Skip to content

Research at St Andrews

A Bayesian approach to modelling subnational spatial dynamics of worldwide non-state terrorism, 2010-2016

Research output: Contribution to journalArticle

DOI

Open Access Status

  • Embargoed (until 28/05/19)

Author(s)

Andre Python, Janine B. Illian, Charlotte M. Jones-Todd, Marta Blangiardo

School/Research organisations

Abstract

Terrorism persists as a worldwide threat, as exemplified by the on‐going lethal attacks perpetrated by Islamic State in Iraq and Syria, Al Qaeda in Yemen and Boko Haram in Nigeria. In response, states deploy various counterterrorism policies, the costs of which could be reduced through efficient preventive measures. Statistical models that can account for complex spatiotemporal dependences have not yet been applied, despite their potential for providing guidance to explain and prevent terrorism. To address this shortcoming, we employ hierarchical models in a Bayesian context, where the spatial random field is represented by a stochastic partial differential equation. Our main findings suggest that lethal terrorist attacks tend to generate more deaths in ethnically polarized areas and in locations within democratic countries. Furthermore, the number of lethal attacks increases close to large cities and in locations with higher levels of population density and human activity.
Close

Details

Original languageEnglish
JournalJournal of the Royal Statistical Society: Series A (Statistics in Society)
VolumeEarly View
Early online date28 May 2018
DOIs
StateE-pub ahead of print - 28 May 2018

    Research areas

  • Bayesian hierarchical models, GMRF, Space-time models, SPDE, Terrorism

Discover related content
Find related publications, people, projects and more using interactive charts.

View graph of relations

Related by author

  1. Understanding species distribution in dynamic populations: a new approach using spatio‐temporal point process models

    Soriano-Redondo, A., Jones-Todd, C. M., Bearhop, S., Hilton, G. M., Lock, L., Stanbury, A., Votier, S. C. & Illian, J. B. 6 Feb 2019 (Accepted/In press) In : Ecography.

    Research output: Contribution to journalArticle

  2. Non-stationary Gaussian models with physical barriers

    Bakka, H., Vanhatalo, J., Illian, J. B., Simpson, D. & Rue, H. 18 Jan 2019 In : Spatial Statistics. In press

    Research output: Contribution to journalArticle

  3. Accounting for preferential sampling in species distribution models

    Pennino, M. G., Paradinas, I., Illian, J. B., Muñoz, F., Bellido, J. M., López-Quílez, A. & Conesa, D. 1 Jan 2019 In : Ecology and Evolution. 9, 1, p. 653-663 11 p.

    Research output: Contribution to journalArticle

  4. Level set Cox processes

    Hildeman, A., Bolin, D., Wallin, J. & Illian, J. B. Dec 2018 In : Spatial Statistics. 28, p. 169-193

    Research output: Contribution to journalArticle

  5. Identifying prognostic structural features in tissue sections of colon cancer patients using point pattern analysis

    Jones-Todd, C. M., Caie, P., Illian, J. B., Stevenson, B. C., Savage, A., Harrison, D. J. & Brown, J. L. 28 Nov 2018 In : Statistics in Medicine. Early View

    Research output: Contribution to journalArticle

Related by journal

ID: 252871422