An investigation into microcycles of violence by the Taliban

  • Julie Haukland Rieber-Mohn
  • Kartikeya TripathiEmail author
Original Article


This study investigated the notion of near-repeat victimisation in the context of the Taliban insurgency in Afghanistan. Applying methods originally developed for epidemiological research the current study found strong evidence that attacks by the Taliban insurgency occurred in microcycles of localised bursts of terrorist events. Nearly 40% of the 305 attacks analysed by the Taliban in 2016 took place within 5 miles and 2 weeks of each other. A binary logistic regression showed that, compared to other strategies, attacks were more likely to occur in microcycles when they were on national or provincial capitals, non-fatal and included bombings or armed assaults. These findings are in accordance with previous research conducted in other countries, suggesting that globally, terrorist organisations face similar strategic options and constraints. The results have implications for the understanding of terrorist campaigns at a more disaggregated level, for the prediction of future attacks and for counter-terrorism strategies.


Microcycles of violence Taliban Afghanistan Counter-terrorism Insurgency 



  1. Andresen, M.A., and G.W. Jenion. 2004. The unspecified temporal criminal event: What is unknown is known with aoristic analysis and multinomial logistic regression. Western Criminology Review 5 (3): 1–11.Google Scholar
  2. Bapat, N.A. 2007. The internationalization of terrorist campaigns. Conflict Management and Peace Science 24 (4): 265–280.CrossRefGoogle Scholar
  3. Behlendorf, B., G. LaFree, and R. Legault. 2012. Microcycles of violence: Evidence from terrorist attacks by ETA and the FMLN. Journal of Quantitative Criminology 28 (1): 49–75. Scholar
  4. Block, S., and S. Fujita. 2013. Patterns of near repeat temporary and permanent motor vehicle thefts. Crime Prevention and Community Safety 15 (2): 151–167. Scholar
  5. Bowers, K. 2014. Risky facilities: Crime radiators or crime absorbers? A comparison of internal and external levels of theft. Journal of Quantitative Criminology 30 (3): 389–414. Scholar
  6. Braithwaite, A., and S.D. Johnson. 2015. The battle for Baghdad: Testing hypotheses about insurgency from risk heterogeneity, repeat victimization, and denial policing approaches. Terrorism and Political Violence 27 (1): 112–132. Scholar
  7. Brantingham, P.J., and P.L. Brantingham (eds.). 1981. Environmental criminology. London: Sage Publications.Google Scholar
  8. Brantingham, P.J., and P.L. Brantingham. 1982. Mobility, notoriety, and crime: A study of crime patterns in urban nodal points. Journal of Environmental Systems 11: 89–99.CrossRefGoogle Scholar
  9. Cassman, D. 2016. The Taliban. Mapping militant organizations. Retrieved 31 June 2017, from
  10. Chainey, S.P., and B.F.A. da Silva. 2016. Examining the extent of repeat and near repeat victimisation of domestic burglaries in Belo Horizonte. Brazil. Crime Science 5 (1): 1. Scholar
  11. Chainey, S.P., and J. Ratcliffe. 2005. GIS and crime mapping. Chichester: Wiley.CrossRefGoogle Scholar
  12. Chainey, S.P., L. Tompson, and S. Uhlig. 2008. The utility of hotspot mapping for predicting spatial patterns of crime. Security Journal 21 (1–2): 4–28. Scholar
  13. Clarke, R.V.G., and G.R. Newman. 2006. Outsmarting the terrorists. Santa Barbara: Greenwood Publishing Group.Google Scholar
  14. Cohen, J. 1941. The geography of crime. The Annals of the American Academy of Political and Social Science 217 (1): 29–37. Scholar
  15. Cohen, L., and M. Felson. 1979. Social change and crime rate trends: A routine activity approach. American Sociological Review 44 (4): 588–608.CrossRefGoogle Scholar
  16. Cornish, D.B., and R.V. Clarke. 1986. The reasoning criminal. New York: Springer.CrossRefGoogle Scholar
  17. Cornish, D.B., and R.V. Clarke. 2003. Opportunities, precipitators and criminal decisions: A reply to Wortley’s critique of situational crime prevention. Crime Prevention Studies 16: 41–96.Google Scholar
  18. Davies, T., and S.D. Johnson. 2015. Examining the relationship between road structure and burglary risk via quantitative network analysis. Journal of Quantitative Criminology 31 (3): 481–507. Scholar
  19. Dugan, L., G. LaFree, and A.R. Piquero. 2005. Testing a rational choice model of airline hijackings. Criminology 43 (4): 1031–1065. Scholar
  20. Falk, G.J. 1952. The influence of the seasons on the crime rate. The Journal of Criminal Law, Criminology, and Police Science 43 (2): 199–213.CrossRefGoogle Scholar
  21. Forest, J.J. 2012. Global trends in kidnapping by terrorist groups. Global Change, Peace & Security 24 (3): 311–330. Scholar
  22. Fuchs, K., and A. Deutz. 2002. Use of variograms to detect critical spatial distances for the Knox’s test. Preventive Veterinary Medicine 54 (1): 37–45. Scholar
  23. George, D. 1984. Meta-preferences: Reconsidering contemporary notions of free choice. International Journal of Social Economics 11 (3/4): 92–107.CrossRefGoogle Scholar
  24. Green, S.B. 1991. How many subjects does it take to do a regression analysis. Multivariate Behavioral Research 26 (3): 499–510. Scholar
  25. Groff, E.R., and B. Lockwood. 2014. Criminogenic facilities and crime across street segments in Philadelphia: Uncovering evidence about the spatial extent of facility influence. Journal of Research in Crime and Delinquency 51 (3): 277–314. Scholar
  26. Grubb, J., and M. Nobles. 2016. A spatiotemporal analysis of Arson. Journal of Research in Crime and Delinquency 53 (1): 66–92. Scholar
  27. Grubesic, T.H., and E.A. Mack. 2008. Spatio-temporal interaction of urban crime. Journal of Quantitative Criminology 24 (3): 285–306. Scholar
  28. Haberman, C.P., and J.H. Ratcliffe. 2012. The predictive policing challenges of near repeat armed street robberies. Policing: A Journal of Policy and Practice 6 (2): 151–166. Scholar
  29. Hedges, M., and T. Karasik. 2010. Evolving Terrorist Tactics, Techniques, and Procedures (TTP) migration across South Asia, Caucasus, and the Middle East. Dubai: Institute of Near East and Gulf Military Analysis.Google Scholar
  30. Johnson, S.D., W. Bernasco, K.J. Bowers, H. Elffers, J. Ratcliffe, G. Rengert, and M. Townsley. 2007. Space-time patterns of risk: A cross national assessment of residential burglary victimization. Journal of Quantitative Criminology 23 (3): 201–219. Scholar
  31. Johnson, S.D., and K.J. Bowers. 2004. The burglary as clue to the future: The beginnings of prospective hot-spotting. European Journal of Criminology 1 (2): 237–255. Scholar
  32. Johnson, S.D., and K.J. Bowers. 2010. Permeability and burglary risk: are cul-de-sacs safer? Journal of Quantitative Criminology 26 (1): 89–111. Scholar
  33. Johnson, S.D., and A. Braithwaite. 2009. Spatio-temporal modeling of insurgency in Iraq. In Reducing terrorism through situational crime prevention, ed. J.D. Freilich and G. Newman, 9–32. New York: Criminal Justice Press.Google Scholar
  34. Johnson, S.D., and A. Braithwaite. 2016. Spatial and temporal analysis of terrorism and insurgency. In The Handbook of the criminology of terrorism, ed. G. LaFree and J.D. Freilich. Chichester: Wiley.Google Scholar
  35. Johnson, N., S. Carran, J. Botner, K. Fontaine, N. Laxague, P. Nuetzel, J. Turnley, B. Tivnan, et al. 2011. Pattern in escalations in insurgent and terrorist activity. Science 333 (6038): 81–84. Scholar
  36. Johnson, S.D., L. Summers, and K. Pease. 2009. Offender as forager? A direct test of the boost account of victimization. Journal of Quantitative Criminology 25 (2): 181–200. Scholar
  37. Kalantari, M., B. Yaghmaei, and S. Ghezelbash. 2016. Spatio-temporal analysis of crime by developing a method to detect critical distances for the Knox test. International Journal Of Geographical Information Science 30 (11): 2302–2320. Scholar
  38. Knox, G. 1964. Epidemiology of childhood leukaemia in Northumberland and Durham. British Journal of Preventive & Social Medicine 18 (1): 17.Google Scholar
  39. Kulldorff, M. (2006). SaTScan user guide. Retrieved from
  40. Kulldorff, M., and U. Hjalmars. 1999. The Knox method and other tests for space-time interaction. Biometrics 55 (2): 544–552. Scholar
  41. LaFree, G., and L. Dugan. 2016. Global terrorism and the deadliest groups since 2001. In Peace and conflict 2016, ed. D. Backer, R. Bhavnani, and P. Huth. New York: Routledge.Google Scholar
  42. LaFree, G., L. Dugan, and E. Miller. 2014. Putting terrorism in context: Lessons from the Global Terrorism Database. New York: Routledge.CrossRefGoogle Scholar
  43. LaFree, G., L. Dugan, M. Xie, and P. Singh. 2012. Spatial and temporal patterns of terrorist attacks by ETA 1970 to 2007. Journal of Quantitative Criminology 28 (1): 7–29. Scholar
  44. Lockwood, B. 2012. The presence and nature of a near-repeat pattern of motor vehicle theft. Security Journal 25 (1): 38–56. Scholar
  45. Mack, E.A., N. Malizia, and S.J. Rey. 2012. Population shift bias in tests of space–time interaction. Computers, Environment and Urban Systems 36 (6): 500–512. Scholar
  46. Mandala, M. 2016. Terrorist Assassinations. In The handbook of the criminology of terrorism, ed. G. Lafree and J.D. Freilich. Chichester: Wiley. Scholar
  47. Mantel, N. 1967. The detection of disease clustering and a generalized regression approach. Cancer Research 27: 209–220.Google Scholar
  48. Marchione, E., and S. Johnson. 2013. Spatial, temporal and spatio-temporal patterns of maritime piracy. Journal of Research in Crime and Delinquency 50 (4): 504–524. Scholar
  49. Medina, R., L. Siebeneck, and G. Hepner. 2011. A geographic information systems (GIS) analysis of spatiotemporal patterns of terrorist incidents in Iraq 2004–2009. Studies in Conflict & Terrorism 34 (11): 862–882. Scholar
  50. National Consortium for the Study of Terrorism and Responses to Terrorism (START). 2017a. Global Terrorism Database [gtd_13to16_0617dist.xlsx]. Retrieved from
  51. National Consortium for the Study of Terrorism and Responses to Terrorism (START). 2017b. Global Terrorism Database [Codebook]. Retrieved from
  52. Pape, R.A. 2003. The strategic logic of suicide terrorism. American Political Science Review 97 (3): 343–361. Scholar
  53. Pease, K. 1998. Repeat victimisation: Taking stock (Crime Prevention and Detection Series, Paper 90). London: Home Office.Google Scholar
  54. Phillips, P.J. 2016. The economics of terrorism. Abingdon: Routledge.CrossRefGoogle Scholar
  55. Piza, E., and J. Carter. 2017. predicting initiator and near repeat events in spatiotemporal crime patterns: An analysis of residential burglary and motor vehicle theft. Justice Quarterly. Scholar
  56. Quetelet, A. 1984. Adolphe Quetelet’s research on the propensity for crime at different ages. Cincinnati: Anderson Publishing Company.Google Scholar
  57. Rabin, M. 2013. Risk aversion and expected-utility theory: A calibration theorem. In Handbook of the fundamentals of financial decision making: Part I, 241–252. Singapore: World Scientific.Google Scholar
  58. Rapoport, D.C. 1971. Assassination & terrorism. Toronto: Canadian Broadcasting Corporation.Google Scholar
  59. Rashid, A. 2010. Taliban. New Heaven: Yale University Press.Google Scholar
  60. Ratcliffe, J.H. 2004. Geocoding crime and a first estimate of a minimum acceptable hit rate. International Journal of Geographical Information Science 18 (1): 61–72. Scholar
  61. Ratcliffe, J.H. 2009a. Near repeat calculator (Version 1.3). Philadelphia, PA/Washington, DC: Temple University/National Institute of Justice.Google Scholar
  62. Ratcliffe, J.H. 2009b. Near repeat calculator. Program Manual for Version 1.3. Philadelphia, PA/Washington, DC: Temple University/National Institute of Justice.Google Scholar
  63. Ratcliffe, J.H., and G.F. Rengert. 2008. Near-repeat patterns in Philadelphia shootings. Security Journal 21 (1–2): 58–76. Scholar
  64. Rengert, G., and J. Wasilchick. 1985. Suburban burglary: A time and a place for everything. Springfield, IL: CC Thomas.Google Scholar
  65. Rossmo, D. 2000. Geographic profiling. Washington, DC: CRC Press.Google Scholar
  66. Sandler, T., and W. Enders. 2004. An economic perspective on transnational terrorism. European Journal of Political Economy 20 (2): 301–316. Scholar
  67. Savitch, H.V. 2014. Cities in a time of terror: Space, territory, and local resilience. London: Routledge.Google Scholar
  68. Schroden, J., C. Norman, J. Meyerle, P. Asfura-Heim, B. Rosenau, D. Gilmore, et al. 2014. Independent Assessment of the Afghan National Security Forces. No. DRM-2014-U-006815-FINAL. Center for Naval Analyses. Alexandria, VA: Strategic Studies Research Department.Google Scholar
  69. Siqueira, K., and T. Sandler. 2007. Terrorist backlash, terrorism mitigation, and policy delegation. Journal of Public Economics 91 (9): 1800–1815.CrossRefGoogle Scholar
  70. Sturup, J., A. Rostami, M. Gerell, and A. Sandholm. 2017. Near-repeat shootings in contemporary Sweden 2011 to 2015. Security Journal. Scholar
  71. Thaler, R.H. 2015. Misbehaving: The making of behavioral economics. New York: WW Norton.Google Scholar
  72. The World Bank. 2017. Population growth (annual %) [API_SP.POP.GROW_DS2_en_excel_v2.xls]. Retrieved from
  73. Townsley, M., R. Homel, and J. Chaseling. 2003. Infectious burglaries. A test of the near repeat hypothesis. British Journal of Criminology 43 (3): 615–633. Scholar
  74. Townsley, M., S.D. Johnson, and J.H. Ratcliffe. 2008. Space time dynamics of insurgent activity in Iraq. Security Journal 21 (3): 139–146. Scholar
  75. Tutun, S., M.T. Khasawneh, and J. Zhuang. 2017. New framework that uses patterns and relations to understand terrorist behaviors. Expert Systems with Applications 78: 358–375.CrossRefGoogle Scholar
  76. UN News. 2016. Afghan casualties hit record high 11,000 in 2015—UN report. Accessed June 19, 2017, from
  77. Wells, W., L. Wu, and X. Ye. 2011. Patterns of near-repeat gun assaults in Houston. Journal of Research in Crime and Delinquency 49 (2): 186–212. Scholar
  78. Ye, X., X. Xu, J. Lee, X. Zhu, and L. Wu. 2015. Space–time interaction of residential burglaries in Wuhan, China. Applied Geography 60: 210–216. Scholar
  79. Zammit-Mangion, A., M. Dewar, V. Kadirkamanathan, and G. Sanguinetti. 2012. Point process modelling of the Afghan War Diary. Proceedings of the National Academy of Sciences of the United States of America 109 (31): 12414–12419. Scholar
  80. Zhang, Y., J. Zhao, L. Ren, and L. Hoover. 2015. Space-time clustering of crime events and neighborhood characteristics in Houston. Criminal Justice Review 40 (3): 340–360. Scholar
  81. Zipf, G. 1965. Human behavior and the principle of least effort: An introduction to human ecology. New York: Hafner Publishing Company.Google Scholar

Copyright information

© Springer Nature Limited 2019

Authors and Affiliations

  • Julie Haukland Rieber-Mohn
    • 1
  • Kartikeya Tripathi
    • 1
    Email author
  1. 1.Department of Security and Crime ScienceUniversity College LondonLondonUK

Personalised recommendations