@article{10.37349/edht.2024.00008,
abstract = {Aim: After the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic and the realization of mass vaccination against the virus, the availability of a reliable, rapid, and easy-to-use system for registering the individual anti-S1 antibody titer could facilitate the personalized assessment of the need for booster vaccine doses and the reduction of social distancing and other measures. Methods: The biosensor system is based on immobilized engineered SK-N-SH neuroblastoma cells, bearing the S1 protein, and it can detect immunoglobulin G (IgG) antibodies against the SARS-CoV-2 S1 spike antigen. A disposable electrode strip bearing the engineered mammalian cells is connected to a customized read-out potentiometric device with real-time data transmission to a wireless fidelity (WiFi)-connected smartphone. Blood samples from past-infected individuals and individuals vaccinated against SARS-CoV-2 were used for validation. Results: In the present study, a smartphone application (app), capable of analyzing data regarding the levels of anti-S1 antibodies in blood is introduced. The app works in conjunction with a portable, ultra-rapid, and sensitive biosensor transmitting real-time measurements to the smartphone. Both historical and current individual data can be encoded by using the app, resulting in a widely accepted quick response (QR) code, which can then be constantly updated to match a person's status. Conclusions: This novel system could be utilized for the eventual development of a coronavirus disease 2019 (COVID-19) electronic passport, which could be further employed to improve the population-wide, cross-country surveillance of vaccination efficiency, as well as facilitate the implementation of cross-border digital health services in a user-friendly and secure way.},
author = {Apostolakis, Apostolos and Barmpakos, Dimitris and Mavrikou, Sofia and Papaionannou, George Marios and Tsekouras, Vasileios and Hatziagapiou, Kyriaki and Koniari, Eleni and Tritzali, Maroula and Michos, Athanasios and Chrousos, George P. and Kanaka-Gantenbein, Christina and Kaltsas, Grigoris and Kintzios, Spyridon},
doi = {10.37349/edht.2024.00008},
journal = {Exploration of Digital Health Technologies},
pages = {20--29},
title = {{System for classifying antibody concentration against severe acute respiratory syndrome coronavirus 2 S1 spike antigen with automatic quick response generation for integration with health passports}},
url = {https://www.explorationpub.com/Journals/edht/Article/10118},
volume = {2},
year = {2024},
number = {1}
}