Multinational - Strengthening ECOWAS Early Warning and Response Capacity for Regional Stability
Sector: Commercial • Location: Multinational
Source: African Development Bank (AfDB)
The ECOWAS Early Warning and Response Network (ECOWARN) is built upon an understanding of the need for conflict sensitivity and contextual risk assessment. The suite of ECOWAS Early Warning and Early Response (EWER) tools and efforts reflects both the shared challenges of the Member states, but also their unique characteristics, thereby factoring in the complex landscape of human securi
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | Obfuscated Data |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
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Phone | 0000000000 |
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Description
Description | The ECOWAS Early Warning and Response Network (ECOWARN) is built upon an understanding of the need for conflict sensitivity and contextual risk assessment. The suite of ECOWAS Early Warning and Early Response (EWER) tools and efforts reflects both the shared challenges of the Member states, but also their unique characteristics, thereby factoring in the complex landscape of human security across the region, while structuring early warning analysis and response under a common framework composed of five key pillars encompassing the range of resilience factors and threats to human security: (1) Environment & Natural Disasters; (2) Crime & Criminality; (3) Health & Pandemics; (4) Security; (5) Governance & Human Rights. These five pillars cover 56 human security indicators underpinning the ECOWAS regional Early Warning system. The Early Warning framework is also adopted by national early warning bodies, thereby creating synergy to respond tothreat and equips countries with the means to cooperate and promote regional peace and security. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
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Article Published Date | Obfuscated Data |
