Catalogue of Early Warning tools for Anticipating the impact of conflict
The number of Early Warning tools for anticipating the impacts of conflict and violence is growing rapidly. Methods range from qualitative, crowd-sourced data, news scraping, to advanced AI and machine learning models to predict when conflict might be likely to escalate, sometimes compounded by climate hazards. That is why the Climate Centre, together with ACAPS, put together this living catalogue of early warning tools and methodologies to keep track of the various approaches to predictive action developed and utilized by actors across the sector.
Many of these tools were presented at the Early Warning Early Action Workshop hosted by the NYU Center on International Cooperation on May 18 – May 20, 2021. The Humanitarian Data Exchange also hosts a catalogue of predictive models that is regularly updated and complements the list presented here. ACLED’s Early Warning Research Hub is another great resource for applied models to predict and prevent violence. A new initiative, called the Complex Risk Analytics Fund (CRAF’d), spearheaded by the UN, and supported by Germany and the United Kingdom, is looking to scale up investments into data and analytics needed to better anticipate, prevent, and respond to complex risks before they become crises.
These tools all share a common objective to inform decisions that can reduce the worst impacts of conflict. For more info, join the Anticipatory Action in Conflict working group.
Tools/ Methodologies
Developed by
UNEP, Earth Blox, University of Edinburgh
Subject
Compound hazards (climate and conflict)
Predicts
Impacts on peace and security, development, and resilience due to climate stressors
Type of AA *
Type 1
Coverage
Pilot phase in Somalia
Description
Provide easy to digest multi-layer risk analysis of climate and social risk factors that do not require technical expertise to use. The tool is GIS based and provides a map of multi-layer risk with further datial on specific risks, strategies and solutions for identified hotspots on the map
Methods
GIS
Contact
Marie Schellens, UNEP (strata@un.org)
Visit the Strata webite here
*Type of AA (1 or 2 - 1 corresponds to AA for climate related disasters in conflict contexts, while type 2 corresponds to AA of impacts of conflict)
Developed by
Potsdam Institute for Climate Impact Research
Subject
Conflict
Predicts
Security risks to sustainable development from impacts of climate change
Type of AA *
Type 1
Coverage
Global, methodology is scalable
Description
Global climate and security risk and foresight assessment.
Methods
Multidisciplinary project based on quantitative assessments and impact modeling and qualitative approaches with a stakeholder focus
Contact
Links
Learn more here.
*Type of AA (1 or 2 - 1 corresponds to AA for climate related disasters in conflict contexts, while type 2 corresponds to AA of impacts of conflict)
Developed by
German Foreign Office - PREVIEW
Subject
Conflict
Predicts
Conflict due to anumber of climate and social factors in order to provide the information to take early action
Type of AA *
Type 1
Coverage
German operational presence in Lake Chad basin
Description
Data-driven solutions for proactive capacity building for early action in anticipation of conflict
Methods
Compound risk analysis
Contact
*Type of AA (1 or 2 - 1 corresponds to AA for climate related disasters in conflict contexts, while type 2 corresponds to AA of impacts of conflict)
Developed by
PACT Ethiopia
Subject
Conflict
Predicts
Community violence
Type of AA *
Type 2
Coverage
Ethiopia
Description
Improving existing EWEA systems in Ethiopia. Based on close collaboration with the community to source and verify data on incidents and signals. Designed to improve Rapid Response actions to conflict through a network of relevant partnerships. The steering comittee includes memers from civil society, communities, religious leaders, administration, police representatives, state and non-state actors
Methods
Qualitative, community-based
Contact
E-mail: info@pactworld.org
Links
Learn more here.
*Type of AA (1 or 2 - 1 corresponds to AA for climate related disasters in conflict contexts, while type 2 corresponds to AA of impacts of conflict)
Developed by
ACLED
Subject
Conflict
Predicts
Violence trends
Type of AA *
Type 2
Coverage
Worldwide
Description
ACLED's strategy to collect accurate, local data on conflict events relies on innovative partnerships with local organizations and associations
Methods
News sourcing and verification
Contact
Roudabeh Kishi - Director of Research and Innovation
Links
Learn more here.
*Type of AA (1 or 2 - 1 corresponds to AA for climate related disasters in conflict contexts, while type 2 corresponds to AA of impacts of conflict)
Developed by
Hala Systems
Subject
Conflict
Predicts
Violent events
Type of AA *
Type 2
Coverage
Syria
Description
Sentry AI is an indication and warning system that utilizes a multi-sensor network to generate a credible, real-time, situational awareness of threats in the toughest places on earth. Sentry uses artificial intelligence (AI) to instantaneously validate information from multiple sources, allowing stakeholders to detect, identify, and predict threats.
Methods
AI, machine learning, remote sensing
Contact
Daniel Henebery
E-Mail: info@halasystems.com
Links
Learn more here.
*Type of AA (1 or 2 - 1 corresponds to AA for climate related disasters in conflict contexts, while type 2 corresponds to AA of impacts of conflict)
Developed by
Sentinel Project
Subject
Conflict
Predicts
Violence based on misinformation
Type of AA *
Type 2
Coverage
Worldwide
Description
Crowdsourcing rumours, mapping their spread, verifying information and returning information back to the community in order to analyze the spread of misinformation and take early action to prevent atrocities like genocide.
Methods
Direct cooperation with communitie s- innovative use of technology - needs drivien
Contact
Christopher Tuckwood
E-mail: chris@thesentinelproject.org
Yuriko Coper-Smith
E-Mail: yuriko@thesentinelproject.org
Links
Learn more here.
*Type of AA (1 or 2 - 1 corresponds to AA for climate related disasters in conflict contexts, while type 2 corresponds to AA of impacts of conflict)
Developed by
Hatebase
Subject
Conflict
Predicts
Violence base on hate speech and misinformation
Type of AA *
Type 2
Coverage
Worldwide
Description
Multilingual database of online hate speech and misinformation
Methods
AI and machine learning methods to identify hatespeech and misinformation, while engaging communities directly to address increasing trends proactively
Contact
View contact form here.
Links
Learn more here.
*Type of AA (1 or 2 - 1 corresponds to AA for climate related disasters in conflict contexts, while type 2 corresponds to AA of impacts of conflict)
Developed by
World Resources Institute
Subject
Conflict
Predicts
Violence based on water-related security risks
Type of AA *
Type 1
Coverage
Worldwide
Description
The Water, Peace and Security (WPS) Partnership was founded in 2018 to pioneer the development of innovative tools that identify and address water-related security risks. The overall objective of the Water, Peace and Security partnership is to offer a platform where actors from the global defense, development, diplomacy, and disaster relief sectors (among others) and national governments of developing countries can identify conflict hotspots before violence erupts, begin to understand the local context, and prioritize opportunities for water interventions.
Methods
Machine learning-based methodology to forecast conflict (defined as organized violence resulting in at least 10 fatalities over a 12 month period), up to a year in advance using a random forest model. When applied to reserved test data, the model captures 86% of future conflicts.
Contact
E-mail: info@waterpeacesecurity.org
Links
Learn more here.
*Type of AA (1 or 2 - 1 corresponds to AA for climate related disasters in conflict contexts, while type 2 corresponds to AA of impacts of conflict)
Developed by
ConflictForecast.org
Subject
Conflict
Predicts
Identify countries at risk of conflict in order to determine where early action can be taken to prevent it
Type of AA *
Type 2
Coverage
Worldwide
Description
Conflict forecast provides forecasts for outbreaks of political violence and escalations into internal armed conflict. Our method based on five years of academic research and exploits millions of newspaper articles through automated summaries.
Methods
2-step machine learning method using aggregated news data from multiple sources
Contact
Hannes Mueller, Christopher Rauh
E-mail: conflictforecast@gmail.com
Links
Learn more here.
*Type of AA (1 or 2 - 1 corresponds to AA for climate related disasters in conflict contexts, while type 2 corresponds to AA of impacts of conflict)
Developed by
UN University
Subject
Conflict
Predicts
Identify factors that put people, especially children, at risk of recruitment into armed groups
Type of AA *
Type 2
Description
MEAC seeks to understand how and why individuals exit armed groups and which interventions support full and sustained transitions to civilian life. It collects data on all aspects of an individuals association with an armed group, including on the nature of their recruitment
Methods
Qualitative
Contact
Siobhan O'Neil
E-mail: oneil@unu.edu
Links
Learn more here.
*Type of AA (1 or 2 - 1 corresponds to AA for climate related disasters in conflict contexts, while type 2 corresponds to AA of impacts of conflict)