Evacuation Inform Index β€” EII

A composite "risk of evacuating vs. risk of staying" model Β· live data: INFORM Severity Index, April 2026 (ACAPS / EU JRC) Β· 104 active crises

πŸ“Œ Pin a conflict to model or click a circle on the map below ↓
Real data. RSS = INFORM Conditions of people affected; RSE = INFORM Complexity (access, safety, operating environment), each rescaled 1β†’5. Bubble size scales with the metric. Click a marker for the full breakdown.

Methodology

The Evacuation Inform Index (EII) is structured as a ratio β€” the Risk Score for Evacuating (RSE) divided by the Risk Score for Staying (RSS) β€” synthesising the INFORM Severity 3-dimension structure with the IOM RICD macro/micro split.

EII = RSE / RSSEII > 1.0 β†’ evacuation is riskier than staying  |  EII < 1.0 β†’ staying is riskier than evacuating
Live data grounding. The map is populated with the real INFORM Severity Index, April 2026 (ACAPS / EU JRC, 104 active crises, via HDX). Each crisis's Conditions of people affected sub-score drives RSS (how severe it is to remain) and its Complexity sub-score β€” access constraints, society & safety, operating environment β€” drives RSE (how hard/dangerous it is to move). Both are rescaled from INFORM's 1–10 to the 1–5 EII scale. Layers 2–3 (route availability, personal modifiers) below are the design roadmap; the current build uses INFORM as the live backbone.
Design note. Pure ratios destabilise as the denominator nears zero. A floor of RSS = 0.5 (on a 5-point scale) is applied, and the EII is always shown alongside both component scores β€” never as the sole output.

Three-layer architecture

LayerFunctionPrecedent
Layer 1 β€” Objective Risk Score (ORS)
50%		Universal factors, identical for everyone in the geography (hostilities, conflict risk, natural-hazard life risk)INFORM Severity, ACLED, GCRI
Layer 2 β€” Infrastructure & Access (IAS)
35%		Availability of evacuation routes, resources & connectivityACAPS Humanitarian Access, IDMC
Layer 3 β€” Personal Vulnerability Modifier (PVM)
15%		Demographic / household factors applied as a multiplicative modifier (0.7×–1.3Γ—)CDC SVI, IOM RICD micro-level

Aggregation β€” weighted geometric mean

Indicators aggregate by weighted geometric mean rather than arithmetic mean, so an extreme imbalance (e.g. all infrastructure unavailable) cannot be compensated by a low score elsewhere β€” the same logic used by the Human Development Index and INFORM Risk.

Score = V₁w₁ Γ— Vβ‚‚wβ‚‚ Γ— … Γ— Vβ‚™wβ‚™Vα΅’ = normalised 1–5 score Β· wα΅’ = weight (Ξ£w = 1.0)

Recommended build sequence

PhaseMethodPurpose
1 Β· Variable designDelphi + Budget Allocation (8–12 experts, 2 rounds)Set initial layer & sub-variable weights
2 Β· Weight validationFuzzy AHP (triangular numbers, Buckley's geometric mean)Validate contested weights under uncertainty
3 Β· CalibrationHistorical case testing (Sudan '23, Ukraine '22, Kabul '21, Lebanon '06, Haiti '10) + PCACheck the index matches real decisions; prune redundant variables

Constraint layers (not scored)

Financial feasibility filter β€” a second-stage check on whether the recommended action is affordable (transport, accommodation, asset-liquidation loss, income disruption). Legal / rights (UDHR Art. 13) β€” flags exit-visa requirements, travel bans or closure orders that restrict self-evacuation.

Variables & Proposed Weights

Preliminary weights synthesised from INFORM, ACLED and FSI logic β€” to be validated by AHP expert surveys.

Layer 1 β€” Objective Risk Score Β· 50%

VariableData sourceWeightRationale
Active hostilitiesACLED: fatalities, attack types, proximity20%Immediate life threat; fastest-changing β†’ heaviest weight
Likelihood of future hostilityGCRI risk score; FSI security; ICEWS15%Forward-looking; less certain than observed events
Life risk (non-conflict)IDMC, FEWS NET β€” flood, quake, fire15%Natural-hazard exposure alongside conflict

Layer 2 β€” Infrastructure & Access Β· 35%

VariableData sourceWeightRationale
Evacuation route availabilityFlight seats, road/border status, satellite imagery12%No route = evacuation impossible
Infrastructure availability (stay)Internet, energy, food, water (IPC, FEWS NET)10%Determines survivability if staying
Security / threat alertsOSAC, embassy alerts, local-language news8%Near-real-time signal, both directions
WeatherNOAA, Copernicus5%Modifier on route viability & shelter

Layer 3 β€” Personal Vulnerability Modifier Β· 15% (multiplicative 0.7×–1.3Γ—)

VariableOperationalisationDirection of effect
Young children (<12)CDC SVI "age ≀17"; self-report↑ RSE (harder to move) & ↑ RSS (more vulnerable)
Elderly (65+)CDC SVI "age 65+"; self-report↑ RSE (mobility) & ↑ RSS (medical risk)
Gender / gendered riskUNHCR GBV risk indicators↑ RSS in conflict zones with GBV risk
Prior evacuation experienceSelf-assessed preparedness↓ RSE (more capable evacuee)
Financial resourcesSelf-reported↓ RSE when high; ↑ RSS when low

Weighting methods considered

MethodSubjectivityDataDefensibilityUse
Equal weightsNoneNoneLowBaseline & sensitivity
Budget allocation (BAP)HighNoneMediumRapid prototyping
AHPMediumExpert surveyHighPublished index
Fuzzy AHPLow–MedExpert surveyVery highAmbiguous variables
PCA / factor analysisNoneHistoricalMediumValidation & pruning

Data Sources

Feeds that populate the index. All free unless noted.

Reference Indices & Key Papers

Methodological precedents

INFORM Severity Index

ACAPS / EU JRC Β· monthly

3 weighted dimensions (Impact 20% Β· Conditions 50% Β· Complexity 30%), 1–5 scale. Closest analogue.

acaps.org β†’

ACLED Conflict Index

ACLED Β· weekly

Deadliness 35 Β· Danger to civilians 25 Β· Diffusion 20 Β· Fragmentation 20; non-linear root aggregation.

acleddata.com β†’

IOM RICD

IOM CMIL Β· project-based

Two-tier macro (spatial risk) + micro (community) model β€” the structural precedent for base score Γ— personal modifier.

iom.int β†’

IDMC Risk Model 2.0

IDMC Β· annual

Probabilistic displacement from natural hazards β€” feeds the "risk of staying" dimension.

internal-displacement.org β†’

Fragile States Index

Fund for Peace Β· annual

12 indicators, CAST text-analysis triangulation β€” template for structural / minor variables.

fragilestatesindex.org β†’

CDC Social Vulnerability Index

CDC/ATSDR Β· biennial

16 variables, 4 equally-weighted themes, percentile ranking β€” the personal-vulnerability layer.

atsdr.cdc.gov β†’

Global Conflict Risk Index

EU JRC Β· annual

Conflict-onset risk β€” separates active conflict (ACLED) from forward-looking risk.

jrc.ec.europa.eu β†’

OECD/JRC Composite Handbook

OECD & JRC

Definitive reference for normalisation, aggregation, weighting & sensitivity analysis.

publications.jrc.ec.europa.eu β†’

Key papers

  • Beccari, B. (2016). A Comparative Analysis of Disaster Risk, Vulnerability and Resilience Composite Indicators. PLoS Currents Disasters, PMC4807925 β€” reviews 106 index methodologies.
  • Can severity of a humanitarian crisis be quantified? Assessment of the INFORM severity index. Globalization & Health (2023). DOI:10.1186/s12992-023-00907-y β€” identifies governance & access as strongest predictors.
  • Al Fozaie (2022). A Guide to Integrating Expert Opinion and Fuzzy AHP When Generating Weights for Composite Indices. Advances in Fuzzy Systems. DOI:10.1155/2022/3396862.
  • OECD/JRC (2008). Handbook on Constructing Composite Indicators. OECD Publishing.
  • Saaty, T.L. (1990). How to Make a Decision: The Analytic Hierarchy Process. EJOR 48(1), 9–26.
  • ACAPS Ukraine Severity Model Methodology Note (March 2024) β€” worked subnational example.