Predicting the Path of Insurgency: Data-Driven Strategies to Counter Boko Haram in Nigeria

Abstract

Background While Boko Haram insurgency’s dangers are well documented, existing research lacks methods for effective monitoring and prediction, of their activities. This study addresses this gap by analyzing data from Nigerian Security Tracker website (https://www.cfr.org/nigeria/nigeria-security-tracker/p29483) from year 2011 to 2023 and geolocated information on Boko Haram activity. Methods The research employs a mixed-methods approach. It uses descriptive statistics to understand attack trends and time series models (ARIMA/SARIMA) to forecast future attacks. Additionally, control charts identify periods of heightened insurgency. Results The findings confirm the Northeast region, as the epicenter of Boko Haram activities. The average monthly attack rate was 18 incidents, leading to 682 deaths over 12 years. 2014 and 2015 witnessed the peak of the insurgency. The forecasting models suggest a potential decrease in attack frequency in the coming years, with an average of nine attacks per month. This predicted decline might be linked to intervention efforts. Control charts reveal periods where attacks surpassed expected levels, highlighting critical moments for intensified counter-insurgency measures. These periods include July 2012-May 2014 and June 2014-August 2015, with a period of regained control. Conclusion This research provides valuable insights for stakeholders working to fight against Boko Haram’s insurgency. It offers forecasting capabilities and identifies critical periods, potentially informing targeted interventions and improving overall counter-insurgency strategies.