Perception of the Communication Campaign for @choum a Symptom Reporting App: Insights from Semi Structured Interviews.

As an attempt to identify cluster of spread of COVID, we have developed the @choum functionality enabling individuals to signal when they perceived COVID-19 symptoms. The associated communication campaign did not encounter the expected success and only a limited amount of person did download the app. As an attempt to understand the barriers of use we have recruited a sample of general population to perform semi structured interview. Interview transcripts were analyzed using thematic analysis. Results highlight 3 profiles, engaged, critics and disengaged. We observe that these 3 profiles have different perception of the communication campaign, engaged participants being much more convinced by its message whereas disengaged people lack strongly of trust. This study helped us to identify what messages must be emphasized in order to attract critic people that may be convinced to use the tool.

Detection of Spatiotemporal Clusters of COVID-19-Associated Symptoms and Prevention Using a Participatory Surveillance App: Protocol for the @choum Study.

BACKGROUND: The early detection of clusters of infectious diseases such as the SARS-CoV-2-related COVID-19 disease can promote timely testing recommendation compliance and help to prevent disease outbreaks. Prior research revealed the potential of COVID-19 participatory syndromic surveillance systems to complement traditional surveillance systems. However, most existing systems did not integrate geographic information at a local scale, which could improve the management of the SARS-CoV-2 pandemic. OBJECTIVE: The aim of this study is to detect active and emerging spatiotemporal clusters of COVID-19-associated symptoms, and to examine (a posteriori) the association between the clusters' characteristics and sociodemographic and environmental determinants. METHODS: This report presents the methodology and development of the @choum (English: "achoo") study, evaluating an epidemiological digital surveillance tool to detect and prevent clusters of individuals (target sample size, N=5000), aged 18 years or above, with COVID-19-associated symptoms living and/or working in the canton of Geneva, Switzerland. The tool is a 5-minute survey integrated into a free and secure mobile app (CoronApp-HUG). Participants are enrolled through a comprehensive communication campaign conducted throughout the 12-month data collection phase. Participants register to the tool by providing electronic informed consent and nonsensitive information (gender, age, geographically masked addresses). Symptomatic participants can then report COVID-19-associated symptoms at their onset (eg, symptoms type, test date) by tapping on the @choum button. Those who have not yet been tested are offered the possibility to be informed on their cluster status (information returned by daily automated clustering analysis). At each participation step, participants are redirected to the official COVID-19 recommendations websites. Geospatial clustering analyses are performed using the modified space-time density-based spatial clustering of applications with noise (MST-DBSCAN) algorithm. RESULTS: The study began on September 1, 2020, and will be completed on February 28, 2022. Multiple tests performed at various time points throughout the 5-month preparation phase have helped to improve the tool's user experience and the accuracy of the clustering analyses. A 1-month pilot study performed among 38 pharmacists working in 7 Geneva-based pharmacies confirmed the proper functioning of the tool. Since the tool's launch to the entire population of Geneva on February 11, 2021, data are being collected and clusters are being carefully monitored. The primary study outcomes are expected to be published in mid-2022. CONCLUSIONS: The @choum study evaluates an innovative participatory epidemiological digital surveillance tool to detect and prevent clusters of COVID-19-associated symptoms. @choum collects precise geographic information while protecting the user's privacy by using geomasking methods. By providing an evidence base to inform citizens and local authorities on areas potentially facing a high COVID-19 burden, the tool supports the targeted allocation of public health resources and promotes testing. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30444.

Maintaining the Link Between Patients and Their Families During the COVID Pandemic Using Visio: Iterative Development and Evaluation.

Access to hospitals has been dramatically restricted during the COVID 19 pandemic. As a result, the patients were unable to communicate with their families other than through virtual communication channels. A still significant number of patients, which do not have access to modern videoconference tools, were completely isolated. As a result, the University Hospitals of Geneva decided to implement a Visio conference system inside their patient app ecosystem to allow every patient to remain connected. This article presents the iterative development of the solution in order to respond to the specific timely constraint of the situations as well as its evaluation by the patients and caregivers. Two iterations of the tool have been developed. The first relied on an existing commercial platform whereas the second is a fully integrated solution in our patient app ecosystem. The very positive evaluation at the first stage by more than 300 patients, relatives and caregivers convinced us to invest additional effort to provide a fully integrated solution. The second version, evaluated by 16 patients, confirmed that the Visio reaches its objective of reducing isolation during hospitalization. This initiative is completely in line with the objective of the hospital of providing human centered care.

Managing Visitor and Patient Flow During the COVID-19 Pandemic: ExpectingU App.

Access to hospitals has been dramatically restricted during the COVID 19 pandemic. Indeed, due to the high risk of contamination by patients and by visitors, only essential visits and medical appointments have been authorized. Restricting hospital access to authorized visitors was an important logistic challenge. To deal with this challenge, our institution developed the ExpectingU app to facilitate patient authorization for medical appointments and for visitors to enter the hospital. This article analyzes different trends regarding medical appointments, visitors' invitations, support staff hired and COVID hospitalizations to demonstrate how the ExpectingU system has helped the hospital to maintain accessibility to the hospital. Results shows that our system has allowed us to maintain the hospital open for medical appointments and visits without creating bottlenecks.