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Kafr Qāsim
City in Central, Israel
Overview
Kafr Qāsim is a lively town in Israel's Central District, known for its welcoming community, traditional markets, and cultural traditions. The city offers an authentic local experience, blending historical sites with modern amenities.
Geographic Context
Jurisdiction
Israel
District
Central
Population
22,743
Time Zone
Asia/Jerusalem
Coordinates
32.11°, 34.98°
Key Metrics
Safety Score · estimate
65
Female Safety
55
LGBTQ+ Safety
35
Traffic Safety
60
Food Safety
80
Monthly Cost · estimate
$1,693
Local Cost
$1,130
Local Income
$1,800
Cashless
60
English
45
Temperature
19.7°C
Summer Avg
26.1°C
Winter Avg
12.4°C
Record High
42.5°C
Record Low
-0.4°C
Humidity
66%
Precipitation
357 mm
Internet Speed
248 Mbps
Upload
98 Mbps
Latency
5 ms
City Vibrancy
20
Coworking
0
Cafes
1
Nightlife
0
Parks
19
Transport
0
Walk Score
0
Footways
—
Airport
TLV
Distance
15 km
Explore
Data sources
Source-backed data
World Air Quality Index - Latest available city-level air quality station measurement. Record updated 2025-12-05.
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-06.
OpenStreetMap transport extract - Walkability, footway density, and airport access metrics derived from mapped transport features. Record updated 2025-12-05.
Estimates and unverified origins
Oyster List climate data - Climate origins are unverified. Available methods include historical APIs and AI estimates; stored rows do not identify the original dataset, reference period, or model for each value. Treat these summaries as estimates until independently verified. Record updated 2026-03-22.
Oyster List city price estimates - Price origins are unverified. Available generation methods include AI estimates; stored records do not identify a survey, observation period, or model for each price. Record updated 2026-01-14.
Oyster List AI-assisted estimates - Safety, lifestyle, income, and practical scores include model-assisted estimates. Stored records do not identify supporting observations for each score. Model-reported confidence: 68/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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