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Governmental and nongovernmental organizations have increasingly relied on early-warning systems of conflict to support their decisionmaking. Predictions of war intensity as probability distributions prove closer to what policymakers need than point estimates, as they encompass useful representations of both the most likely outcome and the lower-probability risk that conflicts escalate catastrophically. Point-estimate predictions, by contrast, fail to represent the inherent uncertainty in the distribution of conflict fatalities. Yet, current early warning systems are preponderantly focused on providing point estimates, while efforts to forecast conflict fatalities as a probability distribution remain sparse. Building on the predecessor VIEWS competition, we organize a prediction challenge to encourage endeavours in this direction. We invite researchers across multiple disciplinary fields, from conflict studies to computer science, to forecast the number of fatalities in state-based armed conflicts, in the form of the UCDP ‘best’ estimates aggregated to two units of analysis (country-months and PRIO-GRID-months), with estimates of uncertainty. This article introduces the goal and motivation behind the prediction challenge, presents a set of evaluation metrics to assess the performance of the forecasting models, describes the benchmark models which the contributions are evaluated against, and summarizes the salient features of the submitted contributions.

Preventing armed conflict is key to promoting development and well-being in the Sahel. To strengthen its work to promote peace globally, the United Nations have recently stressed the importance of early action and early warning about impending conflict. This report presents the ViEWS system, a systematic, data-driven conflict early-warning system developed for Africa and the Middle East. Designed to complement expert assessments drawing on qualitative methods, the system produces estimates of the probability that armed conflict events will occur in countries and sub-national locations during each of the next 1–36 months. The report outlines the main features of the system, discusses the uncertainties involved and how well the system handles these, and presents the latest forecasts for the UNISS countries of the Sahel. The ViEWS forecasts are updated on a monthly basis and made available in full through an API, and in summarised form on the ViEWS website. The report also outlines some possible future developments and improvements of the system. 

The Arab States are affected by a wide range of environmental challenges exacerbated by current and projected impacts of climate change, including, among others, depletion of scarce natural resources such as water and arable land, increasing pollution levels, and the growing number and magnitude of extreme weather events. At the same time, the Arab region has been a hotspot for conflicts during the last decades. This highlights the need among policymakers and practitioners of conflict prevention and peacebuilding to better understand how climate change might contribute to current or future dynamics of conflict. This report provides a conceptual framework for analysts and policymakers in the region that shows how the loss of livelihood, economic contraction, resource competition, migration, poor governance, and other social processes (mechanisms) spurred by climate risk are more likely to increase conflict risk when occurring in certain contexts.

This article presents an update to the ViEWS political Violence Early-Warning System. This update introduces (1) a new infrastructure for training, evaluating, and weighting models that allows us to more optimally combine constituent models into ensembles, and (2) a number of new forecasting models that contribute to improve overall performance, in particular with respect to effectively classifying high- and low-risk cases. Our improved evaluation procedures allow us to develop models that specialize in either the immediate or the more distant future. We also present a formal, 'retrospective' evaluation of how well ViEWS has done since we started publishing our forecasts from July 2018 up to December 2019. Our metrics show that ViEWS is performing well when compared to previous out-of-sample forecasts for the 2015-17 period. Finally, we present our new forecasts for the January 2020-December 2022 period. We continue to predict a near-constant situation of conflict in Nigeria, Somalia, and DRC, but see some signs of decreased risk in Cameroon and Mozambique.