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1.
Journal of Theoretical and Applied Information Technology ; 100(7):2193-2206, 2022.
Article in English | Scopus | ID: covidwho-1823990

ABSTRACT

E-health is an application that focuses on community services that offer services in the health sector. Since the Covid-19 pandemic, e-health applications have experienced an increase in users. The objective of this study was to determine what factors influenced the level of acceptability of e-health applications. The findings of this study indicated the most important aspects, such as the application's success rate and improved e-health application performance. Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) was the research model used. The online questionnaires in the form of survey were distributed and addressed for the e-health application users in Jakarta, Indonesia. PLS-SEM was used for analyzing the data and it involved 190 respondents on the survey. The result showed that the 10 hypotheses proposed, there is 5 hypotheses declared significant or accepted and others declared not significant or rejected. © 2022 Little Lion Scientific.

2.
International Journal of Emerging Technology and Advanced Engineering ; 12(2):124-134, 2022.
Article in English | Scopus | ID: covidwho-1716518

ABSTRACT

Crowdfunding is a method in which the public rally together to share kindness by raising funds to help those in need. In raising funds, a crowdfunding platform is used to collect funds digitally. The trend of sourcing funds or digital donations through crowdfunding platforms increased significantly in Indonesia, mainly during the COVID-19 pandemic. Following the surge in digital donation in Indonesia, a study was conducted to determine the factors that influenced user acceptance, specifically the community as end-users of the XYZ application. Based on the UTAUT2 (Unified Theory of Acceptance and Use of Technology 2) model, this study aimed to identify the factors that influenced the acceptance of the XYZ mobile application as a crowdfunding platform. The data collection was in the form of an online questionnaire and involved respondents from Jabodetabek and outside Jabodetabek with different ages, gender, occupation, and domicile. The Partial Least Squares - Structural Equation Modeling (PLS-SEM) method, supported by SmartPLS software, analyses the research model to obtain valuable results. The results from 200 respondents show that five paths, Facilitating Conditions on Behavioral Intention, Facilitating Conditions on Use Behavior, Habit on Behavioral Intention, Habit on Use Behavior and Behavioral Intention on Use Behavior, had a significant effect. © 2022 IJETAE Publication House. All Rights Reserved.

3.
Eur J Public Health ; 32(1): 140-144, 2022 Feb 01.
Article in English | MEDLINE | ID: covidwho-1672190

ABSTRACT

BACKGROUND: As most COVID-19 transmission occurs locally, targeted measures where the likelihood of infection and hospitalization is highest may be a prudent risk management strategy. To date, in the Republic of Ireland, a regional comparison of COVID-19 cases and hospitalizations has not been completed. Here, we investigate (i) the variation in rates of confirmed infection and hospital admissions within geographical units of the Republic of Ireland and (ii) frequency of deviations in risk of infection or risk of hospitalization. METHODS: We analyzed routinely collected, publicly available data available from the National Health Protection and Surveillance Centre and Health Service Executive from nine geographical units, known as Community Health Organization areas. The observational period included 206 14-day periods (1 September 2020-15 April 2021). RESULTS: A total of 206 844 laboratory-confirmed cases and 7721 hospitalizations were reported. The national incidence of confirmed infections was 4508 [95% confidence interval (CI) 4489-4528] per 100 000 people. The risk of hospital admission among confirmed cases was 3.7% (95% CI 3.5-3.9). Across geographical units, the likelihood that rolling 14-day risk of infection or hospitalization exceeded national levels was 9-86% and 0-88%, respectively. In the most affected regions, we estimate this resulted in an excess of 15 180 infections and 1920 hospitalizations. CONCLUSIONS: Responses to future COVID-19 outbreaks should consider the risk and harm of infection posed to people living in specific regions. Given the recent surges of COVID-19 cases in Europe, every effort should be made to strengthen local surveillance and to tailor community-centred measures to control transmission.


Subject(s)
COVID-19 , Disease Outbreaks , Hospitalization , Humans , Ireland/epidemiology , SARS-CoV-2
4.
10th EAI International Conference on Context-Aware Systems and Applications, ICCASA 2021 ; 409 LNICST:1-19, 2021.
Article in English | Scopus | ID: covidwho-1653365

ABSTRACT

Healthcare supply chains are becoming increasingly complex and characterized by rapid and unpredictable changes, particularly during the Covid-19 pandemic. This unpredictability means supply chains are challenged from all levels. Patients, employees and society are all sources of uncertainty resulting with the need for supply chains to be healthier. This research explores the need for healthcare supply chains to be more adaptable and flexible. A literature informed design science approach was adopted as the methodology. We propose a systems view of an adaptive and flexible healthcare supply chain. Furthermore, we build system dynamic models to illustrate an unhealthy healthcare supply chain and a healthy healthcare supply chain. Theoretical supply chain conceptual frameworks and information systems concepts were synthesized to propose models that look to solve some of the supply chain problems arising from the Covid-19 pandemic. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

5.
Eur J Public Health ; 32(1): 140-144, 2022 Feb 01.
Article in English | MEDLINE | ID: covidwho-1413557

ABSTRACT

BACKGROUND: As most COVID-19 transmission occurs locally, targeted measures where the likelihood of infection and hospitalization is highest may be a prudent risk management strategy. To date, in the Republic of Ireland, a regional comparison of COVID-19 cases and hospitalizations has not been completed. Here, we investigate (i) the variation in rates of confirmed infection and hospital admissions within geographical units of the Republic of Ireland and (ii) frequency of deviations in risk of infection or risk of hospitalization. METHODS: We analyzed routinely collected, publicly available data available from the National Health Protection and Surveillance Centre and Health Service Executive from nine geographical units, known as Community Health Organization areas. The observational period included 206 14-day periods (1 September 2020-15 April 2021). RESULTS: A total of 206 844 laboratory-confirmed cases and 7721 hospitalizations were reported. The national incidence of confirmed infections was 4508 [95% confidence interval (CI) 4489-4528] per 100 000 people. The risk of hospital admission among confirmed cases was 3.7% (95% CI 3.5-3.9). Across geographical units, the likelihood that rolling 14-day risk of infection or hospitalization exceeded national levels was 9-86% and 0-88%, respectively. In the most affected regions, we estimate this resulted in an excess of 15 180 infections and 1920 hospitalizations. CONCLUSIONS: Responses to future COVID-19 outbreaks should consider the risk and harm of infection posed to people living in specific regions. Given the recent surges of COVID-19 cases in Europe, every effort should be made to strengthen local surveillance and to tailor community-centred measures to control transmission.


Subject(s)
COVID-19 , Disease Outbreaks , Hospitalization , Humans , Ireland/epidemiology , SARS-CoV-2
6.
54th Annual Hawaii International Conference on System Sciences, HICSS 2021 ; 2020-January:64-73, 2021.
Article in English | Scopus | ID: covidwho-1283089

ABSTRACT

Considering the economic changes of recent times, financial literacy arises as a focal point of interest. COVID-19, coupled with the culmination of other societal issues, underlines the importance of understanding sensible personal finance. Nationwide lockdown and other economic constraints put us in immobilised positions to confide in safe and accessible entertainment havens such as games. Herein lies an interesting research opportunity to progress personal wellbeing and capability despite the extant issues of recent times. The paper demonstrates the design and implementation of an evolving serious game that supports lifelong learning and decision making relating to personal finance. The example is a useful account of serious games' evolutionary potential to incrementally support users through lifelong learning. The game's holistic design incorporates autonomy, motivation, and support structures to ensure that lifelong learning and decision making is effectively managed through an evolving system. The corresponding implementation evidences the sheer potential of serious games. © 2021 IEEE Computer Society. All rights reserved.

7.
10th International Conference on the Internet of Things, IoT 2020 ; 2020.
Article in English | Scopus | ID: covidwho-901451

ABSTRACT

World Health Organisation (WHO) advises that humans must try to avoid touching their eye, nose and mouth, which is an effective way to stop the spread of viral diseases. This has become even more prominent with the widespread coronavirus (COVID-19), resulting in a global pandemic. However, we humans on average touch our face (eye, nose and mouth) 10-20 times an hour [22] [12], which is often the primary source [15] of getting infected by a variety of viral infections including seasonal Influenza, Coronavirus, Swine flu, Ebola virus, etc. Touching our face all day long is a quirk of human nature [13] and it is extremely difficult to train people to avoid touching their face. However, wearable devices and technology can help to continuously monitor our movements and trigger a timely event reminding people to avoid touching their face. In this work, we have collected a hand-to-face multi-sensor 3D motion dataset and named it COVID-away dataset. Using our dataset, we trained models that can continuously monitor human arm/hand movement using a wearable device and trigger a timely notification (e.g. vibration) to warn the device users when their hands are moved (unintentionally) towards their face. Our trained COVID-away models can be easily integrated into an app for smartwatches or fitness bands. Our evaluation shows that the Minimum Covariance Determinant (MCD) model produces the highest F1-score (0.93) using just the smartwatch's accelerometer data (39 features). Both the dataset and trained models are openly available on the Web at https://github.com/bharathsudharsan/COVID-away. © 2020 ACM.

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