Author ORCID Identifier

0000-0002-3812-8590

Document Type

Article

Publication Date

2021

Publication Title

Criminology & Public Policy

Volume

20

Issue

3

First Page

573

Last Page

591

Abstract

We examine changes in help-seeking for domestic violence (DV) in seven U.S. cities during the COVID-19 pandemic. Using Bayesian structural time-series modeling with daily data to construct a synthetic counterfactual, we test whether calls to police and/or emergency hotlines varied in 2020 as people stayed home due to COVID-19. Across this sample, we estimate there were approximately 1,030 more calls to police and 1,671 more calls to emergency hotlines than would have occurred absent the pandemic.Inter-agency data analysis holds great promise for better understanding localized trends in DV in real time. Research-practitioner partnerships can help DV coordinated community response teams (CCRTs) develop accessible and sustainable dashboards to visualize data and advance community transparency. As calls for drastic changes in policing are realized, prioritization of finite resources will become critical. Data-driven decision-making using CCRTs provides an opportunity to work within resource constraints without compromising the safety of DV victims.

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