EPIDEM: A Technology-Enabled COVID-19 Elimination Strategy

2020 
Background: The novel Coronavirus disease 2019 (COVID-19) has rapidly evolved into a global emergency with far-reaching consequences. Multiple models predict mounting morbidity and mortality in the absence of appropriate interventions. Screening of sub-clinical cases through technological tools has the potential to eliminate virus containment in the population. Objective: Our aim was to develop an effective application that detected early COVID-19 infections and resulted in four-dimensional (4-D) data visualization systems to develop safe networks whilst respecting user privacy. Methods: We proposed an algorithm for a novel form of contact tracing and screening that can detect infection before manifestation of clinical symptoms and signs. We developed a simulation model that demonstrated impact on the pandemic through percent change in the “trigger point”. Results: A “trigger point” based on personal risk assessment generated a visual report to the community network. The following outcomes were rendered in the app: live surveillance of metadata, hotspot mapping, targeted live health messaging to a large population, an infection control passport technology, and personal hotspot avoidance warnings. Our model suggested that higher adoption of such strategies can potentially eliminate viral carriage in the population. Conclusions: Our proposed technology-enabled screening, detection, and elimination strategy presents a novel approach to eliminate the viral containment. This app could be applied to the COVID-19 pandemic as well as other outbreaks and epidemics in the future to control the unprecedented disease spread.
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