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1.
Ieee Internet of Things Journal ; 10(1):144-165, 2023.
Article in English | Web of Science | ID: covidwho-2237279

ABSTRACT

Throughout human history, deadly infectious diseases emerged occasionally. Even with the present-day advanced healthcare systems, the COVID-19 has caused more than six million deaths worldwide (as of 27 July 2022). Currently, researchers are working to develop tools for better and effective management of the pandemic. "Contact tracing " is one such tool to monitor and control the spread of the disease. However, manual contact tracing is labor-intensive and time-consuming. Therefore, manually tracking all potentially infected individuals is a great challenge, especially for an infectious disease like COVID-19. To date, many digital contact tracing applications were developed and used globally to restrain the spread of COVID-19. In this work, we perform a detailed review of the current digital contact tracing technologies. We mention some of their key limitations and propose a fully integrated system for contact tracing of infectious diseases using COVID-19 as a case study. Our system has four main modules-1) case maps;2) exposure detection;3) screening;and 4) health indicators that take multiple inputs like users' self-reported information, measurement of physiological parameters, and information of the confirmed cases from the public health, and keeps a record of contact histories using Bluetooth technology. The system can potentially evaluate the users' risk of getting infected and generate notifications to alert them about the exposure events, risk of infection, or abnormal health indicators. The system further integrates the Web-based information on confirmed COVID-19 cases and screening tools, which potentially increases the adoption rate of the system.

2.
IEEE Internet of Things Journal ; : 1-1, 2022.
Article in English | Scopus | ID: covidwho-2018948

ABSTRACT

Throughout human history, deadly infectious diseases emerged occasionally. Even with the present-day advanced healthcare systems, the COVID-19 has caused more than six million deaths worldwide (as of 27 July 2022). Currently, researchers are working to develop tools for better and effective management of the pandemic. ’Contact tracing’is one such tool to monitor and control the spread of the disease. However, manual contact tracing is labor-intensive and time-consuming. Therefore, manually tracking all potentially infected individuals is a great challenge, especially for an infectious disease like COIVD-19. To date, many digital contact tracing applications were developed and used globally to restrain the spread of COVID-19. In this work, we perform a detailed review of the current digital contact tracing technologies. We mention some of their key limitations and propose a fully integrated system for contact tracing of infectious diseases using COVID-19 as a case study. Our system has four main modules -Case Maps, Exposure Detection, Screening, and Health Indicators that takes multiple inputs like users’self-reported information, measurement of physiological parameters, and information of the confirmed cases from the public health, and keeps a record of contact histories using Bluetooth technology. The system can potentially evaluate the users’risk of getting infected and generate notifications to alert them about the exposure events, risk of infection, or abnormal health indicators. The system further integrates the web-based information on confirmed Covid-19 cases and screening tools, which potentially increases the adoption rate of the system. IEEE

3.
Spat Spatiotemporal Epidemiol ; 38: 100433, 2021 08.
Article in English | MEDLINE | ID: covidwho-1240626

ABSTRACT

Timely monitoring of incidence risks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and associated deaths at small-area level is essential to inform containment strategies. We analysed the spatiotemporal epidemiology of the SARSCoV- 2 pandemic at district level in Germany to develop a tool for disease monitoring. We used a Bayesian spatiotemporal model to estimate the district-specific risk ratios (RR) of SARS-CoV-2 incidence and the posterior probability (PP) for exceedance of RR thresholds 1, 2 or 3. Of 220 districts (55% of 401 districts) showing a RR > 1, 188 (47%) exceed the RR threshold with sufficient certainty (PP ≥ 80%) to be considered at high risk. 47 districts show very high (RR > 2, PP ≥ 80%) and 15 extremely high (RR > 3, PP ≥ 80%) risks. The spatial approach for monitoring the risk of SARS-CoV-2 provides an informative basis for local policy planning.


Subject(s)
COVID-19/epidemiology , Pandemics , SARS-CoV-2 , COVID-19/mortality , Germany/epidemiology , Humans , Incidence , Small-Area Analysis
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