The dramatic increase in the number of fatalities in organized violence, seen between 2011 and 2014, did not continue in 2015 and 2016. Rather, the notation of some 131,000 fatalities in 2014 was followed by a steep decline, with just below 119,000 in 2015 and a little over 102,000 fatalities in 2016. Despite the decrease, the number was the fifth highest during the entire 1989-2016 period. Most of the fatalities -over 87,000 -were incurred in statebased conflicts, the main driver behind the trend. Just as the number of fatalities, the number of state-based conflicts, albeit remaining on a high level, continued to decrease in 2016, going from 52 to 49, with 12 of them reaching the level of war, with at least 1,000 battle-related deaths. Also the non-state conflicts dropped in number in 2016, from 73 to 60. This was followed by a decrease in the number of fatalities, and only one conflict caused more than 1,000 deaths. Twenty-one actors were registered in one-sided violence, down by five from 2015. A number this low has only been recorded twice before; in both 2009 and 2010, 21 one-sided actors were listed in UCDP data. The number of fatalities also decreased, going from almost 9,800 to a little over 6,000.

This article presents ViEWS – a political violence early-warning system that seeks to be maximally transparent, publicly available, and have uniform coverage, and sketches the methodological innovations required to achieve these objectives. ViEWS produces monthly forecasts at the country and subnational level for 36 months into the future and all three UCDP types of organized violence: state-based conflict, non-state conflict, and one-sided violence in Africa. The article presents the methodology and data behind these forecasts, evaluates their predictive performance, provides selected forecasts for October 2018 through October 2021, and indicates future extensions. ViEWS is built as an ensemble of constituent models designed to optimize its predictions. Each of these represents a theme that the conflict research literature suggests is relevant, or implements a specific statistical/machine-learning approach. Current forecasts indicate a persistence of conflict in regions in Africa with a recent history of political violence but also alert to new conflicts such as in Southern Cameroon and Northern Mozambique. The subsequent evaluation additionally shows that ViEWS is able to accurately capture the long-term behavior of established political violence, as well as diffusion processes such as the spread of violence in Cameroon. The performance demonstrated here indicates that ViEWS can be a useful complement to non-public conflict-warning systems, and also serves as a reference against which future improvements can be evaluated.

This article presents the Uppsala Conflict Data Program (UCDP) “Violent Political Protest” (VPP) data set: a new –standalone- category of organized violence, which complements, and is compatible with, UCDP’s three categories of organized violence: one-sided violence, non-state, and state-based conflict. It consists of violent political protests, with at least 25 casualties during a year, in which informally organized civilians challenge states over governmental or territorial issues. We describe the data collection process, and demonstrate the data’s use with empirical analyses. Violent political protest is present globally, but most prevalent in the Middle East and Africa, and increasingly common over time. Violent political protest frequently co-occurs with state-based conflicts, but rarely due to conflict escalation. We explore if this is due to shared contexts, and find that gender inequality increases the likelihood of VPP onset, similar to state-based conflicts. Finally, we identify avenues for future research, including using VPP to assist in a more precise and complete analysis of organized violence.