Asian Journal of Criminology ( IF 1.778 ) Pub Date : 2021-03-12 , DOI: 10.1007/s11417-020-09341-0 Sungida Rashid 1
The COVID-19 pandemic had a substantial impact on the historical criminal trend around the world. This study explores the early impact of COVID-19 lockdown on selected crimes in Dhaka, Bangladesh. Based on open data of the total number of arrests reported by Dhaka Metropolitan Police (DMP), an uninterrupted historical time series analysis is applied to evaluate the immediate impact during and after the official stay-at-home order due to COVID-19. Auto-regressive moving average (ARIMA) modeling technique was used to compute 6-month-ahead forecasts of the expected frequency of the total number of arrests for illegal arms dealing, vehicle theft, and narcotics trafficking in the absence of the pandemic. These forecasts were compared with the observed data from April 2020 to September 2020. The results suggest that the observed numbers of total arrests for vehicle thefts and illegal arms dealing are not significantly different from their predicted values. However, the observed frequency of the total number of arrests for illegal drug trafficking shows a steep upward trend, which is 75% more than that of the expected frequencies. Estimated results are used to recognize scopes and suggestions for future research on the relationship between crimes and the pandemic.
中文翻译:
COVID-19 对孟加拉国达卡部分犯罪活动的影响
COVID-19 大流行对世界各地的历史犯罪趋势产生了重大影响。本研究探讨了 COVID-19 封锁对孟加拉国达卡选定犯罪的早期影响。根据达卡市警察局 (DMP) 报告的逮捕总数的公开数据,应用不间断的历史时间序列分析来评估官方居家期间和之后的直接影响由于 COVID-19 的订单。自回归移动平均 (ARIMA) 建模技术用于计算在没有大流行的情况下因非法武器交易、车辆盗窃和毒品贩运而被捕总数的预期频率的 6 个月前预测。将这些预测与 2020 年 4 月至 2020 年 9 月的观测数据进行了比较。结果表明,观测到的因车辆盗窃和非法武器交易而被捕的总人数与其预测值没有显着差异。然而,观察到的非法贩毒逮捕总人数的频率呈急剧上升趋势,比预期频率高出 75%。估计结果用于识别未来研究犯罪与大流行之间关系的范围和建议。