Respiratory infections, including influenza and COVID-19, have substantial impacts across all areas of life on both the individual and population scale. The detection and monitoring of such diseases is critical for maintaining public health at a local, national and global level. There is a need to understand how individual behaviors and factors contribute to the development and spread of disease.
The purpose of this study is to provide near real-time ongoing surveillance data on coronavirus-like illness (CLI) and influenza-like illness (ILI) by community, county, state, region and nation (US). This will be done by collecting symptoms on a weekly basis. Further, this study hopes to identify the association between specific risk factors (demographics, household information, medical conditions, and mobility patterns) in the development of respiratory infections. This study will also assess the value of preventative measures (wearing a facemask, social distancing) on development of CLI and ILI. It will also determine how usual mobility patterns change when someone develops CLI and/or ILI. Mobility will be collected by obtaining permission to assess location on the Android device. Mobility patterns include time spent at home vs. work, number of unique places visited in a week, time spent on public transportation, and time spent running, walking, and bicycling.
On a weekly basis, participants will be asked to respond to surveys regarding the presence and severity of respiratory symptoms, self-reported coronavirus and influenza test results, and influenza vaccination status, and use of respiratory disease prevention strategies (mask and social distancing) during the previous 7 days. It is the goal of this study to understand how these individual factors contribute to the development of coronavirus-like illness and influenza-like illness.
