Trend · rank 13 of 250

Social protection coverage gaps

Changing employment patterns and household risks are outgrowing social protection systems in many countries, so that the costs of shocks fall directly on households, deepen poverty and weaken public consent for government.

Governance & IntegrityState capacity & governanceinequalityinstitutionsresilience

Second pass: Carried forward from the first pass, where it was Weak social protection. Held by all three panel models.

Sensitivity and network position

Rank
13of 250
Sensitivity
29.2rank 3
Breadth
4of 20 scenarios High or above
PageRank
64.3rank 15
Eigenvector
62.3
Betweenness
32.8
Links
19trends at Moderate similarity or above
Composite
54.3

Attention over three years

How much this trend is read about on Wikipedia and searched for on Google, week by week, set against the typical trend in the list so that what moves every trend at once is taken out. 100 is this trend's own three-year average. The score measures public attention, which is not the same as the strength of the force: a trend can deepen unnoticed, and a news event can lift attention for a fortnight.

Now
78
Over a year
−2%Steady
Over three years
−38%
Peak
15129 Dec 2024
Sources
Bothagreement 0.66
Coverage
16languages · 25 nations

Trailing 4-week average. 100 is this trend’s three-year average.

By language

Wikipedia reading in each language edition where the trend’s pages are read enough to measure (16 of 28). Share is of all the readers counted.

LanguageShareNowOver a yearThree years
English41%87−6%
Spanish11%78−8%
Japanese8%73−24%
Russian8%85−2%
German7%85−5%
French6%90−9%
Chinese4%105−4%
Italian4%88+9%
Polish2%80−21%
Arabic2%110+34%
Korean2%58−34%
Persian1%86+23%
Turkish1%112−2%
Bengali1%91+26%
Hebrew1%112+25%
Ukrainian1%56−13%

By country

Google search interest over the three years, as a share of each country’s searching. 100 is the nation where interest is highest. The search terms are English, which favours countries that search in English.

United States

Ireland

Philippines

Portugal

South Africa

Nigeria

Pakistan

South Korea

Belgium

Canada

United Kingdom

India

100

13

9

8

8

7

7

7

6

6

6

5

The 12 highest of 25 nations with a reading.

By region and G20 member

Attention to this trend inside each place, from Google searches made in its countries and Wikipedia reading in the languages mostly read there, averaged where both exist. Each line compares the trend with its own past in that place; the lines do not compare places.

Regions

PlaceRead fromNow90 days1 year3 yearsThree years
North AmericaGoogle in 2 countries + Wikipedia in English88+17%−1%−21%
EuropeGoogle in 8 countries + Wikipedia in German, French, Italian, Polish86−5%−6%−20%
Indo-PacificGoogle in 11 countries + Wikipedia in Japanese, Chinese, Korean99+6%−0%+1%
South AsiaGoogle in 4 countries + Wikipedia in Bengali91−29%+6%−1%
Gulf and Middle EastGoogle in 2 countries + Wikipedia in Persian, Arabic, Turkish, Hebrew114+2%+19%−4%
AfricaGoogle in 5 countries125+11%+74%+8%
Latin America and CaribbeanGoogle in 6 countries + Wikipedia in Spanish99−3%+13%−12%
Russia and EurasiaGoogle in 2 countries + Wikipedia in Russian, Ukrainian76−2%−19%−37%

G20 members

PlaceRead fromNow90 days1 year3 yearsThree years
ArgentinaGoogle89−36%+18%−15%
AustraliaGoogle91−3%−2%+1%
BrazilGoogle91−8%−13%−11%
CanadaGoogle88−20%−9%−0%
FranceGoogle + Wikipedia in French84+5%−16%−17%
GermanyGoogle + Wikipedia in German74−8%−23%−36%
IndiaGoogle + Wikipedia in Bengali91−27%+10%−3%
IndonesiaGoogle58−26%−28%−59%
ItalyGoogle + Wikipedia in Italian79−3%+0%−42%
JapanGoogle + Wikipedia in Japanese85+41%−18%−19%
South KoreaGoogle + Wikipedia in Korean66−1%−41%−30%
MexicoGoogle222+60%+132%+125%
RussiaWikipedia in Russian85+1%−2%−34%
South AfricaGoogle314+42%+618%+360%
TürkiyeGoogle + Wikipedia in Turkish124+13%+16%+31%
United KingdomGoogle108+7%+10%+10%
United StatesGoogle + Wikipedia in English88+32%+2%−24%

Relation to each scenario

A trend relates to a scenario when it changes how likely the scenario is, how hard it lands, or is itself sharply changed by it. Each score is the median of three scores given separately by the members of the model panel.

RelationScenarioFamily
5 · Very highAn AI deployment step causes abrupt labour displacement S08Technology and infrastructure
4 · HighA global funding seizure reaches sovereign balance sheets S02Economic and trade
4 · HighTwo breadbasket failures trigger a food availability crisis S06Energy, climate and resources
4 · HighA major disaster disables the national economic core S07Energy, climate and resources
3 · ModerateA novel respiratory pathogen exceeds health surge capacity S10Health
3 · ModerateAffordable preventive treatments reduce chronic illness S19 ↗Health
2 · LowA disputed transfer of power breaks effective government S05Geopolitical and security
2 · LowA creditor agreement releases fiscal capacity S11 ↗Economic and trade
2 · LowA validated farming package raises water-efficient output S16 ↗Energy, climate and resources
2 · LowA public service platform reaches inclusive operation S18 ↗Technology and infrastructure
1 · Very lowCritical trade divides into rival blocs S01Economic and trade
1 · Very lowA regional war closes a globally important sea route S03Geopolitical and security
1 · Very lowHybrid coercion ends in an infrastructure blackout S04Geopolitical and security
1 · Very lowA verified Middle East settlement restores access S14 ↗Geopolitical and security
0 · Not relatedA cryptographic breakthrough invalidates digital trust S09Technology and infrastructure
0 · Not relatedA cross-regional market access compact redirects investment S12 ↗Economic and trade
0 · Not relatedA great-power agreement lowers economic security barriers S13 ↗Geopolitical and security
0 · Not relatedCheap firm clean power becomes available at scale S15 ↗Energy, climate and resources
0 · Not relatedAI-directed research produces a reproducible discovery step S17 ↗Technology and infrastructure
0 · Not relatedA live outbreak proves rapid distributed pandemic defence S20 ↗Health

Similarity = 0.3 × shared tags (Jaccard) + 0.3 × likeness of scenario profiles (cosine) + 0.3 × likeness of names and descriptions (TF-IDF cosine) + 0.1 if in the same capability domain, cut into seven levels at 0.12, 0.22, 0.33, 0.45, 0.58, 0.72. Shown at Moderate and above.

SimilarityTrendThemeRank
4 · HighState capacity & deliveryState capacity & governance1
4 · HighPublic procurement capabilityState capacity & governance6
4 · HighLocal & city government capacityState capacity & governance11
4 · HighCivil unrest & protest mobilisationState capacity & governance25
4 · HighOutsourcing & public-private deliveryState capacity & governance27
3 · ModerateCivil service capability & payState capacity & governance2
3 · ModerateRule of law & judicial independenceState capacity & governance3
3 · ModerateExecutive overreach & emergency powersState capacity & governance4
3 · ModerateCorruption & state captureState capacity & governance5
3 · ModerateRegulatory capture & lobbying powerState capacity & governance8
3 · ModerateEntrenched opportunity inequalityPeople, health & work9
3 · ModeratePublic communication in crisisInformation & trust10
3 · ModerateErosion of rights & civic freedomsState capacity & governance14
3 · ModeratePolarisation & populismState capacity & governance15
3 · ModerateFiscal rules & budget credibilityState capacity & governance17
3 · ModerateOfficial statistics & data capacityState capacity & governance21
3 · ModerateCentral bank independence under pressureState capacity & governance64
3 · ModerateInformal employment persistencePeople, health & work84
3 · ModerateAlgorithmic accountability & biasState capacity & governance135