Persistent and emerging district-level hotspots of domestic violence against women in India: a spatiotemporal analysis, 2020–2024
- 1Department of Social Sciences, School of Social Sciences & Languages, Vellore Institute of Technology
- 2Department of Sociology, Faculty of Arts, University of Peradeniya
Abstract
Introduction: Domestic violence (DV) against women remains a substantial public health concern in India. However, most existing spatial analyses of crime against women examine a single crime, a single state or region, or a short study period.
Methods: This study conducted a district-level spatiotemporal analysis of recorded domestic violence against women across Indian districts between 2020 and 2024. Dowry Deaths, Abetment to Suicide, Cruelty by Husband or Relatives, Dowry Prohibition Act offenses, and Protection of Women from Domestic Violence Act cases were selected from the National Crime Records Bureau’s crime categories and integrated into a composite standardized Domestic Violence Index (DV Index). District-level population estimates were derived from Census 2011 boundaries and official population projections. Global Moran’s I and Local Getis-Ord Gi* statistics were used to assess spatial autocorrelation and identify significant hotspots for each study year. Mann–Kendall trend statistics were used to classify persistent, recurrent, and directional (new, emerging, intensifying, and diminishing) hotspot typologies.
Results: Global Moran’s I indicated statistically significant spatial autocorrelation in the DV Index in every study year (0.36–0.53, all p ≤ 0.0001), with the highest value in 2024. This indicated that spatial clustering increased overall, although not continuously, across the study period. Local analysis identified 30 districts (4.7%) as persistent hotspots and 52 (8.2%) as recurrent hotspots, concentrated mainly in a belt across northern and central India, with a smaller cluster in Telangana. Directional analysis identified 31 emerging and 38 intensifying hotspot districts. Hotspot identification was largely stable under a k -nearest-neighbors spatial weights specification and moderately stable under an alternative weighting scheme; however, the strict persistent hotspot classification did not survive false discovery rate correction.
Discussion: Because the index is based on police-recorded cases, these hotspots show where formal registration of domestic violence is concentrated, not necessarily where prevalence or unmet need is highest. Read alongside information on reporting capacity and survey-based prevalence, such maps can help prioritize protective and health-system services.
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BibTeX
@article{susmitha2026persistent,
title = {{Persistent and emerging district-level hotspots of domestic violence against women in India: a spatiotemporal analysis, 2020–2024}},
author = {K. Susmitha and J. Balamurugan and Upali Weerakoon},
journal = {Frontiers in Public Health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1994555},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1994555/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Persistent and emerging district-level hotspots of domestic violence against women in India: a spatiotemporal analysis, 2020–2024
AU - K. Susmitha
AU - J. Balamurugan
AU - Upali Weerakoon
PY - 2026
DA - 2026/10/29
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1994555
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1994555/full
AB - Introduction: Domestic violence (DV) against women remains a substantial public health concern in India. However, most existing spatial analyses of crime against women examine a single crime, a single state or region, or a short study period. Methods: This study conducted a district-level spatiotemporal analysis of recorded domestic violence against women across Indian districts between 2020 and 2024. Dowry Deaths, Abetment to Suicide, Cruelty by Husband or Relatives, Dowry Prohibition Act offenses, and Protection of Women from Domestic Violence Act cases were selected from the National Crime Records Bureau’s crime categories and integrated into a composite standardized Domestic Violence Index (DV Index). District-level population estimates were derived from Census 2011 boundaries and official population projections. Global Moran’s I and Local Getis-Ord Gi* statistics were used to assess spatial autocorrelation and identify significant hotspots for each study year. Mann–Kendall trend statistics were used to classify persistent, recurrent, and directional (new, emerging, intensifying, and diminishing) hotspot typologies. Results: Global Moran’s I indicated statistically significant spatial autocorrelation in the DV Index in every study year (0.36–0.53, all p ≤ 0.0001), with the highest value in 2024. This indicated that spatial clustering increased overall, although not continuously, across the study period. Local analysis identified 30 districts (4.7%) as persistent hotspots and 52 (8.2%) as recurrent hotspots, concentrated mainly in a belt across northern and central India, with a smaller cluster in Telangana. Directional analysis identified 31 emerging and 38 intensifying hotspot districts. Hotspot identification was largely stable under a k -nearest-neighbors spatial weights specification and moderately stable under an alternative weighting scheme; however, the strict persistent hotspot classification did not survive false discovery rate correction. Discussion: Because the index is based on police-recorded cases, these hotspots show where formal registration of domestic violence is concentrated, not necessarily where prevalence or unmet need is highest. Read alongside information on reporting capacity and survey-based prevalence, such maps can help prioritize protective and health-system services.
SN - 2296-2565
ER -