 0.2% of adults aged 15-49, 10.7% of health spendingDjibouti: 0.9% of adults aged 15-49, 28.8% of health spendingDominica: 0.5% of adults aged 15-49, 29.3% of health spendingDenmark: 0.1% of adults aged 15-49, 13.9% of health spendingDominican Republic: 1% of adults aged 15-49, 25.1% of health spendingAlgeria: 0.1% of adults aged 15-49, 45% of health spendingEcuador: 0.4% of adults aged 15-49, 30.9% of health spendingEgypt, Arab Rep.: 0.1% of adults aged 15-49, 57.2% of health spendingSpain: 0.3% of adults aged 15-49, 20.9% of health spendingEstonia: 0.7% of adults aged 15-49, 21.4% of health spendingEthiopia: 0.7% of adults aged 15-49, 46.3% of health spendingFiji: 1% of adults aged 15-49, 8.31% of health spendingFrance: 0.3% of adults aged 15-49, 9.23% of health spendingGabon: 2.8% of adults aged 15-49, 17.3% of health spendingUnited Kingdom: 0.2% of adults aged 15-49, 14.6% of health spendingGeorgia: 0.4% of adults aged 15-49, 58.8% of health spendingGhana: 1.5% of adults aged 15-49, 26.7% of health spendingGuinea: 1.3% of adults aged 15-49, 54.4% of health spendingGambia, The: 1.3% of adults aged 15-49, 33.8% of health spendingGuinea-Bissau: 2.2% of adults aged 15-49, 61.6% of health spendingGreece: 0.3% of adults aged 15-49, 34.3% of health spendingGuatemala: 0.2% of adults aged 15-49, 57.2% of health spendingGuyana: 1.6% of adults aged 15-49, 26.3% of health spendingHonduras: 0.2% of adults aged 15-49, 53.1% of health spendingCroatia: 0.1% of adults aged 15-49, 9.38% of health spendingHaiti: 1.6% of adults aged 15-49, 52.4% of health spendingIndonesia: 0.4% of adults aged 15-49, 31.1% of health spendingIndia: 0.2% of adults aged 15-49, 43.9% of health spendingIreland: 0.2% of adults aged 15-49, 10.6% of health spendingIraq: 0.1% of adults aged 15-49, 54% of health spendingIceland: 0.1% of adults aged 15-49, 14.9% of health spendingItaly: 0.3% of adults aged 15-49, 22.3% of health spendingJamaica: 1.1% of adults aged 15-49, 20.2% of health spendingJordan: 0.1% of adults aged 15-49, 34.5% of health spendingKazakhstan: 0.3% of adults aged 15-49, 27.6% of health spendingKenya: 3% of adults aged 15-49, 24.2% of health spendingKyrgyz Republic: 0.3% of adults aged 15-49, 42.3% of health spendingCambodia: 0.5% of adults aged 15-49, 60.6% of health spendingSt. Kitts and Nevis: 0.8% of adults aged 15-49, 41.8% of health spendingKuwait: 0.1% of adults aged 15-49, 10% of health spendingLao PDR: 0.4% of adults aged 15-49, 44.8% of health spendingLebanon: 0.1% of adults aged 15-49, 29.7% of health spendingLiberia: 0.9% of adults aged 15-49, 63.2% of health spendingLibya: 0.1% of adults aged 15-49, 19.2% of health spendingSt. Lucia: 0.4% of adults aged 15-49, 37.1% of health spendingSri Lanka: 0.1% of adults aged 15-49, 54.8% of health spendingLesotho: 17.1% of adults aged 15-49, 13.2% of health spendingLithuania: 0.2% of adults aged 15-49, 31.4% of health spendingLuxembourg: 0.3% of adults aged 15-49, 8.5% of health spendingLatvia: 0.5% of adults aged 15-49, 35.1% of health spendingMorocco: 0.1% of adults aged 15-49, 37.3% of health spendingMoldova: 0.9% of adults aged 15-49, 27.5% of health spendingMadagascar: 0.5% of adults aged 15-49, 27.4% of health spendingMaldives: 0.1% of adults aged 15-49, 18% of health spendingMexico: 0.5% of adults aged 15-49, 41.2% of health spendingNorth Macedonia: 0.1% of adults aged 15-49, 39.6% of health spendingMali: 0.8% of adults aged 15-49, 47.2% of health spendingMalta: 0.3% of adults aged 15-49, 30.9% of health spendingMyanmar: 0.9% of adults aged 15-49, 71.1% of health spendingMontenegro: 0.1% of adults aged 15-49, 26.3% of health spendingMongolia: 0.1% of adults aged 15-49, 48.8% of health spendingMozambique: 11.5% of adults aged 15-49, 10.4% of health spendingMauritania: 0.1% of adults aged 15-49, 43.8% of health spendingMalawi: 6.2% of adults aged 15-49, 12% of health spendingMalaysia: 0.3% of adults aged 15-49, 37.1% of health spendingNamibia: 9% of adults aged 15-49, 7.49% of health spendingNiger: 0.2% of adults aged 15-49, 51.5% of health spendingNigeria: 1.2% of adults aged 15-49, 71.9% of health spendingNetherlands: 0.1% of adults aged 15-49, 11.8% of health spendingNorway: 0.1% of adults aged 15-49, 13.7% of health spendingNepal: 0.1% of adults aged 15-49, 59.4% of health spendingNew Zealand: 0.1% of adults aged 15-49, 12.7% of health spendingOman: 0.1% of adults aged 15-49, 6.31% of health spendingPakistan: 0.2% of adults aged 15-49, 52.9% of health spendingPanama: 1.1% of adults aged 15-49, 40.5% of health spendingPeru: 0.4% of adults aged 15-49, 27% of health spendingPhilippines: 0.3% of adults aged 15-49, 44.4% of health spendingPapua New Guinea: 1.5% of adults aged 15-49, 8.55% of health spendingPortugal: 0.5% of adults aged 15-49, 28.2% of health spendingParaguay: 0.5% of adults aged 15-49, 36.3% of health spendingQatar: 0.1% of adults aged 15-49, 7.43% of health spendingRomania: 0.2% of adults aged 15-49, 23% of health spendingRwanda: 2% of adults aged 15-49, 4.1% of health spendingSaudi Arabia: 0.1% of adults aged 15-49, 14.1% of health spendingSudan: 0.2% of adults aged 15-49, 57.4% of health spendingSenegal: 0.3% of adults aged 15-49, 44.3% of health spendingSingapore: 0.1% of adults aged 15-49, 25.4% of health spendingSolomon Islands: 0.1% of adults aged 15-49, 3.16% of health spendingSierra Leone: 1.4% of adults aged 15-49, 54.5% of health spendingEl Salvador: 0.4% of adults aged 15-49, 32.5% of health spendingSomalia, Fed. Rep.: 0.1% of adults aged 15-49, 30.8% of health spendingSerbia: 0.1% of adults aged 15-49, 32.1% of health spendingSuriname: 1.6% of adults aged 15-49, 19.7% of health spendingSlovak Republic: 0.1% of adults aged 15-49, 20.2% of health spendingSlovenia: 0.1% of adults aged 15-49, 11.7% of health spendingSweden: 0.1% of adults aged 15-49, 13.4% of health spendingEswatini: 23.4% of adults aged 15-49, 11% of health spendingSyrian Arab Republic: 0.1% of adults aged 15-49, 72.4% of health spendingChad: 0.9% of adults aged 15-49, 51.7% of health spendingTogo: 1.6% of adults aged 15-49, 64.3% of health spendingThailand: 1% of adults aged 15-49, 9.93% of health spendingTajikistan: 0.2% of adults aged 15-49, 62.4% of health spendingTimor-Leste: 0.2% of adults aged 15-49, 6.99% of health spendingTunisia: 0.1% of adults aged 15-49, 37.9% of health spendingTuvalu: 0.4% of adults aged 15-49, 0.0446% of health spendingTanzania: 3.5% of adults aged 15-49, 27.9% of health spendingUganda: 4.9% of adults aged 15-49, 32.2% of health spendingSt. Vincent and the Grenadines: 0.8% of adults aged 15-49, 26.6% of health spendingViet Nam: 0.4% of adults aged 15-49, 39.2% of health spendingVanuatu: 0.1% of adults aged 15-49, 8.38% of health spendingSouth Africa: 17.2% of adults aged 15-49, 6.69% of health spendingZambia: 9.4% of adults aged 15-49, 10.3% of health spendingZimbabwe: 9.8% of adults aged 15-49, 10.6% of health spendingAFGARMBGDBWALSOOMNSLBSWZTUVZAF

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.2670.001148
By rank (Spearman), not adjusted-0.0440.599148
Standard (Pearson), adjusted for national income-0.3891.1e-6148
By rank (Spearman), adjusted for national income-0.2330.005148

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 148 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: -0.122 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.409 (without SLB) to -0.366 (without MOZ). 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: MOZ (+0.023).

Fragile: this link may not hold up.
  • correlation moves sharply once outliers are trimmed

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 & Pacific18+0.02
Europe & Central Asia35-0.01
Latin America & Caribbean27-0.16
Middle East, North Africa, Afghanistan & Pakistan19-0.30
Sub-Saharan Africa42-0.60

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 third50-0.43
Middle third49-0.47
Richest third49+0.31

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
Christians89-0.38
Muslims42-0.06

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
France25-0.23
Never a European colony14-0.35
Spain16-0.07
United Kingdom51-0.43

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 = -0.091 after dropping 16 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 25years. 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 = +0.104, 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 out-of-pocket health spending move with it.

Across countries (adjusted)-0.389for comparison
Within countries+0.183each country vs itself
…and vs the same year elsewhere+0.104q = 0.260 · 152 countries
Year-on-year changes+0.016q = 0.630
Read with care.
  • Almost all of this indicator's variation is between countries, not within them, so the within-country estimate rests on a small part of the data.

3,556 country-years (one country in one year), 152 countries, 2000–2024, about 23 years each on average. Share of the variation that happens within countries over time: 2% for HIV prevalence, 11% for Out-of-pocket health spending. 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

0.20−0.2-100+10years Out-of-pocket health spending trails HIV prevalence →lag -10: r = 0.137 (n = 2,189)lag -9: r = 0.132 (n = 2,340)lag -8: r = 0.124 (n = 2,487)lag -7: r = 0.120 (n = 2,639)lag -6: r = 0.123 (n = 2,787)lag -5: r = 0.125 (n = 2,935)lag -4: r = 0.113 (n = 3,083)lag -3: r = 0.106 (n = 3,236)lag -2: r = 0.100 (n = 3,390)lag -1: r = 0.101 (n = 3,540)lag +0: r = 0.104 (n = 3,556)lag +1: r = 0.104 (n = 3,559)lag +2: r = 0.100 (n = 3,559)lag +3: r = 0.093 (n = 3,557)lag +4: r = 0.082 (n = 3,555)lag +5: r = 0.069 (n = 3,549)lag +6: r = 0.055 (n = 3,548)lag +7: r = 0.041 (n = 3,547)lag +8: r = 0.028 (n = 3,546)lag +9: r = 0.015 (n = 3,545)lag +10: r = 0.001 (n = 3,544)

Same year (lag 0): +0.104. 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.

This curve peaks at the edge of the window (lag -10), so it is still drifting where the search stops. That pattern usually reflects a slow trend left over in the data, not a link with real timing. The peak value should not be read as the “true” link at the right lag.

The data


% of adults aged 15-49
% of health spending		Years
Eswatini SWZ23.4%11%2024, 2023
South Africa ZAF17.2%6.69%2024, 2023
Lesotho LSO17.1%13.2%2024, 2023
Botswana BWA15.7%4.26%2024, 2023
Mozambique MOZ11.5%10.4%2024, 2023
Zimbabwe ZWE9.8%10.6%2024, 2023
Zambia ZMB9.4%10.3%2024, 2023
Namibia NAM9%7.49%2024, 2023
Malawi MWI6.2%12%2024, 2023
Uganda UGA4.9%32.2%2024, 2023
Tanzania TZA3.5%27.9%2024, 2023
Congo, Rep. COG3.2%28%2024, 2023
Kenya KEN3%24.2%2024, 2023
Gabon GAB2.8%17.3%2024, 2023
Cameroon CMR2.5%67.7%2024, 2023

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.

Out-of-pocket health spending

Out-of-pocket expenditure (% of current health expenditure)

World Health Organization Global Health Expenditure Database · CC BY 4.0 · updated quarterly

The share of a country's health spending paid by patients themselves when they get care. Health spending as a share of GDP is already on the site and shows how much is spent. This shows who pays.

How this was computed

Data used: most recent value in 2010-2025; values come from 2022–2024. 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 Out-of-pocket health spending

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

More links with HIV prevalence or Out-of-pocket health spending