Winter Michael, Probst Thomas, Keil Thomas, Pryss Rüdiger
Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany.
Institute of Medical Data Science, University Hospital of Würzburg, Würzburg, Germany.
NPJ Digit Med. 2025 Apr 9;8(1):197. doi: 10.1038/s41746-025-01595-1.
This study explored differences in COVID-19 infections and symptoms between Android and iOS users using data from the CoronaCheck app. This cross-sectional analysis included 23,063 global users (20,753 Android and 2310 iOS) from April 2020 to February 2023. Participants reported COVID-19 symptoms and contact risks, with data analyzed to adjust for age, sex, education, and country. Android users were generally younger, more often male, had a lower educational level, and reported more symptoms on average (2.1 vs. 1.6) than iOS users. Android users also had higher suspected COVID-19 infection rates (24% vs. 11%), with an adjusted odds ratio of 2.21 (95% CI: 1.93-2.54). These findings suggest platform-based differences in COVID-19 infection rates and symptom reporting, highlighting potential biases in mobile health research. Adjusting for device operating systems may be crucial in improving the reliability of population-based health data collected through mobile platforms.
本研究利用CoronaCheck应用程序的数据,探讨了安卓和iOS用户在新冠病毒感染及症状方面的差异。这项横断面分析涵盖了2020年4月至2023年2月期间的23063名全球用户(20753名安卓用户和2310名iOS用户)。参与者报告了新冠病毒症状及接触风险,并对数据进行分析以调整年龄、性别、教育程度和国家等因素。安卓用户总体上更年轻,男性比例更高,教育水平较低,且平均报告的症状更多(2.1种 vs. 1.6种)。安卓用户的疑似新冠病毒感染率也更高(24% vs. ),调整后的优势比为2.21(95%置信区间:1.93 - 2.54)。这些发现表明,在新冠病毒感染率及症状报告方面存在基于平台的差异,凸显了移动健康研究中的潜在偏差。调整设备操作系统对于提高通过移动平台收集的基于人群的健康数据的可靠性可能至关重要。