Dataset Information

Predicting non-state terrorism worldwide.

ABSTRACT: Several thousand people die every year worldwide because of terrorist attacks perpetrated by non-state actors. In this context, reliable and accurate short-term predictions of non-state terrorism at the local level are key for policy makers to target preventative measures. Using only publicly available data, we show that predictive models that include structural and procedural predictors can accurately predict the occurrence of non-state terrorism locally and a week ahead in regions affected by a relatively high prevalence of terrorism. In these regions, theoretically informed models systematically outperform models using predictors built on past terrorist events only. We further identify and interpret the local effects of major global and regional terrorism drivers. Our study demonstrates the potential of theoretically informed models to predict and explain complex forms of political violence at policy-relevant scales.

SUBMITTER: Python A

PROVIDER: S-EPMC8324061 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Predicting non-state terrorism worldwide.

Python Andre A Bender Andreas A Nandi Anita K AK Hancock Penelope A PA Arambepola Rohan R Brandsch Jürgen J Lucas Tim C D TCD

Science advances 20210730 31

Several thousand people die every year worldwide because of terrorist attacks perpetrated by non-state actors. In this context, reliable and accurate short-term predictions of non-state terrorism at the local level are key for policy makers to target preventative measures. Using only publicly available data, we show that predictive models that include structural and procedural predictors can accurately predict the occurrence of non-state terrorism locally and a week ahead in regions affected by ...[more]

PMID: 34330703

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Project description:BackgroundThe Global Terrorism Database (GTD) is an open-source database on terrorist incidents around the world since 1970, and it is maintained by the National Consortium for the Study of Terrorism and Responses to Terrorism (START; College Park, Maryland USA), a US Department of Homeland Security Center of Excellence. The consortium reviews media reports to determine if an event meets eligibility to be categorized as a terrorism incident for entry into the database.ObjectiveThe objective of this study was to characterize chemical terrorism incidents reported to the GTD and understand more about the kinds of chemical agents used, the associated morbidity and mortality, the geography of incidents, and the intended targets.MethodsChemical terrorism incidents from 1970 through 2015 were analyzed by chemical agent category, injury and fatality, geographic region, and target.ResultsDuring the study period, 156,772 terrorism incidents were reported to the GTD, of which 292 (0.19%) met the inclusion criteria for analysis as a chemical terrorism incident. The reported chemical agent categories were: unknown chemical (30.5%); corrosives (23.3%); tear gas/mace (12.3%); unspecified gas (11.6%); cyanide (8.2%); pesticides (5.5%); metals (6.5%); and nerve gas (2.1%). On average, chemical terrorism incidents resulted in 51 injuries (mean range across agents: 2.5-1,622.0) and seven deaths (mean range across agents: 0.0-224.3) per incident. Nerve gas incidents (2.1%) had the highest mean number of injuries (n = 1,622) and fatalities (n = 224) per incident. The highest number of chemical terrorism incidents occurred in South Asia (29.5%), Western Europe (16.8%), and Middle East/North Africa (13.0%). The most common targets were private citizens (19.5%), of which groups of women (22.8%) were often the specific target. Incidents targeting educational institutions often specifically targeted female students or teachers (58.1%).ConclusionsChemical terrorism incidents rarely occur; however, the use of certain chemical terrorism agents, for example nerve gas, can cause large mass-causality events that can kill or injure thousands with a single use. Certain regions of the world had higher frequency of chemical terrorism events overall, and also varied in their frequencies of the specific chemical terrorism agent used. Data suggest that morbidity and mortality vary by chemical category and by region. Results may be helpful in developing and optimizing regional chemical terrorism preparedness activities.

Dataset Information

Predicting non-state terrorism worldwide.

Publications

Predicting non-state terrorism worldwide.

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