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Learnings from the design and acceptance of the German COVID-19 tracing app for IS-driven crisis management: a design science research.

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TLDR
In this paper, the authors investigated the research problem of digital solutions to overcome the pandemic, more closely examining the limited effectiveness and scope of the governmental COVID-19 tracing apps.
Abstract
BACKGROUND: This article investigates the research problem of digital solutions to overcome the pandemic, more closely examining the limited effectiveness and scope of the governmental COVID-19 tracing apps, using the German COVID-19 tracing app (Corona-Warn-App) as an example. A well-designed and effective instrument in the technological toolbox is of utmost importance to overcome the pandemic. METHOD: A multi-methodological design science research approach was applied. In three development and evaluation cycles, we presented, prototyped, and tested user-centered ideas of functional and design improvement. The applied procedure contains (1) a survey featuring 1993 participants from Germany for evaluating the current app, (2) a gathering of recommendations from epidemiologists and from a focus group discussion with IT and health experts identifying relevant functional requirements, and (3) an online survey combined with testing our prototype with 53 participants to evaluate the enhanced tracing app. RESULTS: This contribution presents 14 identified issues of the German COVID-19 tracing app, six meta-requirements, and three design principles for COVID-19 tracing apps and future pandemic apps (e.g., more user involvement and transparency). Using an interactive prototype, this study presents an extended pandemic app, containing 13 potential front-end (i.e., information on the regional infection situation, education and health literacy, crowd and event notification) and six potential back-end functional requirements (i.e., ongoing modification of risk score calculation, indoor versus outdoor). In addition, a user story approach for the COVID-19 tracing app was derived from the findings, supporting a holistic development approach. CONCLUSION: Throughout this study, practical relevant findings can be directly transferred to the German and other international COVID-19 tracing applications. Moreover, we apply our findings to crisis management theory-particularly pandemic-related apps-and derive interdisciplinary learnings. It might be recommendable for the involved decision-makers and stakeholders to forego classic application management and switch to using an agile setup, which allows for a more flexible reaction to upcoming changes. It is even more important for governments to have a well-established, flexible, design-oriented process for creating and adapting technology to handle a crisis, as this pandemic will not be the last one.

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Utilization of Random Forest and Deep Learning Neural Network for Predicting Factors Affecting Perceived Usability of a COVID-19 Contact Tracing Mobile Application in Thailand “ThaiChana”

TL;DR: The findings of this study could be considered by the government to promote the usage of contact tracing applications even in other countries and deep learning neural network and random forest classifier as machine learning algorithms may be utilized for predicting factors affecting human behavior in technology or system acceptance worldwide.

Mathematical modeling and impact analysis of the use of COVID Alert SA app

TL;DR: In this paper, a modified SEIR (Susceptible-exposed-infectious-Removed) compartmental deterministic model was proposed to control the spread of the SARS-CoV-2 pandemic.
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Learning From the Past to Improve the Future

TL;DR: In this article , the authors analyze goal-congruent features as drivers for user adoption of contact tracing apps and reveal the role of value-added services in addressing heterogeneous user segments to drive user adoption.
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Design of a Reminder and Recall System in a Contact Tracing Application to Support Coronavirus Booster Vaccination

TL;DR: In this article , a reminder and recall system for the PeduliLindungi contact tracing application was designed and evaluated using the design science research (DSR) methodology with three iterations.
Journal ArticleDOI

The role of ethics in technology acceptance: analysing resistance to new health technologies on the example of a COVID-19 contact-tracing app

TL;DR: In this paper , the influence of typical acceptance predictors (perceived health threat, privacy attitudes, and technology readiness) and two new ethics-related variables (ethical optimism and perceived governmental responsibility) on resistance to a government-issued COVID-19 contact-tracing app was investigated.
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