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An Application of Scan Statistics in Identification and Analysis of Hotspot of Crime against Women in Rajasthan, India

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Abstract

Crime against women (CAW) is not a present-day problem but has been prevalent in the world through the ages and since the beginning of civilizations. The cases of CAW have been increasing in almost all parts of the world and India is no exception. The distribution of CAW cases has not been found uniform across the country. The evidence of heterogeneity of cases has been a concern. Rajasthan, the largest state in India, has witnessed a very high surge in CAW in recent years. Therefore, there arises a need to study and analyze the pattern of CAW to identify the areas with high intensity for prevention and control. The CAW data from the National Crime Records Bureau (NCRB) website for the period 2014 to 2021 and the population census data of 2011 are used for the analysis. The Statistical analysis software, SaTScan, is employed for hotspot (areas with a high concentration of crimes) detection. Python programming is used to compute the data’s trend or pattern through visualization and descriptive statistics. In addition, the simple exponential smoothing method is applied for predicting the CAW for the year 2021. Our work elucidates Jhalawar, Baran, Kota, Bundi, Sawai Madhopur, and Chittorgarh districts as consistently occurring hotspots of CAW in the state. A comparative study of the hotspots found is made with the result obtained from the descriptive analysis. The trend in the data explains the years 2017 and 2019 as trough and crest of CAW cases. The hotspot detected using the forecast value of 2021 appears to be the same districts as for the period 2014 to 2020. Our work concludes that the consistency and the most likely cluster of CAW are distributed distinctly. We also found that the hotspot of CAW is not by chance but has certain man-made reasons. Most of the clusters have been identified as districts sharing boundaries with adjacent states. This further implies that if sincere efforts to collaborate with the government of the adjacent states like Madhya Pradesh, Haryana, Punjab, Uttar Pradesh, and Gujarat, the incidences resulting in detrimental effects due to CAW could reduce effectively and significantly. Thus, our study may help the government, law enforcement agencies, police organizations, judiciaries, and other stakeholders to optimize their scarce resources most effectively to curb such incidents.

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Data Availability

The datasets generated and analysed during the study are freely applicable on the National Crime Records Bureau (NCRB) and Census of India Website.

Abbreviations

Abbreviations:

Description

CAW:

Crime Against Women

NCRB:

National Crime Records Bureau

SCRB:

State Crime Records Bureau

DCRB:

District Crime Records Bureau

IPC:

Indian Penal Code

SLL:

Special and Local Laws

MLC:

Most Likely cluster

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Acknowledgements

The authors are thankful to the Vellore Institute of Technology, Vellore, for providing us with the required facilities to successfully carry out this research work.

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The authors did not receive any funding for this research from any organization.

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Authors and Affiliations

  1. Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India

    Poonam K. Saravag & Rushi Kumar B.

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  1. Poonam K. Saravag
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  2. Rushi Kumar B.
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Correspondence to Rushi Kumar B..

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Saravag, P.K., B., R.K. An Application of Scan Statistics in Identification and Analysis of Hotspot of Crime against Women in Rajasthan, India. Appl. Spatial Analysis (2024). https://doi.org/10.1007/s12061-024-09572-z

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