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Nsang
City in Kié-Ntem, Equatorial Guinea
Overview
Nsang is a small, welcoming town set in the Kié-Ntem region of Equatorial Guinea. Known for its community spirit and scenic riverside landscapes, it offers visitors a glimpse into authentic local life and tranquil surroundings. The town is a gateway for exploring the region's natural beauty and engaging with its friendly residents.
Geographic Context
Jurisdiction
Equatorial Guinea
Province
Kié-Ntem
Population
2,122
Time Zone
Africa/Malabo
Coordinates
2.02°, 10.95°
Key Metrics
Safety Score · estimate
38
Female Safety
32
LGBTQ+ Safety
20
Traffic Safety
35
Food Safety
40
Monthly Cost · estimate
$455
Local Cost
$275
Local Income
$130
Cashless
5
English
10
Temperature
23.5°C
Summer Avg
22.9°C
Winter Avg
24.1°C
Record High
36.7°C
Record Low
15.0°C
Humidity
88%
Precipitation
1572 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
GEM
Distance
39 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 2025-12-08.
OpenStreetMap transport extract - Walkability, footway density, and airport access metrics derived from mapped transport features. Record updated 2025-12-06.
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: 52/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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