scholarly journals An Internet of Things Approach to Contact Tracing—The BubbleBox System

Information ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 347 ◽  
Author(s):  
Andrea Polenta ◽  
Pietro Rignanese ◽  
Paolo Sernani ◽  
Nicola Falcionelli ◽  
Dagmawi Neway Mekuria ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Contact Tracing ◽  
Healthcare Sector ◽  
Prototype Implementation ◽  
Privacy Concerns ◽  
Social Distancing ◽  
Infected People ◽  
Containment Measures ◽  
Pros And Cons ◽  
National Governments

The COVID-19 pandemic exploded at the beginning of 2020, with over four million cases in five months, overwhelming the healthcare sector. Several national governments decided to adopt containment measures, such as lockdowns, social distancing, and quarantine. Among these measures, contact tracing can contribute in bringing under control the outbreak, as quickly identifying contacts to isolate suspected cases can limit the number of infected people. In this paper we present BubbleBox, a system relying on a dedicated device to perform contact tracing. BubbleBox integrates Internet of Things and software technologies into different components to achieve its goal—providing a tool to quickly react to further outbreaks, by allowing health operators to rapidly reach and test possible infected people. This paper describes the BubbleBox architecture, presents its prototype implementation, and discusses its pros and cons, also dealing with privacy concerns.

Potential of ICT in India to Cater Pandemics in Healthcare Sector with Special Reference to Covid-19

2020 ◽  
Vol 9 (2) ◽  
pp. 11-17
Author(s):  
Zafar Majeed Rather ◽  
Magray Ajaz Ahmad
Keyword(s):  
Information And Communication Technologies ◽  
Virus Disease ◽  
Close Contact ◽  
Personal Data ◽  
The Body ◽  
Contact Tracing ◽  
Healthcare Sector ◽  
Infected People ◽  
Personal Data Protection ◽  
Corona Virus

Corona virus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome Corona virus 2 (SARS-CoV-2). The disease was first identified in December 2019 in Wuhan, the capital of China’s Hubei province, and has since spread globally, resulting in the ongoing 2019–20 corona virus pandemic. As of 9 June 2020, more than 7.12 million cases have been reported across 187 countries and territories, resulting in more than 406,000 deaths. More than 3.29 million people have recovered. The virus is primarily spread between people during close contact, often via small droplets produced by coughing, sneezing, or talking. The disease has been given official name as COVID-19[1]. Since its outbreak in china, infrared thermometers were used to check the body temperature in order to identify the infected people. Countries like China and Korea started the use of different technologies to detect, track and prevent the spread of this deadly virus. Among the major technologies used are Internet of Things (IoT), Artificial Intelligence (AI) and deep learning. With the invent of 5G technologies, we are able to transfer and process huge amounts of data on a real time basis. Health experts have argued that a key tool at governments’ disposal to contain the COVID-19 outbreak, and which was not around during the 1918 Spanish Flu, is the ability to harness digital technologies to track the spread. At the same time, deployment of contact tracing apps by governments or public health authorities has added to the debate on online privacy and personal data protection. In this research paper, we discuss the potential application of different information and communication technologies (ICT) like IoT, AI and 5G that can help in (i) Monitoring (ii) surveillance (iii) detection and prevention of COVID-19 and enhancing the healthcare to make it future-ready for any such diseases like COVID-19.

scholarly journals Modelling and Simulating the Novel Coronavirus with Implications of Asymptomatic Carriers

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ghassane Benrhmach ◽  
Khalil Namir ◽  
Jamal Bouyaghroumni
Keyword(s):  
Control Strategies ◽  
World Health ◽  
Contact Tracing ◽  
Effective Control ◽  
Public Authorities ◽  
Asymptomatic Carriers ◽  
Social Distancing ◽  
Infected People ◽  
Novel Coronavirus ◽  
Health Organization

The World Health Organization declared that the total number of confirmed cases tested positive for SARS‐CoV‐2, affecting 210 countries, exceeded 3 million on 29 April 2020, with more than 207,973 deaths. In order to end the global COVID‐19 pandemic, public authorities have put in place multiple strategies like testing, contact tracing, and social distancing. Predictive mathematical models for epidemics are fundamental to understand the development of the epidemic and to plan effective control strategies. Some hosts may carry SARS‐CoV‐2 and transmit it to others, yet display no symptoms themselves. We propose applying a model (SELIAHRD) taking in consideration the number of asymptomatic infected people. The SELIAHRD model consists of eight stages: Susceptible, Exposed, Latent, Symptomatic Infected, Asymptomatic Infected, Hospitalized, Recovered, and Dead. The asymptomatic carriers contribute to the spread of disease, but go largely undetected and can therefore undermine efforts to control transmission. The simulation of possible scenarios of the implementation of social distancing shows that if we rigorously follow the social distancing rule then the healthcare system will not be overloaded.

scholarly journals A review of infectious disease surveillance to inform public health action against the novel coronavirus SARS-CoV-2

2020 ◽  
Author(s):  
David Larsen ◽  
Rachel E. Dinero ◽  
Elizabeth Asiago-Reddy ◽  
Hyatt Green ◽  
Sandra Lane ◽  
...  
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Disease Surveillance ◽  
Behavioral Interventions ◽  
Contact Tracing ◽  
Public Health Action ◽  
Infectious Disease Surveillance ◽  
Genetic Sequencing ◽  
Social Distancing ◽  
Infected People

The SARS-CoV-2 pandemic exposed the inadequacy of infectious disease surveillance throughout the US and other countries. Isolation and contact tracing to identify all infected people are key public health interventions necessary to control infectious disease outbreaks. However, these activities are dependent upon the surveillance platform to identify infections quickly. A robust surveillance platform can also reinforce community adherence to behavioral interventions such as social distancing. In situations where contact tracing is feasible, all suspected cases and contacts of confirmed cases must be tested for a SARS-CoV-2 infection and effectively isolated. At the community level wastewater surveillance can identify areas where transmission is or is not occurring, and genetic sequencing of SARS-CoV-2 can help to elucidate the intensity of transmission independent of the number of known cases and hospitalizations. State and county public health departments should improve the infectious disease surveillance platform whilst the public is practicing social distancing. These enhanced surveillance activities are necessary to contain the epidemic once the curve has been sufficiently flattened in highly burdened areas, and to prevent escalation in areas where transmission is minimal.

scholarly journals An evaluation of COVID-19 transmission control in Wenzhou using a modified SEIR model

2021 ◽  
Vol 149 ◽  
Author(s):  
Wenning Li ◽  
Jianhua Gong ◽  
Jieping Zhou ◽  
Lihui Zhang ◽  
Dongchuan Wang ◽  
...  
Keyword(s):  
Emergency Preparedness ◽  
Close Contact ◽  
Control Measures ◽  
Contact Tracing ◽  
Seir Model ◽  
Social Distancing ◽  
Infected People ◽  
Travel Restrictions ◽  
Developmental Characteristics ◽  
Novel Coronavirus

Abstract In December 2019, the first confirmed case of pneumonia caused by a novel coronavirus was reported. Coronavirus disease 2019 (COVID-19) is currently spreading around the world. The relationships among the pandemic and its associated travel restrictions, social distancing measures, contact tracing, mask-wearing habits and medical consultation efficiency have not yet been extensively assessed. Based on the epidemic data reported by the Health Commission of Wenzhou, we analysed the developmental characteristics of the epidemic and modified the Susceptible-Exposed-Infectious-Removed (SEIR) model in three discrete ways. (1) According to the implemented preventive measures, the epidemic was divided into three stages: initial, outbreak and controlled. (2) We added many factors, such as health protections, travel restrictions and social distancing, close-contact tracing and the time from symptom onset to hospitalisation (TSOH), to the model. (3) Exposed and infected people were subdivided into isolated and free-moving populations. For the parameter estimation of the model, the average TSOH and daily cured cases, deaths and imported cases can be obtained through individual data from epidemiological investigations. The changes in daily contacts are simulated using the intracity travel intensity (ICTI) from the Baidu Migration Big Data platform. The optimal values of the remaining parameters are calculated by the grid search method. With this model, we calculated the sensitivity of the control measures with regard to the prevention of the spread of the epidemic by simulating the number of infected people in various hypothetical situations. Simultaneously, through a simulation of a second epidemic, the challenges from the rebound of the epidemic were analysed, and prevention and control recommendations were made. The results show that the modified SEIR model can effectively simulate the spread of COVID-19 in Wenzhou. The policy of the lockdown of Wuhan, the launch of the first-level Public Health Emergency Preparedness measures on 23 January 2020 and the implementation of resident travel control measures on 31 January 2020 were crucial to COVID-19 control.

COVID-19: Challenges and its Technological Solutions using IoT

2021 ◽  
Vol 17 ◽  
Author(s):  
Farhana Ajaz ◽  
Mohd Naseem ◽  
Sparsh Sharma ◽  
Mohammad Shabaz ◽  
Gaurav Dhiman
Keyword(s):  
Good Health ◽  
Machine Learning Techniques ◽  
Contact Tracing ◽  
Healthcare Sector ◽  
Plasma Therapy ◽  
Vast Number ◽  
Infected People ◽  
Global Pandemic ◽  
Aerial Vehicle ◽  
The Impact

: COVID-19 is a global pandemic that has affected a vast number of countries in a short span of time. People of the whole world are susceptible to this deadly disease. To control the prevailing havoc of Coronavirus, researchers worldwide are adopting techniques like plasma therapy, proning, medicines, etc. To stop the rapid spreading of COVID-19, contact tracing is one of the important ways that can put a check on the infected people. This paper explains the various challenges people and health practitioners are facing due to COVID-19. In this paper, various ways with which the impact of COVID-19 can be controlled using IoT technology have been discussed. A six-layer architecture of IoT solutions for containing the deadly COVID-19 has been proposed. In addition to this, role of machine learning techniques for diagnosing COVID-19 have been discussed in this paper, and a quick explanation of the Unmanned aerial vehicle (UAVs) applications for contact tracing has also been specified. From the study conducted, it is quite evident that IoT solutions can be used in various ways for restricting the impact of COVID-19. Furthermore, IoT can be used in the healthcare sector to assure people's safety and good health with little healthcare costs.

Designing Better Exposure Notification Apps: The Role of Persuasive Design (Preprint)

2021 ◽  
Author(s):  
Kiemute Oyibo ◽  
Plinio Pelegrini Morita
Keyword(s):  
Public Health ◽  
Critical Mass ◽  
Contact Tracing ◽  
Key Factors ◽  
Privacy Concerns ◽  
Social Distancing ◽  
Motivational Design ◽  
The Government

UNSTRUCTURED Digital contact tracing apps have been deployed worldwide to limit the spread of COVID-19 during this pandemic and to facilitate the lifting of public health restrictions. However, the apps are yet to be widely adopted and require a critical mass of users to be successful. Privacy concerns aside, the minimalist and non-motivational design of the contact tracing apps have been identified as key factors that contribute to low uptake. Using the Government of Canada’s exposure notification app, COVID Alert, as a case study, we demonstrated how incorporating persuasive features in contract tracing apps may improve uptake, usage, reporting diagnosis, and compliance with social distancing guidelines.

Embedding Isolation, Contact Tracing, and Quarantine in Transmission Dynamics of the Coronavirus Epidemic—A Case Study of COVID-19 in Wuhan

2021 ◽  
Author(s):  
Miao Yu ◽  
Zhongsheng Hua
Keyword(s):  
Close Contact ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Social Distancing ◽  
Infected People ◽  
Epidemic Curve ◽  
Specific Effects ◽  
Lag Effect ◽  
Novel Coronavirus

Coronaviruses have caused multiple global pandemics. As an emerging epidemic, the coronavirus disease relies on nonpharmacological interventions to control its spread. However, the specific effects of these interventions are unknown. To evaluate their effects, we extend the susceptible–latent–infectious–recovered model to include suspected cases, confirmed cases, and their contacts and to embed isolation, close contact tracing, and quarantine into transmission dynamics. The model simplifies the population into two parts: the undiscovered part (where the virus spreads freely—the extent of freedom is determined by the strength of social distancing policy) and the discovered part (where the cases are incompletely isolated or quarantined). Through the isolation of the index case (suspected or confirmed case) and the subsequent tracing and quarantine of its close contacts, the infections flow from the undiscovered part to the discovered part. In our case study, multisource data of the novel coronavirus SARS-CoV-2 (COVID-19) in Wuhan were collected to validate the model, the parameters were calibrated based on the prediction of the actual number of infections, and then the time-varying effective reproduction number was obtained to measure the transmissibility of COVID-19 in Wuhan, revealing the timeliness and lag effect of the nonpharmacological interventions adopted there. Finally, we simulated the situation in the absence of a strict social distancing policy. Results show that the current efforts of isolation, close contact tracing, and quarantine can take the epidemic curve to the turning point, but the epidemic could be far from over; there were still 4,035 infected people, and 1,584 latent people in the undiscovered part on March 11, 2020, when the epidemic was actually over with a strict social distancing policy.

Weight-Loss Program Assistance System for Obesity Patients Based on Internet of Things (IoT) Technology

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
I Gusti Bagus Astawa ◽  
I Ketut Agung Enriko
Keyword(s):  
Weight Loss ◽  
Internet Of Things ◽  
Mobile Application ◽  
Human Life ◽  
Weight Loss Program ◽  
Internet Technology ◽  
Healthcare Sector ◽  
Home Automation ◽  
Index Terms ◽  
Use Of Internet

These days, the use of Internet technology can be found in almost every sector of human life. One of the advanced Internet technologies is Internet of Things (IoT), that is a technology where devices can communicate via Internet connectivity. It is used in many vital industries like automotive, electricity, home automation, and healthcare. This study aims to implement IoT technology for healthcare sector, i.e. in helping obesity people to pursue their weight-loss program (WLP). The result is a system which consists of a smart weight scale, a mobile application, and food menu recommendation database in order to help obesity people in their WLP program. A trial to some obesity patients is performed to collect data. Index Terms—Internet of things; overweight; weight loss program; food recommendation

Multi-Disciplinary Opinions Focused on Healthcare Sector for Global Pandemic: COVID-19 (Preprint)

2020 ◽  
Author(s):  
Vinod Kumar Verma
Keyword(s):  
Internet Of Things ◽  
Research Community ◽  
Security And Privacy ◽  
Healthcare Sector ◽  
The Internet ◽  
Thought Process ◽  
Related Information ◽  
Global Pandemic ◽  
The People ◽  
The Internet Of Things

BACKGROUND COVID- 19 pandemics has affected the life of every human being in this world dramatically. The daily routine of the human has been changed to an uncertain extent. Some of the people are affected by the COVID-19, and some of the people are in fear of this epidemic. This has completely changed the thorough process of the people, and now, they are looking for solutions of this pandemic at different levels of the human addressable areas. These areas include medicine, vaccination, precautions, psychology, technology-assisted solutions like information technology, etc. There is a need to think in the direction of technology compliant solutions in the era of COVID-19 pandemic. OBJECTIVE The objective of this paper is to discuss the existing views and focus on the recommendations for the enhancement in the current situation from COVID-19. METHODS Based on the literature, perceptions, challenges, and viewpoints, the following opinions are suggested to the research community for the prevention and elimination of global pandemic COVID-19. The research community irrespective of the discipline focus on the following: 1. The comprehensive thought process for the designing of the internet of things (IoT) based solutions for healthcare applications used in the prevention from COVID-19. 2. Strategies for restricting outbreak of COVID-19 with the emerging trends in Ehealthcare applications. Which should be the optimal strategy to deal with a global pandemic? 3. Explorations on the data analysis as derived from the advanced data mining and warehousing associated with IoT. Besides, cloud-based technologies can be incorporated for the global spread of healthcare-related information to serve the community of different countries in the world. 4. The most adaptable method and technology can be deployed for the development of innovative solutions for COVID-19 related people like smart, patient-centric healthcare information systems. 5. Implementation of smart solutions like wearable technology for mask and PPE along with their disposal can be considered to deal with a global epidemic like COVID-19. This will lead to the manufacturing and incorporation of wearable technologies in the healthcare sector by industries. 6. A Pervasive thought process can be standardized for dealing with global pandemic like COVID-19. In addition, research measures should be considered for the security and privacy challenges of IoT services carrying healthcare-related information. These areas and directions are diverse but, in parallel, the need for healthy bonding and correlation between the people like researchers and scientists irrespective of their discipline. The discipline may vary from medical, engineering, computing, finance, and management, etc. In addition, standard protocols and interoperability measures can be worked out for the exchange of information in the global pandemic situations. RESULTS Recommendations Discussed CONCLUSIONS In this paper, the opinions have been discussed in the multi-disciplinary areas of research like COVID-19 challenges, medicines and vaccines, precautionary measures, technology assistance, and the Internet of Things. These opinions and discussion serve as an integrated platform for researchers and scientists to think about future perspectives to deal with healthcare-related COVID-19 pandemic situation. This includes the original, significant, and visionary automation based ideas, innovations, scientific designs, and applications focusing on Inter-disciplinary technology compliant solutions like IoT, vaccinations, manufacturing, preventive measures, etc. for the improvement of efficiency and reliability of existing healthcare systems. For the future, there is dire need to strengthen the technology not only in the one area but also for the interdisciplinary areas to recover from the pandemic situation rapidly and serve the community.

Are social networking platforms the key to effective social distancing for COVID-19? (Preprint)

2020 ◽  
Author(s):  
Viknesh Sounderajah ◽  
Hutan Ashrafian ◽  
Sheraz Markar ◽  
Ara Darzi
Keyword(s):  
Operating System ◽  
Social Networking ◽  
Contact Tracing ◽  
Text Data ◽  
Social Distancing ◽  
Web Mapping ◽  
Viral Spread ◽  
Behavioural Insights ◽  
Mapping Software ◽  
Incidence And Mortality

UNSTRUCTURED If health systems are to effectively employ social distancing measures to in response to further COVID-19 peaks, they must adopt new behavioural metrics that can supplement traditional downstream measures, such as incidence and mortality. Access to mobile digital innovations may dynamically quantify compliance to social distancing (e.g. web mapping software) as well as establish personalised real-time contact tracing of viral spread (e.g. mobile operating system infrastructure through Google-Apple partnership). In particular, text data from social networking platforms can be mined for unique behavioural insights, such as symptom tracking and perception monitoring. Platforms, such as Twitter, have shown significant promise in tracking communicable pandemics. As such, it is critical that social networking companies collaborate with each other in order to (1) enrich the data that is available for analysis, (2) promote the creation of open access datasets for researchers and (3) cultivate relationships with governments in order to affect positive change.

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