Presented by Susan Mason, PhD, MPH, Associate Professor
Division of Epidemiology & Community Health

Policies necessary to mitigate the COVID-19 pandemic, such as school closures and stay-at-home orders, coupled with stark increases in unemployment, have the potential to increase risks of child abuse and neglect. However, the same challenges also restrict the systems (mandated reporting, Child Protection) that we rely on for child maltreatment surveillance. Alternative data sources are critically needed to monitor trends in child maltreatment over the pandemic. We used data from the Google Health Trends API to estimate the change in child abuse-related search volume from pre- to post- shelter-in-place (SIP) orders, using a difference-in-difference approach to compare this change for states that imposed SIP orders to those that did not, adjusting for long-term trends and seasonal variation in these searches. I will share the results of these analyses, as well as lessons learned about using Google Health Trends as a tool for epidemiologic surveillance.