Is censorship rising in Africa, Asia, MENA?
A single aggregate 7-day shutdown-risk level per region — evidence-volume-weighted mean of the per-country forecasts. Use this for the regional headline; click through to a region for the per-country dispersion. Because it aggregates the per-country v1 forecast, it inherits the same scope: a current-regime signal, not an onset predictor.
Generated 2026-07-06 21:01 UTC · region-forecast v1 · regions API · methodology API
Regions ranked by aggregate 7-day risk
Each row is one region. The bar shows the weighted average probability (max risk over the next 7 days, evidence-weighted across the region's countries). Max and min point to the highest- and lowest-risk constituent country.
| Region | Countries | Weighted avg 7d | Max country | Min country | # ≥25% | # ≥50% |
|---|---|---|---|---|---|---|
| Africa africa | 30 | 11.5% | Egypt EG 43.4% | Ethiopia ET 3.2% | 2 | 0 |
| Asia asia | 49 | 11.1% | Pakistan PK 95.0% | Yemen YE 3.1% | 2 | 2 |
| MENA mena | 19 | 9.2% | Egypt EG 43.4% | Yemen YE 3.1% | 2 | 0 |
| World world | 148 | 8.7% | Pakistan PK 95.0% | Mexico MX 2.5% | 4 | 2 |
| Oceania oceania | 7 | 6.6% | New Zealand NZ 8.7% | Guam GU 3.5% | 0 | 0 |
| Americas americas | 23 | 5.3% | Cuba CU 12.3% | Mexico MX 2.5% | 0 | 0 |
| Europe europe | 39 | 5.2% | Ukraine UA 11.5% | Russia RU 2.9% | 0 | 0 |
Drill down by region
Constituent country probabilities for each region. The evidence weight column shows how much each country contributes to its region's weighted average — a country with weight 1000 dominates more than one with weight 1.
Africa africa
30 countries · 2 ≥25% · 0 ≥50%
| Country | Day 0 | Avg 7d | Max 7d | Weight | 7d bar |
|---|---|---|---|---|---|
| Egypt EG | 38.4% | 41.6% | 43.4% | 1712 | |
| Sudan SD | 27.3% | 27.4% | 29.9% | 44 | |
| Ghana GH | 3.2% | 5.1% | 8.4% | 6 | |
| Rwanda RW | 4.4% | 6.2% | 8.3% | 9 | |
| Angola AO | 5.4% | 6.2% | 8.2% | 6 | |
| Gabon GA | 3.1% | 5.4% | 8.2% | 6 | |
| Tunisia TN | 3.5% | 5.6% | 8.2% | 344 | |
| Zambia ZM | 5.6% | 5.7% | 8.2% | 2 | |
| Zimbabwe ZW | 1.9% | 5.1% | 8.1% | 4 | |
| DR Congo CD | 3.6% | 5.9% | 8.0% | 274 | |
| Senegal SN | 5.7% | 6.4% | 8.0% | 3 | |
| Congo CG | 5.5% | 5.8% | 7.9% | 1 | |
| Madagascar MG | 2.6% | 5.4% | 7.9% | 1 | |
| Mozambique MZ | 3.0% | 5.3% | 7.8% | 2 | |
| Burkina Faso BF | 4.3% | 5.9% | 7.6% | 1 | |
| Cameroon CM | 2.4% | 5.5% | 7.5% | 790 | |
| Uganda UG | 3.6% | 4.8% | 6.8% | 788 | |
| Botswana BW | 4.0% | 5.2% | 6.6% | 3 | |
| Tanzania TZ | 1.7% | 3.3% | 5.9% | 785 | |
| Kenya KE | 2.4% | 3.2% | 5.5% | 156 | |
| South Africa ZA | 1.0% | 2.7% | 5.1% | 828 | |
| Ivory Coast CI | 2.1% | 3.2% | 5.0% | 59 | |
| Libya LY | 1.0% | 2.0% | 5.0% | 1044 | |
| Algeria DZ | 1.7% | 3.0% | 4.9% | 1034 | |
| Eritrea ER | 1.0% | 2.0% | 4.9% | 1 | |
| Mali ML | 1.0% | 3.0% | 4.9% | 2 | |
| Morocco MA | 1.5% | 2.8% | 4.4% | 1404 | |
| Niger NE | 1.0% | 2.2% | 3.6% | 1 | |
| Nigeria NG | 3.1% | 2.8% | 3.5% | 46 | |
| Ethiopia ET | 1.0% | 2.0% | 3.2% | 1359 |
Asia asia
49 countries · 2 ≥25% · 2 ≥50%
| Country | Day 0 | Avg 7d | Max 7d | Weight | 7d bar |
|---|---|---|---|---|---|
| Pakistan PK | 95.0% | 95.0% | 95.0% | 2088 | |
| Uzbekistan UZ | 84.8% | 84.9% | 87.0% | 1044 | |
| Qatar QA | 8.8% | 10.0% | 12.1% | 493 | |
| Jordan JO | 6.6% | 8.3% | 11.3% | 1230 | |
| Kuwait KW | 6.6% | 7.5% | 9.8% | 164 | |
| Georgia GE | 6.7% | 7.6% | 8.8% | 156 | |
| Kyrgyzstan KG | 4.1% | 5.8% | 8.6% | 2 | |
| Mongolia MN | 2.2% | 5.8% | 8.4% | 2 | |
| Cambodia KH | 3.1% | 5.6% | 8.2% | 974 | |
| Singapore SG | 3.7% | 5.2% | 8.2% | 929 | |
| Brunei BN | 3.5% | 4.9% | 8.1% | 1 | |
| Palestine PS | 4.5% | 4.8% | 8.0% | 1 | |
| Sri Lanka LK | 4.5% | 5.2% | 7.8% | 217 | |
| Bhutan BT | 3.6% | 5.5% | 7.6% | 1 | |
| Bahrain BH | 3.1% | 4.9% | 7.5% | 218 | |
| Maldives MV | 3.0% | 5.5% | 7.4% | 1 | |
| Laos LA | 4.9% | 5.2% | 7.3% | 6 | |
| Afghanistan AF | 3.3% | 6.0% | 7.0% | 10 | |
| Cyprus CY | 2.9% | 5.4% | 7.0% | 3 | |
| Tajikistan TJ | 5.7% | 5.3% | 6.6% | 2 | |
| Nepal NP | 1.0% | 2.5% | 6.1% | 66 | |
| United Arab Emirates AE | 1.0% | 3.4% | 5.9% | 1839 | |
| South Korea KR | 1.6% | 2.3% | 5.9% | 1088 | |
| Kazakhstan KZ | 1.0% | 2.6% | 5.9% | 1504 | |
| Myanmar MM | 1.0% | 2.6% | 5.8% | 1752 | |
| Lebanon LB | 1.8% | 3.2% | 5.2% | 151 | |
| Azerbaijan AZ | 2.4% | 2.9% | 5.1% | 957 | |
| Taiwan TW | 2.3% | 3.1% | 5.1% | 171 | |
| Armenia AM | 2.6% | 3.0% | 4.9% | 144 | |
| Syria SY | 1.0% | 2.4% | 4.9% | 862 |
MENA mena
19 countries · 2 ≥25% · 0 ≥50%
| Country | Day 0 | Avg 7d | Max 7d | Weight | 7d bar |
|---|---|---|---|---|---|
| Egypt EG | 38.4% | 41.6% | 43.4% | 1712 | |
| Sudan SD | 27.3% | 27.4% | 29.9% | 44 | |
| Qatar QA | 8.8% | 10.0% | 12.1% | 493 | |
| Jordan JO | 6.6% | 8.3% | 11.3% | 1230 | |
| Kuwait KW | 6.6% | 7.5% | 9.8% | 164 | |
| Tunisia TN | 3.5% | 5.6% | 8.2% | 344 | |
| Palestine PS | 4.5% | 4.8% | 8.0% | 1 | |
| Bahrain BH | 2.5% | 5.7% | 7.5% | 218 | |
| Oman OM | 1.0% | 2.9% | 5.5% | 648 | |
| Lebanon LB | 1.8% | 3.2% | 5.2% | 151 | |
| Algeria DZ | 1.7% | 3.0% | 4.9% | 1034 | |
| Libya LY | 1.0% | 2.6% | 4.9% | 1044 | |
| Syria SY | 1.0% | 2.4% | 4.9% | 862 | |
| Turkey TR | 1.0% | 2.0% | 4.8% | 2843 | |
| Iraq IQ | 1.0% | 2.3% | 4.2% | 1530 | |
| Morocco MA | 1.0% | 2.2% | 4.2% | 1404 | |
| United Arab Emirates AE | 1.0% | 2.2% | 4.0% | 1839 | |
| Saudi Arabia SA | 1.0% | 1.9% | 3.9% | 1802 | |
| Yemen YE | 1.0% | 2.0% | 3.1% | 712 |
World world
148 countries · 4 ≥25% · 2 ≥50%
| Country | Day 0 | Avg 7d | Max 7d | Weight | 7d bar |
|---|---|---|---|---|---|
| per-country detail unavailable | |||||
Oceania oceania
7 countries · 0 ≥25% · 0 ≥50%
| Country | Day 0 | Avg 7d | Max 7d | Weight | 7d bar |
|---|---|---|---|---|---|
| New Zealand NZ | 4.6% | 5.8% | 8.1% | 651 | |
| Fiji FJ | 5.4% | 6.0% | 7.7% | 1 | |
| Papua New Guinea PG | 4.9% | 6.2% | 7.7% | 1 | |
| Australia AU | 1.0% | 3.4% | 5.9% | 863 | |
| Tonga TO | 2.1% | 2.9% | 5.5% | 1 | |
| Samoa WS | 1.0% | 2.9% | 4.9% | 1 | |
| Guam GU | 1.0% | 2.5% | 3.5% | 2 |
Americas americas
23 countries · 0 ≥25% · 0 ≥50%
| Country | Day 0 | Avg 7d | Max 7d | Weight | 7d bar |
|---|---|---|---|---|---|
| Cuba CU | 3.0% | 6.9% | 12.2% | 195 | |
| Colombia CO | 5.3% | 7.6% | 10.6% | 988 | |
| Argentina AR | 7.2% | 8.0% | 10.1% | 828 | |
| Jamaica JM | 3.5% | 5.6% | 8.6% | 16 | |
| Bolivia BO | 4.4% | 6.5% | 8.3% | 4 | |
| Uruguay UY | 5.0% | 5.8% | 7.8% | 15 | |
| Costa Rica CR | 3.3% | 6.1% | 7.6% | 7 | |
| Honduras HN | 5.3% | 5.6% | 7.4% | 129 | |
| Puerto Rico PR | 2.2% | 5.3% | 7.2% | 1 | |
| Haiti HT | 2.8% | 5.5% | 6.9% | 1 | |
| Guatemala GT | 5.1% | 5.2% | 6.7% | 1 | |
| Panama PA | 5.2% | 5.6% | 6.7% | 4 | |
| Paraguay PY | 1.0% | 2.9% | 6.2% | 9 | |
| Ecuador EC | 1.0% | 3.1% | 5.5% | 20 | |
| Mexico MX | 1.0% | 2.7% | 5.1% | 1054 | |
| Chile CL | 1.0% | 2.7% | 5.0% | 718 | |
| United States US | 1.8% | 2.7% | 4.6% | 1046 | |
| Dominican Republic DO | 1.7% | 2.9% | 4.5% | 14 | |
| Nicaragua NI | 1.0% | 2.4% | 4.5% | 23 | |
| Peru PE | 1.5% | 2.7% | 4.3% | 64 | |
| Canada CA | 1.3% | 2.1% | 4.1% | 1008 | |
| Brazil BR | 2.3% | 2.8% | 4.0% | 1044 | |
| Venezuela VE | 1.0% | 2.5% | 3.8% | 2471 |
Europe europe
39 countries · 0 ≥25% · 0 ≥50%
| Country | Day 0 | Avg 7d | Max 7d | Weight | 7d bar |
|---|---|---|---|---|---|
| Ukraine UA | 7.2% | 8.2% | 11.5% | 214 | |
| Bulgaria BG | 4.7% | 7.9% | 9.5% | 140 | |
| Belgium BE | 5.7% | 6.0% | 8.8% | 679 | |
| Montenegro ME | 3.7% | 5.7% | 8.8% | 1 | |
| Slovenia SI | 2.2% | 5.3% | 8.8% | 15 | |
| Lithuania LT | 3.2% | 5.7% | 8.7% | 9 | |
| Latvia LV | 4.7% | 5.8% | 8.6% | 1 | |
| Luxembourg LU | 3.5% | 6.2% | 8.4% | 2 | |
| Ireland IE | 4.4% | 6.1% | 8.3% | 657 | |
| Finland FI | 3.3% | 5.4% | 8.2% | 690 | |
| Switzerland CH | 3.4% | 5.2% | 8.1% | 648 | |
| Norway NO | 2.6% | 5.0% | 8.1% | 662 | |
| Sweden SE | 4.7% | 5.7% | 8.1% | 789 | |
| Denmark DK | 1.9% | 5.2% | 8.0% | 628 | |
| Iceland IS | 3.3% | 5.7% | 8.0% | 2 | |
| North Macedonia MK | 4.1% | 5.6% | 7.8% | 157 | |
| Croatia HR | 3.8% | 5.3% | 7.7% | 8 | |
| Moldova MD | 5.3% | 5.6% | 7.6% | 8 | |
| Slovakia SK | 5.6% | 5.8% | 7.6% | 9 | |
| Austria AT | 3.9% | 5.4% | 7.4% | 653 | |
| Hungary HU | 4.5% | 5.6% | 7.4% | 42 | |
| Estonia EE | 2.8% | 5.4% | 7.3% | 3 | |
| Monaco MC | 5.3% | 5.6% | 7.3% | 1 | |
| Czech Republic CZ | 4.8% | 5.4% | 7.2% | 677 | |
| Netherlands NL | 2.3% | 5.4% | 6.8% | 970 | |
| Romania RO | 2.3% | 5.1% | 6.5% | 855 | |
| Albania AL | 2.8% | 5.1% | 6.2% | 2 | |
| Portugal PT | 1.0% | 2.5% | 6.0% | 803 | |
| Poland PL | 1.0% | 2.1% | 5.9% | 1038 | |
| Serbia RS | 1.5% | 3.0% | 5.6% | 146 |
Methodology
Aggregation: Route A (cheap). For each region we pull the existing per-country /v1/forecast/{cc}/7day output for every constituent country and take an evidence-volume-weighted mean of the per-country max risk over the next 7 days. Weights are the number of evidence rows the country has produced in the last 30 days (floored at 1.0 so quiet countries still contribute). The headline number is weighted_avg_probability_7d.
Why evidence weighting, not population? A country's probability of a shutdown isn't a per-capita quantity — it's a yes/no event for that country's network. We don't ship a population table on the forecasting server, and using population as the weight would let India and China dominate every Asian average. Weighting by evidence volume puts more confidence on countries we actually have measurements for, which is the right epistemic move when aggregating model output.
Single high-risk countries pull averages up. If MENA looks 12% but Sudan is 80%, the region number obscures that. Always check the per-country drill-down above before citing a region figure — the “# ≥50%” column tells you how many countries are doing the lifting.
Region definitions. Continents follow UN M.49 geographic groupings (Africa / Americas / Asia / Europe / Oceania). MENA is a custom grouping — UN doesn't define MENA — composed of Northern Africa (DZ, EG, LY, MA, SD, TN) plus Western Asia, minus IL, CY, AM, GE, AZ which journalists typically don't count as MENA. World is every country in the country_geography table.
Route B (per-region model) — not shipped yet. A dedicated XGBoost on region-level features (sum of evidence, count of countries in elevated risk, etc.) would be more accurate than aggregating per-country probabilities, but it needs its own label assembly and a temporal holdout before it can replace Route A. We expect to ship it after the first month of journalist feedback on which regions get most-cited.
Calibration limits. The underlying per-country forecast model is isotonic-recalibrated only for the 30 watched censorship-heavy countries (see /atlas/forecast). Countries outside that set get raw uncalibrated probabilities, so the world and oceania averages should be read as relative rankings, not absolute calibrated figures.
Which countries are in each region?
The full mapping queried live from country_geography.
Africa (30 countries)
Americas (23 countries)
Asia (49 countries)
Europe (39 countries)
Mena (19 countries)
Oceania (7 countries)
API
Supported slugs: africa, americas, asia, europe, mena, oceania, world. Each region response includes a honest_caveats array.