PEAK: Policy Event Assessment of COVID-19 Cases at the Start of the Pandemic in New York City

The impact of events and associated public health announcements on COVID-19 incidence remains an interesting and open question for future response and prevention. To address this issue, we propose a policy event impact assessment framework (PEAK) that quantifies the impact of policies and events on COVID-19 incidence in this paper. PEAK uses timeseries change point detection to estimate how health policies and events affected COVID-19 incidence during the most difficult period of the pandemic experienced in New York City and uses the long short-term memory for impact analysis at each change point. We analyze 26 public announcements on COVID19 and events that occurred in New York City from March 2020 to February 2021. The results show the top 10 largest-impact change points identified by PEAK and the events that caused such impacts.