JMIR Publications

ABSTRACT

With the continued spread of COVID-19 in the United States, identifying potential outbreaks before infected individuals cross the clinical threshold is key to allowing public health officials time to ensure local health care institutions are adequately prepared. In response to this need, researchers have developed participatory surveillance technologies which allow individuals to report their symptoms (or lack thereof) daily so that their data can be extrapolated and disseminated to local health care authorities. The purpose of this paper is to inform decision making by highlighting this work and note key similarities and differences between different programs through a framework synthesis. Programs were identified through keyword internet searches and snowball sampling and screened for inclusion criteria. Six programs were included in our final framework synthesis. Commonalities in data collection were identified, specifically among demographic information (age, race, gender, etc.), and in affiliation - all were associated with universities, medical schools, or schools of public health. Dissimilarities included smoking status and suspected exposure to COVID-19. Coordination between research teams and with local and state authorities is currently lacking, presenting an opportunity for collaboration to avoid duplication of efforts and greater efficiency and efficacy. This paper does not endorse any singular program.