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2.
Stud Health Technol Inform ; 283: 186-193, 2021 Sep 21.
Article in English | MEDLINE | ID: covidwho-1430675

ABSTRACT

The global COVID-19 pandemic revealed the necessity for mobile and web-based solutions for a variety of medical processes, e.g., individual risk calculation, communication of health information and contact tracing. Many such solutions are provided in form of open source software. However, there are major obstacles to the sustainable long-term continuation of such projects. As the topic of sustainability strategies is complex, a classification would be useful to help new projects to identify relevant sustainability factors. Based on a literature review a classification for long-term success of open source software was created. This paper presents a classification focusing on five unique categories: (1) structural decision, (2) revenue generation, (3) user focus, (4) openness and (5) community building. It was developed within the NUM-COMPASS project, focusing content-wise on pandemic apps and structure-wise on open-source provision. We provide some insights into the community building dimension by discussing factors that go into building sustainable communities.


Subject(s)
COVID-19 , Mobile Applications , Contact Tracing , Humans , Pandemics , SARS-CoV-2
3.
Int J Environ Res Public Health ; 18(14)2021 07 10.
Article in English | MEDLINE | ID: covidwho-1308344

ABSTRACT

Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July 2020) in eight languages and attracted 7290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures.


Subject(s)
COVID-19 , Mobile Applications , Ecological Momentary Assessment , Humans , Pandemics/prevention & control , SARS-CoV-2
4.
Stud Health Technol Inform ; 281: 1027-1028, 2021 May 27.
Article in English | MEDLINE | ID: covidwho-1247826

ABSTRACT

The COVID-19 pandemic has brought along a massive increase in app development. However, most of these apps are not using interoperable data. The COMPASS project of the German COVID-19 Research Network of University Medicine ("Netzwerk Universitätsmedizin (NUM)") tackles this issue, by offering open-source technology, best practice catalogues, and suggestions for designing interoperable pandemic health applications (https://www.netzwerk-universitaetsmedizin.de/projekte/compass). Therefore, COMPASS conceived a framework that includes automated conformity checks as well as reference implementations for more efficient and pandemic-tailored app developments. It further aims to motivate and support developers to use interoperable standards.


Subject(s)
COVID-19 , Mobile Applications , Humans , Pandemics , Reference Standards , SARS-CoV-2
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