voidly
Atlas · 7-day per-region forecast

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 2026-05-22 19:12 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.

RegionCountriesWeighted avg 7dMax countryMin country# ≥25%# ≥50%
Americas
americas
23
40.4%
Venezuela VE
78.9%
United States US
2.6%
22
Asia
asia
49
31.1%
Pakistan PK
95.0%
Myanmar MM
2.6%
1010
World
world
148
28.2%
Pakistan PK
95.0%
Myanmar MM
2.6%
1916
MENA
mena
19
26.9%
Sudan SD
79.1%
Morocco MA
3.9%
54
Africa
africa
30
25.9%
Sudan SD
79.1%
Eritrea ER
3.7%
63
Europe
europe
39
12.3%
Belarus BY
61.0%
Russia RU
3.8%
11
Oceania
oceania
7
5.2%
Fiji FJ
7.9%
Tonga TO
4.9%
00
Legend:<10% Low10-25% Watch25-50% Elevated≥50% High

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.

Americas americas

23 countries · 2 ≥25% · 2 ≥50%

Elevated
40.4%
weighted avg 7d
CountryDay 0Avg 7dMax 7dWeight7d bar
Venezuela VE74.5%76.9%78.9%1745
Nicaragua NI49.5%51.6%54.3%181
Peru PE9.1%11.8%14.2%38
Colombia CO5.2%9.5%12.9%166
Panama PA8.6%9.1%11.7%122
Ecuador EC3.6%4.9%8.0%19
Dominican Republic DO4.4%5.2%7.6%26
Haiti HT2.0%5.2%7.1%1
Uruguay UY3.6%5.1%7.1%5
Costa Rica CR1.7%4.5%6.8%9
Jamaica JM2.4%4.2%6.8%6
Honduras HN2.5%4.8%6.6%213
Paraguay PY4.4%4.7%6.6%35
Bolivia BO4.1%4.9%6.3%14
Guatemala GT4.9%4.3%6.2%7
Argentina AR1.0%3.6%5.9%174
Chile CL1.4%4.5%5.8%90
United States US1.0%2.7%5.7%266
Cuba CU2.9%3.8%5.6%242
Canada CA2.0%2.4%4.3%186
Mexico MX1.0%2.9%4.2%210
Brazil BR1.0%2.3%4.1%210
Puerto Rico PR1.0%2.6%3.9%1

Asia asia

49 countries · 10 ≥25% · 10 ≥50%

Elevated
31.1%
weighted avg 7d
CountryDay 0Avg 7dMax 7dWeight7d bar
Pakistan PK95.0%95.0%95.0%932
Uzbekistan UZ95.0%95.0%95.0%257
Thailand TH73.3%76.8%79.8%674
India IN76.5%76.9%79.4%1159
Saudi Arabia SA76.7%76.8%79.0%517
Turkmenistan TM74.0%76.5%78.5%9
Turkey TR60.8%64.7%70.3%1036
Kazakhstan KZ56.3%60.2%63.5%879
Syria SY58.7%60.6%63.4%237
Malaysia MY58.1%59.7%62.2%670
Cyprus CY18.2%15.3%24.5%2
Laos LA6.5%8.6%11.6%14
Iran IR4.4%7.6%10.5%740
Afghanistan AF3.2%6.1%9.6%18
Kuwait KW6.0%6.5%9.1%57
Bahrain BH5.3%6.6%8.6%137
China CN2.3%4.7%8.4%1489
Cambodia KH3.2%5.8%8.0%310
Mongolia MN2.6%5.1%7.8%3
Sri Lanka LK3.3%5.9%7.7%6
Maldives MV3.7%4.5%7.7%3
Tajikistan TJ4.9%4.3%7.4%4
Israel IL3.7%5.5%7.3%95
Azerbaijan AZ2.9%4.4%6.9%242
Lebanon LB2.0%3.7%6.6%185
Nepal NP4.5%4.8%6.6%106
Palestine PS1.7%4.8%6.6%5
Bhutan BT4.6%4.7%6.4%3
Vietnam VN1.0%3.3%6.3%807
Brunei BN2.2%4.4%6.2%2

World world

148 countries · 19 ≥25% · 16 ≥50%

Elevated
28.2%
weighted avg 7d
CountryDay 0Avg 7dMax 7dWeight7d bar
per-country detail unavailable

MENA mena

19 countries · 5 ≥25% · 4 ≥50%

Elevated
26.9%
weighted avg 7d
CountryDay 0Avg 7dMax 7dWeight7d bar
Sudan SD73.6%76.7%79.1%5
Saudi Arabia SA76.7%76.8%79.0%517
Turkey TR60.8%64.7%70.3%1036
Syria SY58.7%60.6%63.4%237
Egypt EG42.2%45.4%48.2%731
Tunisia TN3.7%6.0%9.2%106
Kuwait KW6.0%6.5%9.1%57
Bahrain BH5.3%6.6%8.6%137
Lebanon LB2.0%3.7%6.6%185
Libya LY3.2%4.1%6.6%269
Palestine PS1.7%4.8%6.6%5
Oman OM1.4%3.1%5.4%198
United Arab Emirates AE1.0%2.6%5.1%747
Yemen YE1.0%2.0%4.8%213
Qatar QA1.0%2.4%4.7%274
Algeria DZ1.0%1.9%4.6%559
Iraq IQ1.0%2.3%4.6%837
Jordan JO2.1%2.0%4.4%265
Morocco MA1.0%1.7%3.9%569

Africa africa

30 countries · 6 ≥25% · 3 ≥50%

Elevated
25.9%
weighted avg 7d
CountryDay 0Avg 7dMax 7dWeight7d bar
Sudan SD73.6%76.7%79.1%5
Ethiopia ET62.7%64.2%67.6%434
Nigeria NG56.3%59.0%60.9%142
Egypt EG42.2%45.4%48.2%731
Uganda UG40.1%43.0%44.9%10
Zimbabwe ZW27.9%31.1%34.4%70
Ivory Coast CI6.9%8.7%10.7%15
Cameroon CM6.4%8.6%10.6%26
Tunisia TN3.7%6.0%9.2%106
Ghana GH3.5%5.9%8.9%31
Botswana BW1.5%5.1%7.9%7
Burkina Faso BF5.1%5.4%7.8%5
Mali ML4.7%5.1%7.8%1
Mozambique MZ4.6%5.3%7.7%18
DR Congo CD4.4%4.9%7.5%11
Congo CG3.0%4.7%7.5%14
Rwanda RW3.5%5.3%7.5%4
Tanzania TZ1.3%4.3%7.2%33
Angola AO2.4%4.7%7.0%19
Niger NE2.6%5.2%7.0%2
Gabon GA1.4%4.4%6.6%8
Madagascar MG4.4%4.8%6.6%1
Zambia ZM3.2%4.7%6.3%8
Libya LY1.7%3.0%6.2%269
Kenya KE1.5%2.4%5.1%160
Algeria DZ1.0%1.9%4.6%559
Senegal SN1.0%2.2%4.1%1
Morocco MA1.0%1.7%3.9%569
South Africa ZA1.0%2.2%3.9%158
Eritrea ER1.0%2.5%3.7%1

Europe europe

39 countries · 1 ≥25% · 1 ≥50%

Watch
12.3%
weighted avg 7d
CountryDay 0Avg 7dMax 7dWeight7d bar
Belarus BY56.9%59.2%61.0%646
Netherlands NL5.3%8.6%11.4%109
Ukraine UA5.9%8.8%11.2%316
Switzerland CH7.0%7.6%10.4%23
Ireland IE3.7%5.0%8.6%22
Estonia EE3.6%5.4%8.5%7
Czech Republic CZ2.8%5.3%8.4%14
Bosnia and Herzegovina BA2.6%5.7%8.3%40
Croatia HR2.2%5.2%8.3%18
Hungary HU1.6%4.4%8.3%41
Luxembourg LU2.5%5.2%8.2%1
North Macedonia MK3.0%4.9%8.1%20
France FR3.7%4.6%7.9%367
Monaco MC1.6%5.1%7.6%1
Moldova MD1.3%4.7%7.6%80
Slovenia SI5.0%4.9%7.6%121
Iceland IS4.7%5.6%7.4%4
Latvia LV3.3%5.1%7.4%6
Finland FI2.8%4.2%7.2%16
Albania AL3.7%5.1%7.1%10
Austria AT2.0%4.5%7.1%9
Montenegro ME4.9%5.0%7.1%12
Slovakia SK3.3%4.9%7.1%9
Norway NO2.9%4.6%7.0%17
Serbia RS3.0%4.2%7.0%152
Sweden SE4.9%5.0%6.8%27
Denmark DK5.0%5.2%6.6%3
Belgium BE4.5%5.2%6.5%3
Bulgaria BG3.3%5.1%6.5%123
Lithuania LT1.2%4.3%6.5%32

Oceania oceania

7 countries · 0 ≥25% · 0 ≥50%

Low
5.2%
weighted avg 7d
CountryDay 0Avg 7dMax 7dWeight7d bar
Fiji FJ2.1%4.8%7.9%2
Guam GU5.0%5.5%7.5%1
Samoa WS4.1%5.3%6.2%6
New Zealand NZ2.8%4.7%6.1%16
Papua New Guinea PG4.6%4.8%5.7%2
Australia AU1.0%2.2%5.0%170
Tonga TO1.0%1.8%4.9%1

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

# Aggregate forecast for a region
GET https://api.voidly.ai/v1/forecast/region/mena
# All regions in one response
GET https://api.voidly.ai/v1/forecast/regions
# Methodology + region membership
GET https://api.voidly.ai/v1/forecast/regions/info

Supported slugs: africa, americas, asia, europe, mena, oceania, world. Each region response includes a honest_caveats array.

See also