Tracking of COVID 19 Symptoms by Android Mobile Application

The major goal in preventing the spread of infection was to monitor and track the symptoms of COVID 19. During the COVID 19 pandemic, mobile health app applications greatly aided the public in forecasting, preventing, diagnosing, managing, and delivering accurate regarding the COVID-19 information. The objective of this study was to use a mobile application rating system to assess the quality of various apps. The systematic search strategy was used to find suitable apps in the Google Play store for Android mobile devices. The exploration words are COVID 19, coronavirus, symptoms of CIVID 19, and tracking symptoms. Following a thorough screening, the authors exclusively reviewed ten Apps. Researchers used a mobile application rating scale based on semantic review and associated literature to assess the quality of the selected apps. The specific acute and chronic symptoms reported by WHO and CDC are tracked by each app were evaluated. Individual reviewers have evaluated the selected apps and reliability of the extracted data is assessed and the value was 0.89. Mean MARS values for each domain, total score were evaluated. There were 811 Android application apps found in the Google Play store that are possibly relevant to the current study; however, only 10 of those apps met the criteria of our study. 90% of the applications received four stars and higher, and the majority of the apps developed by government agencies and provided the reliable information about COVID 19 prevention measures. 80% of the applications require registration and lengthy details, and all apps notify users if they are in close proximity to an infected person and if new information is posted to the apps. In terms of quality, all apps have scored the above 4 the mean values. Overall, all apps were reported to be effective in maintaining their quality and obtaining excellent ratings. However, most of the apps track the short term COVID 19 clinical features , and Only a few apps focused to track the long term clinical features.