Defining Key Performance Indicators for the California COVID-19 Exposure Notification System (CA Notify)

Autor: Eliah Aronoff-Spencer, Camille Nebeker, Alexander T. Wenzel, Kevin Nguyen, Rachel Kunowski, Mingjia Zhu, Gary Adamos, Ravi Goyal, Sepideh Mazrouee, Aaron Reyes, Nicole May, Holly Howard, Christopher A. Longhurst, Mohsen Malekinejad
Rok vydání: 2022
Předmět:
Zdroj: Public health reports (Washington, D.C. : 1974), vol 137, iss 2_suppl
ISSN: 1468-2877
Popis: Objectives: Toward common methods for system monitoring and evaluation, we proposed a key performance indicator framework and discussed lessons learned while implementing a statewide exposure notification (EN) system in California during the COVID-19 epidemic. Materials and Methods: California deployed the Google Apple Exposure Notification framework, branded CA Notify, on December 10, 2020, to supplement traditional COVID-19 contact tracing programs. For system evaluation, we defined 6 key performance indicators: adoption, retention, sharing of unique codes, identification of potential contacts, behavior change, and impact. We aggregated and analyzed data from December 10, 2020, to July 1, 2021, in compliance with the CA Notify privacy policy. Results: We estimated CA Notify adoption at nearly 11 million smartphone activations during the study period. Among 1 654 201 CA Notify users who received a positive test result for SARS-CoV-2, 446 634 (27%) shared their unique code, leading to ENs for other CA Notify users who were in close proximity to the SARS-CoV-2–positive individual. We identified at least 122 970 CA Notify users as contacts through this process. Contact identification occurred a median of 4 days after symptom onset or specimen collection date of the user who received a positive test result for SARS-CoV-2. Practice Implications: Smartphone-based EN systems are promising new tools to supplement traditional contact tracing and public health interventions, particularly when efficient scaling is not feasible for other approaches. Methods to collect and interpret appropriate measures of system performance must be refined while maintaining trust and privacy.
Databáze: OpenAIRE