Contact Tracing Applications Against COVID-19: A Systematic Review (Preprint)

BACKGROUND The novel coronavirus 2019 (COVID-19) pandemic has triggered public anxiety around the world. So far, the evidence suggests that prevention on a public scale is the most effective health measure for thwarting the progress of COVID-19. Another critical aspect of preventing COVID-19 is contact tracing. OBJECTIVE We aimed to investigate the effectiveness of contact tracing applications currently available in the context of the COVID-19 pandemic. METHODS We undertook a systematic review and narrative synthesis of all literature relating to contact tracing applications in the context of COVID-19. We searched 3 major scientific databases. Only articles that were published in English and were available as full-text articles were selected for review. Data were extracted and narrative syntheses conducted. RESULTS Five studies relating to COVID-19 were included in the review. Our results suggest that digitalized contact tracing methods can be beneficial for impeding the progress of COVID-19. Three key themes were generated from this systematic review. First, the critical mass of application adoption must be attained at the population level before the sensitivity and positive predictive value of the solution can be increased. Second, usability factors such as access, ease of use and the elimination of barriers are essential in driving this uptake. Third, privacy must be ensured where possible as it is the single most significant barrier against achieving critical mass. CONCLUSIONS The COVID-19 pandemic has claimed more than 2 million lives globally, with over 100 million confirmed cases. Contact tracing can rapidly identify potentially infected individuals before the emergence of severe or critical symptoms, and it can also prevent the subsequent transmission of disease from secondary cases when implemented efficiently. Contact tracing methods have proved to be beneficial for impeding the progress of COVID-19 as compared to older, more labor intensive manual methods.