Vicious Circle Research

Main Findings

Use the dropdown to compare spatial patterns across socio-economic cluster, disability rate, and income support rate. Bubble size reflects population, so dense areas stand out quickly.

Main Findings: Values closer to -1 or 1 indicate stronger negative/positive correltation between different indicators.

Methodology: How We Calculated the Indices

Both indices are normalized to a range of -1 (Distress) to +1 (Resilience).

1. The Social Index (X-Axis)

A weighted measure of a settlement's socio-economic strength:

• 50% Socio-Economic Score (CBS): The official government ranking.
• 25% Peripherality Index: Geographic distance from the center.
• 25% Income Support Rate: A direct measure of deep poverty.

Meaning: A score of +1 represents a wealthy, central locality; -1 represents a poor, peripheral one.

2. The Health Index (Y-Axis)

A weighted measure of the working-age population's health (inverted, so high = healthy):

• 50% General Disability Rate: The volume of disability cases.
• 25% Special Services Rate: Indicates severe disability requiring daily assistance.
• 25% Mobility Disability Rate: Indicates physical mobility limitations.

Meaning: A score of +1 represents a locality with very low disability rates (Healthy); -1 represents high disability rates (Unhealthy).

Main Findings: Higher social vulnerability aligns with higher disability severity across settlements, even after combining multiple indicators into the social and health indices.

Key Anomalies

• The "Service Magnet" Effect (Regional Hubs): Cities like Tiberias and Be'er Sheva suffer from "excess disability" (Red Zone). They act as regional hubs, attracting vulnerable populations seeking medical services and public housing. These cities carry a "regional burden".
• Community Resilience: Settlements like Brukhin, Talmon and Ofra significantly outperform the model. Strong community support networks and younger demographics likely prevent the slide into welfare dependency.

Main Findings: Higher income support tends to co-occur with higher LTC rates, reflecting overlapping vulnerability among older populations.

Main Findings

The chart compares the average disability rate across Israeli settlements, grouped into socio-economic quartiles—from the lowest (Q1) to the highest (Q4). The analysis includes only settlements with more than 10,000 residents. Each bar represents the mean disability rate across settlements within that quartile. The key takeaway is that there is no linear downward trend across the three lower quartiles (Q1–Q3): the values are similar, and Q2 is even slightly higher than Q1. In contrast, the highest quartile (Q4) shows a sharp and substantial drop in disability rates compared to the other quartiles.

Benchmark: Overall weighted disability rate = 6.76%.

Main Findings: Settlements with higher disability rates also tend to show higher income support rates, indicating overlapping vulnerability.

Main Findings: Lower socio-economic scores are associated with higher disability rates, especially in peripheral localities.

Main Findings: LTC rates are influenced by age structure, but still show a meaningful association with socio-economic conditions.