Skip to content

Research at St Andrews

Explaining the lethality of boko haram’s terrorist attacks in nigeria, 2009–2014: a hierarchical Bayesian approach

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Since 2009, Nigeria has been the scene of numerous deadly terrorist attacks perpetrated by the terrorist group Boko Haram. In response to this threat, stakeholders in the fight against terrorism have deployed various counterterrorism policies, the costs of which could be reduced through efficient preventive measures. Statistical models able to integrate complex spatial dependence structures have not yet been applied, despite their potential for providing guidance to assess characteristics of terrorist attacks. In an effort to address this shortcoming, we use a flexible approach that represents a Gaussian Markov random field through stochastic partial differential equation and model the fine-scale spatial patterns of the lethality of terrorism perpetrated by Boko Haram in Nigeria from 2009 to 2014. Our results suggest that the lethality of terrorist attacks is contagious in space and attacks are more likely to be lethal at higher altitudes and far from large cities.



Original languageEnglish
Title of host publicationBayesian statistics in action
Subtitle of host publicationBAYSM 2016, Florence, Italy, June 19-21
EditorsR Argiento, E Lanzarone, I Antoniano Villalobos, A Mattei
Place of PublicationCham
Number of pages9
ISBN (Print)9783319540832
StatePublished - 2017
Event3rd Bayesian Young Statisticians Meeting, BAYSM 2016 - Florence, Italy
Duration: 19 Jun 201621 Jun 2016

Publication series

NameSpringer Proceedings in Mathematics & Statistics
ISSN (Print)2194-1009


Conference3rd Bayesian Young Statisticians Meeting, BAYSM 2016

    Research areas

  • Bayesian hierarchical model, Boko Haram, GMRF, SPDE, Terrorism

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

View graph of relations

Related by author

  1. 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

  2. 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

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

    Python, A., Illian, J. B., Jones-Todd, C. M. & Blangiardo, M. 28 May 2018 In : Journal of the Royal Statistical Society: Series A (Statistics in Society). Early View

    Research output: Contribution to journalArticle

  4. Level set Cox processes

    Hildeman, A., Bolin, D., Wallin, J. & Illian, J. B. 4 Apr 2018 In : Spatial Statistics. In press

    Research output: Contribution to journalArticle

  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

ID: 248480450