COVID-19 Pandemic
Freezing data to increase efficiency within the COVID-19 program in Tennessee. Magdalena Dorvil-Joanem* Chaitra Subramanya Jennifer Jain Sarah Waldo Vanessa Davis Kelly Squires Jane Yackley
BACKGROUND: The COVID-19 program’s continuously increasing data needs for both public dissemination and internal usage lead to a significant surge in data processing in SAS, affecting its performance and causing low resource errors. Long processing times also negatively impacted the staff who run these codes. Therefore, program staff implemented a data freeze for the years 2020 and 2021 to reduce staff and resource burden and to preserve data integrity, with the added benefit of reproducibility.
METHODS: All reported cases of COVID-19 in Tennessee are recorded in the National Electronic Disease Surveillance System (NEDSS) Base System (NBS). Tables and linelists summarizing years 2020 and 2021 by cases, hospitalizations, deaths, and labs were frozen using SAS. Three codes were utilized to separate and later merge the large dataset. The first code froze 2020 and 2021 data for cases, deaths, hospitalizations, and labs, and exported output tables and linelists. The second exported the data from 2022-current. The third merged the frozen 2020 and 2021 data with the 2022-current data. The final exports were stored on a secure server.
RESULTS: Efficiency concerns were mitigated following the data freeze, which substantially decreased the volume of data requiring processing. The program’s completion time dropped from 2.5 hours to 1.2 hours, reducing staff time spent running codes.
CONCLUSIONS: Freezing COVID-19 data by year reduced the burden on both technical and human resources and improved the program’s efficiency.