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


Open Access Status

  • Embargoed (until 28/05/19)


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

School/Research organisations


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.


Original languageEnglish
JournalJournal of the Royal Statistical Society: Series A (Statistics in Society)
VolumeEarly View
Early online date28 May 2018
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. 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

  2. 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

  3. Careful prior specification avoids incautious inference for log-Gaussian Cox point processes

    Sørbye, S., Illian, J. B., Simpson, D. P., Burlsem, D. & Rue, H. 2 Nov 2018 In : Journal of the Royal Statistical Society: Series C (Applied Statistics). Early View

    Research output: Contribution to journalArticle

  4. Spatial modeling with R-INLA: a review

    Bakka, H., Rue, H., Fuglstad, G., Riebler, A., Bolin, D., Illian, J., Krainski, E., Simpson, D. & Lindgren, F. 5 Jul 2018 In : Wiley Interdisciplinary Reviews: Computational Statistics. Early View, 24 p., e1443

    Research output: Contribution to journalReview article

  5. A spatiotemporal multispecies model of a semicontinuous response

    Jones-Todd, C. M., Swallow, B., Illian, J. B. & Toms, M. Apr 2018 In : Journal of the Royal Statistical Society: Series C (Applied Statistics). 67, 3, p. 705-722

    Research output: Contribution to journalArticle

Related by journal

ID: 252871422