A Time-Series Analysis of Daily Crime Patterns and Socio-Environmental Correlates in Jamaica

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Paul Andrew Bourne, PhD, DrPH. Nicola Brown, PhD Feliciano Thorpe, MSc.

Abstract

This study examines daily violent crime patterns in Jamaica and investigates the influence of temporal, environmental, and policy-related factors using high-frequency time-series analysis. While prior research has focused on monthly or annual crime trends, little attention has been given to intra-week fluctuations and short-term dynamics. Daily counts of homicides and shootings spanning 2010-2024 were analysed using Seasonal Autoregressive Integrated Moving Average models with exogenous regressors (SARIMAX) and Negative Binomial regression. Independent variables included day-of-week, public holidays, maximum temperature, rainfall, and policy interventions such as States of Emergency. Preliminary analyses revealed strong temporal dependence and pronounced weekend peaks, consistent with Routine Activity Theory. Environmental factors were significant: higher temperatures were positively associated with violent crime, while rainfall reduced daily incidents, supporting environmental criminology predictions. Policy interventions yielded immediate reductions in crime, though effects were partly temporary, highlighting the limits of enforcement-driven strategies for sustained suppression. Model diagnostics indicated that high-frequency time-series models accurately captured short-term volatility, seasonal patterns, and intervention effects, with robust forecasting performance. Comparative analysis with international studies suggests that Jamaica’s crime patterns share similarities with North American weekend surges but exhibit unique environmental sensitivities and policy response dynamics. These findings underscore the importance of daily-level crime monitoring for evidence-based policing and targeted intervention planning. The study contributes methodologically by demonstrating the utility of high-resolution count data and SARIMAX/Negative Binomial modelling for Caribbean crime research. Practically, results inform operational resource allocation, policy design, and community engagement strategies, advancing both theoretical understanding and applied crime management in small island developing states.

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