A Framework for Infectious Disease Monitoring With Automated Contact Tracing-A Case Study of COVID-19

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.

A Framework for Infectious Disease Monitoring with Automated Contact Tracing - A Case Study of COVID-19

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

Video-Observed Therapy With a Notification System for Improving the Monitoring of Tuberculosis Treatment in Thailand: Usability Study.

BACKGROUND: In Thailand, the health care system has struggled to cope with COVID-19, resulting in directly observed therapy for tuberculosis being de-emphasized. A video-observed therapy (VOT) system, or more specifically, the Thai VOT (TH VOT) system, was developed to replace directly observed therapy. According to the pilot study, the system needed notifications to improve usability and user compliance. The updated version of the TH VOT system thus enabled LINE (Line Corporation) notifications. OBJECTIVE: This study aimed to reassess users' compliance with and the usability of the updated TH VOT system. METHODS: This study was conducted in the Hat Yai and Mueang Songkhla districts in Songkhla Province, Southern Thailand, from September 18 to December 1, 2021. The system was used by not only patients with tuberculosis but also tuberculosis staff, who acted as observers in primary health care settings. Some of the observers used the simulated VOT system instead of the actual system due to the lack of participating patients in their jurisdiction. After 30 days of using the system, VOT session records were analyzed to determine the compliance of the patients and observers. The User Experience Questionnaire was administered to reassess the usability of the system and compare the ratings of the participants with the general benchmark scores of the User Experience Questionnaire. The results were summarized to reveal the degree of user compliance and usability in the following three groups: the patients, actual VOT observers, and simulated VOT observers. RESULTS: Of the 19 observers, 10 used the actual VOT system, and the remaining 9 used the simulated VOT system; there were also 10 patients with tuberculosis. The patients, actual VOT observers, and simulated VOT observers exhibited about 70%, 65%, and 50% compliance, respectively, in terms of following the standard operating procedures every day. The scores of all groups on all dimensions were well above the average scores. There was no significant difference in any of the dimensional scores among the three groups. CONCLUSIONS: The updated version of the TH VOT system was deemed usable by both the patients and the health care staff. Compliance with the use of the system was high among the patients but moderate among the observers.

Consumer-grade wearables identify changes in multiple physiological systems during COVID-19 disease progression.

Consumer-grade wearables are needed to track disease, especially in the ongoing pandemic, as they can monitor patients in real time. We show that decomposing heart rate from low-cost wearable technologies into signals from different systems can give a multidimensional description of physiological changes due to COVID-19 infection. We find that the separate physiological features of basal heart rate, heart rate response to physical activity, circadian variation in heart rate, and autocorrelation of heart rate are significantly altered and can classify symptomatic versus healthy periods. Increased heart rate and autocorrelation begin at symptom onset, while the heart rate response to activity increases soon after symptom onset and increases more in individuals exhibiting cough. Symptom onset is associated with a blunting of circadian variation in heart rate, as measured by the uncertainty in the phase estimate. This work establishes an innovative data analytic approach to monitor disease progression remotely using consumer-grade wearables.

Requirements for a Bespoke Intensive Care Unit Dashboard in Response to the COVID-19 Pandemic: Semistructured Interview Study.

BACKGROUND: Intensive care units (ICUs) around the world are in high demand due to patients with COVID-19 requiring hospitalization. As researchers at the University of Bristol, we were approached to develop a bespoke data visualization dashboard to assist two local ICUs during the pandemic that will centralize disparate data sources in the ICU to help reduce the cognitive load on busy ICU staff in the ever-evolving pandemic. OBJECTIVE: The aim of this study was to conduct interviews with ICU staff in University Hospitals Bristol and Weston National Health Service Foundation Trust to elicit requirements for a bespoke dashboard to monitor the high volume of patients, particularly during the COVID-19 pandemic. METHODS: We conducted six semistructured interviews with clinical staff to obtain an overview of their requirements for the dashboard and to ensure its ultimate suitability for end users. Interview questions aimed to understand the job roles undertaken in the ICU, potential uses of the dashboard, specific issues associated with managing COVID-19 patients, key data of interest, and any concerns about the introduction of a dashboard into the ICU. RESULTS: From our interviews, we found the following design requirements: (1) a flexible dashboard, where the functionality can be updated quickly and effectively to respond to emerging information about the management of this new disease; (2) a mobile dashboard, which allows staff to move around on wards with a dashboard, thus potentially replacing paper forms to enable detailed and consistent data entry; (3) a customizable and intuitive dashboard, where individual users would be able to customize the appearance of the dashboard to suit their role; (4) real-time data and trend analysis via informative data visualizations that help busy ICU staff to understand a patient's clinical trajectory; and (5) the ability to manage tasks and staff, tracking both staff and patient movements, handovers, and task monitoring to ensure the highest quality of care. CONCLUSIONS: The findings of this study confirm that digital solutions for ICU use would potentially reduce the cognitive load of ICU staff and reduce clinical errors at a time of notably high demand of intensive health care.

Application of the Internet of Things (IoT) to Fight the COVID-19 Pandemic

The emergence of coronavirus (COVID-19) is currently a challenge that has physical, economic, social, and pedagogical boundaries, thus gaining global attention. The emergence of new trends in technologies contributed to the commencement of the Internet of Things (IoT), which is gaining worldwide attention as well as becoming available for monitoring, diagnosing, forecasting, and preventing emerging communicable diseases. IoT in the medical organization is advantageous and has enabled appropriate control of individuals with COVID-19 by using interconnected wearable sensors and networks. IoT is an evolving area of investigation in infectious disease epidemiology. However, the augmented dangers of communicable diseases transmitted through worldwide integration and the pervasive availability of smart types of machinery, including the interrelatedness of the world, require its utilization for monitoring, averting, predicting, and managing transmittable viruses. This has helped in reducing the circulation rate in the hospital and increasing patient satisfaction. Therefore, this chapter discusses the overall applications of IoT during the COVID-19 pandemic. Also, the significant applications of IoT, challenges, and opportunities of deploying the technologies during the outbreak are presented. This can be of help to identify symptoms and provides better treatment for the outbreak. Taking into account the current situation worldwide, smart disease monitoring systems focused on IoT can be significantly advanced in an attempt to combat the next contagion. With the development of smartphones, wearable devices, and Internet access, IoT’s role will limit the spread of the pandemic by collecting and analyzing data already gathered. These technologies also help to provide an automated and efficient warning system that allows early and timely identification of COVID-19, thus reducing mortality and preventing global spread. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

COVID-19 vs media: Time series data analysis towards media and COVID-19 epidemic data

COVID-19 has presented an unprecedented event that causes great fatalities. Online news has shown potential for infectious diseases monitoring. Knowing how the volume of online news corresponds to COVID-19 epidemic data can help to better understand online news parameters to accurately predicting the disease trends. We use Indonesian online news time series data to understand the relation between daily news volume and Indonesian national case and reproduction number (Rt) of the disease. We investigate different news categories, based on the content (event and non-event news) and the sentiment (negative, neutral and positive news). We use Pearson's correlation coefficient to measure the statistical relationship between news and COVID-19. The result shows that there exist a significantly correlation (0.6370) for the negative-news towards the national case number. This correlation is slightly higher to event news number (0.6328) and significantly higher compared to the total news number (0.5228). This result indicates a finer grained classification could increase the correlation number. © 2021 ACM.

Application of Smartphone Technologies in Disease Monitoring: A Systematic Review.

Technologies play an essential role in monitoring, managing, and self-management of chronic diseases. Since chronic patients rely on life-long healthcare systems and the current COVID-19 pandemic has placed limits on hospital care, there is a need to explore disease monitoring and management technologies and examine their acceptance by chronic patients. We systematically examined the use of smartphone applications (apps) in chronic disease monitoring and management in databases, namely, Medline, Web of Science, Embase, and Proquest, published from 2010 to 2020. Results showed that app-based weight management programs had a significant effect on healthy eating and physical activity (p = 0.002), eating behaviours (p < 0.001) and dietary intake pattern (p < 0.001), decreased mean body weight (p = 0.008), mean Body Mass Index (BMI) (p = 0.002) and mean waist circumference (p < 0.001). App intervention assisted in decreasing the stress levels (paired t-test = 3.18; p < 0.05). Among cancer patients, we observed a high acceptance of technology (76%) and a moderately positive correlation between non-invasive electronic monitoring data and questionnaire (r = 0.6, p < 0.0001). We found a significant relationship between app use and standard clinical evaluation and high acceptance of the use of apps to monitor the disease. Our findings provide insights into critical issues, including technology acceptance along with regulatory guidelines to be considered when designing, developing, and deploying smartphone solutions targeted for chronic patients.

Syndromic surveillance using monthly aggregate health systems information data: methods with application to COVID-19 in Liberia.

BACKGROUND: Early detection of SARS-CoV-2 circulation is imperative to inform local public health response. However, it has been hindered by limited access to SARS-CoV-2 diagnostic tests and testing infrastructure. In regions with limited testing capacity, routinely collected health data might be leveraged to identify geographical locales experiencing higher than expected rates of COVID-19-associated symptoms for more specific testing activities. METHODS: We developed syndromic surveillance tools to analyse aggregated health facility data on COVID-19-related indicators in seven low- and middle-income countries (LMICs), including Liberia. We used time series models to estimate the expected monthly counts and 95% prediction intervals based on 4 years of previous data. Here, we detail and provide resources for our data preparation procedures, modelling approach and data visualisation tools with application to Liberia. RESULTS: To demonstrate the utility of these methods, we present syndromic surveillance results for acute respiratory infections (ARI) at health facilities in Liberia during the initial months of the COVID-19 pandemic (January through August 2020). For each month, we estimated the deviation between the expected and observed number of ARI cases for 325 health facilities and 15 counties to identify potential areas of SARS-CoV-2 circulation. CONCLUSIONS: Syndromic surveillance can be used to monitor health facility catchment areas for spikes in specific symptoms which may indicate SARS-CoV-2 circulation. The developed methods coupled with the existing infrastructure for routine health data systems can be leveraged to monitor a variety of indicators and other infectious diseases with epidemic potential.

Monitoring the spatiotemporal epidemiology of Covid-19 incidence and mortality: A small-area analysis in Germany.

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.

Emerging technologies for diagnostics and drug delivery in the fight against COVID-19 and other pandemics.

INTRODUCTION: A pandemic is the worst-case scenario in the field of infectious diseases. Innovative technologies have the potential to address the challenges associated with the manufacture of personalized drug delivery systems, biosensors, and medical devices during a pandemic. 3D-Printing, microfluidics, and Microelectromechanical systems (MEMS) can provide an important part on this fight, as are cheap, easy to be operated, capable to provide rapid detection and monitoring of a disease, and deliver medicines. AREAS COVERED: This manuscript answers the question of how these emerging technologies can save lives during a pandemic by avoiding supply chain delays and also by providing rapid diagnostics, disease monitoring, or by offering personalized treatments. The manuscript covers recent approaches in the topic with a focus in manuscripts published in the last year and by emphasising recent regulatory considerations by regulatory agencies in the manufacturing of 3DP systems or other medical devices during COVID. EXPERT OPINION: New manufacturing techniques are emerging with the ability to address the challenges associated with the development of medical devices or diagnostics, during a pandemic. Are many challenges in order to achieve this and especially in short times that are required under a pandemic attack, which will also be covered in this manuscript.