Novel Indicators and Analysis of New Jersey COVID-19 Data

Project Aims

This project aims to improve analytically based policy responses to public health emergencies through improved analytics applied to surveillance data. Specific research purposes including validating and utilizing novel metrics, and development of a toolkit specifically designed to inform health policy decision makers.

Significance and Alignment

Based on previous U.S. metropolitan work, this project has the potential to significantly curtail morbidity and mortality in potential future public health emergencies. This aligns with iPHD’s mission to “improve the health, safety, security, and 
wellbeing of New Jersey residents” and specifically Research Priority #4: Supporting New Jersey’s response to COVID-19 and other public health emergencies.

Research Methods

This project requests use of the NJ Communicable Disease Reporting and Surveillance System (CDRSS) Data 2020 and forward. Data will be analyzed via novel metrices established by the PI in the COVID-19 literature and machine learning techniques. The proximate outcomes of the analysis are novel, validated, statistical results characterizing the COVID-19 trajectories in New Jersey and related policy implications. The deliverables include the analytical result and, more importantly, Python code to help automate surveillancebased analysis, prediction, and forecasting that can be applied to potential future New Jersey contagions and pandemics.
 

Post-research Plans

Plans include peer-reviewed publication, presentation, and liaison with 
the iPHD program, the Rutgers Center for State Health Policy, and health policy decision 
makers to create an automated toolkit for conducting and interpreting the novel analytics