The aim of this paper is to synthesize and analyze existing evidence on virtual care technologies, wearable health monitoring sensors, and Internet of Medical Things-based smart disease surveillance systems in the diagnosis and treat- ment of COVID-19 patients. Using and replicating data from Deloitte, Ericsson ConsumerLab, GlobalWebIndex, McKinsey, PwC, Sony, and Sykes, we performed analyses and made estimates regarding artificial intelligence-based diagnostic algo- rithms in Internet of Things-supported healthcare delivery. Artificial intelligenceenabled wearable medical devices, virtualized care systems, and wireless biomedical sensing devices are pivotal in COVID-19 screening, testing, and treatment. Digital epidemiological surveillance in monitoring, detection, and prevention of COVID-19 is optimized by use of medical artificial intelligence, clinical and diagnostic decision support systems, machine learning-based real-time data sensing and processing, and smart healthcare devices and applications. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate. [ABSTRACT FROM AUTHOR]