China
Africa
Explore chapters and articles related to this topic
Machine Learning Implementations in COVID-19
Published in Chhabi Rani Panigrahi, Bibudhendu Pati, Mamata Rath, Rajkumar Buyya, Computational Modeling and Data Analysis in COVID-19 Research, 2021
Kabita Kumari, S.K. Pahuja, Sanjeev Kumar
The most crucial step for controlling coronavirus’s spread is contact tracing, as the virus spreads from one person to another through saliva and droplets (www.who.int). Contact tracing plays a vital role in the healthcare system. It will help identify and manage the people with COVID-19 and can suppress the outbreak of a pandemic throughout a population (Lalmuanawma, Hussain, and Chhakchhuak 2020). Nowadays, digital contact tracing methods are used by many countries, notably South Korea and Singapore (Wong, Leo, and Tan 2020), such as mobile data tracing, GPS (Global Positioning System), proximity tool Bluetooth, etc. These methods allow quicker processing of data than non-digital systems. The digital tracing process employs machine learning and artificial tools for the analysis of the disease. Several countries have employed ML and AI in digital tracing for infectious chronic wasting disease (Rorres et al. 2018) using centralized, decentralized, or hybrid techniques to minimize traditional, labor-intensive, and manual tracing methods. One study (Ferretti et al. 2020) highlighted the challenges and voluntariness of COVID-19 tracking apps (CTAs) that provide information about testing or advice for self-isolation from healthcare experts. A schematic diagram for COVID-19 contact tracing based on apps is shown in Figure 1.6.
Evaluating the Performance of Wearable Devices for Contact Tracing in Care Home Environments
Published in Journal of Occupational and Environmental Hygiene, 2023
Kishwer Abdul Khaliq, Catherine Noakes, Andrew H. Kemp, Carl Thompson
Digital contact tracing can be an effective way to collect data on close contacts, location, mobility of people and their health status. The study by Grekousis and Liu 2021 provided a review of the use of digital devices to interrupt the chain of infection and suggested such devices can overcome manual contact tracing regardless of technology limitations and trade-offs between privacy and effectiveness. Contact tracing using smartphone apps that exploit Bluetooth Low Energy (BLE) technology has been the subject of considerable interest during the pandemic (Parker et al. 2020; Jalabneh et al. 2021; Madoery et al. 2021), and includes analysis to estimate COVID-19 risks from BLE contact data sets (Aljohani et al. 2021). The smartphone approach can effectively record contacts with other app users and has been shown to be workable in the wider community. However, it has limited utility for care homes as residents rarely use phones and staff are often discouraged from using phones at work. Wearable BLE devices are a potentially low-cost means of digital contact tracing (Rawat et al. 2020). They consume little energy, exchange minimal data efficiently, are lightweight, small and can be worn in a variety of forms. Wearable fobs and other stand-alone devices have been suggested as being potentially beneficial for collecting data or getting alerts for older people or other vulnerable groups (Wilmink et al. 2020).