Syndromic surveillance of COVID-19 using crowdsourced data
Autor
Desjardins, Michael R.
Institución
Resumen
As of August 20, 2020, COVID-19 has caused ~22.4 million
co nfirmed cases and over 789,000 confirmed deaths, globally
[1]. However, the global case and death counts are likely much
higher due to a variety of factors, such as misdiagnoses during
the early stages of the pandemic, testing disparities, and high rates
of asymptomatic carriers (up to 50%) of the SARS-CoV-2 virus [2].
Surveillance of COVID-19 has largely relied on confirmed case and
death statistics, contact tracing, and projections via epidemiological modeling [3,4]. Furthermore, the timeliness of data availability
often suffers from reporting delays due to the incubation period,
testing lags, and others