Factors Associated with Anti-Asian Hate Incident Reporting during COVID-19 Pandemic: Comparisons between Media and Law Enforcement Data

Background and Purpose: The surge in Anti-Asian hate incidents (AAHIs) amid the COVID-19 pandemic has highlighted the pressing need to delve into the underlying contextual factors contributing to bias-motivated violence. While law enforcement agencies provide documented records of hate crime, media reports often capture incidents that are not reported as hate crime. This significant disparity between media and law enforcement data offers a valuable opportunity to explore possible biases in reporting acts of aggression or harassment particularly AAHIs. In this study, our objective is to investigate the effect of county-level contextual factors on reported AAHIs in both media and law enforcement data, aiming to explore the disparities between the two resources.

Method: The study utilized AAHI reporting data from two distinct sources between 2020 and 2021: (1) Media data on AAHIs complied by The Asian American Foundation through a web scrapping technique and (2) law enforcement data documented by the FBI Uniform Crime Reporting program. County-level data were sourced from repositories (e.g., HealthData.gov). Three dependent variables were considered: (a) The AAHI counts reported in media data and law enforcement data, and (b) the ratio of AAHI counts in the media data to those in law enforcement data. Independent variables encompassed various county-level factors including COVID-related metrics, political affiliation, healthcare accessibility, socioeconomic indicators, demographics, among others. A county-random effects model was employed, incorporating a vector of county-level variables, while controlling for year- and month-fixed effects along with their interaction.

Result: Our findings indicate that overdose mortality rates within Asian, Black, and Hispanic communities, as well as median household income and income inequality, were correlated with counts of AAHIs in both media and low enforcement records, as well as the ratio of the counts between the two resources. Conversely, COVID-19 new case rates and home ownership exhibited negative correlations with all three dependent variables. Factors positively correlated with AAHI counts reported in media data and the ratio, but not significant or with opposite effects in law enforcement data, included COVID-19 death case rates, insufficient sleep, excessive drinking, availability of free lunch, and the percentage of Asian population. Conversely, access to exercise opportunities, overdose mortality rates among Whites, and flu vaccination rates were negatively associated with AAHI counts reported in media data and the ratio. Furthermore, Democratic vote shares in presidential elections were positively correlated with AAHI counts reported in law enforcement data only, while physical distress was negatively correlated with the counts.

Conclusion:

Our research highlights key county-level factors contributing to inconsistent reporting of AAHIs across U.S. counties. By examining healthcare, socioeconomic, and demographic influences, we pave the way for social service providers to effectively support Asian Americans facing hate and discrimination. The risk and protective factors unearthed in this study should inform the strategies of local social service agencies for prevention and response. It is imperative for policymakers to leverage these insights, confronting systemic inequities to improve hate incidents reporting. Our findings are a call to action for revamping hate crime policies and strengthening support for Asian American communities.