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Corona-warn-app: tracing the start of the official COVID-19 exposure notification app for germany
... There exist various design patterns of FL [15,22,25,29]. A typical FL goal for a nonconvex neural network optimization, as demonstrated [30], is to minimize a global loss function f of the weighted average of each participating edge device's losses (Equation (1)). ...
... The model is evaluated, for instance, at the model orchestrator instance/node, until a higher-performing model is achieved, which also meets the defined model utility requirement-performance, speed, accuracy, etc. A model orchestrator could drop participants during training based on pre-defined criteria (e.g., data quality, computational power, or model performance at the edge [30]) to reduce communication latency and increase security and model quality. However, such criteria could affect the model's personalization/generalization and performance and yield privacy issues due to access to users' device computational resources. ...
... instance, at the model orchestrator instance/node, until a higher-performing model is achieved, which also meets the defined model utility requirement-performance, speed, accuracy, etc. A model orchestrator could drop participants during training based on predefined criteria (e.g., data quality, computational power, or model performance at the edge [30]) to reduce communication latency and increase security and model quality. However, such criteria could affect the model's personalization/generalization and performance and yield privacy issues due to access to users' device computational resources. ...
Patient-centered health care information systems (PHSs) on peer-to-peer (P2P) networks (e.g., decentralized personal health records) enable storing data locally at the edge to enhance data sovereignty and resilience to single points of failure. Nonetheless, these systems raise concerns on trust and adoption in medical workflow due to non-alignment to current health care processes and stakeholders’ needs. The distributed nature of the data makes it more challenging to train and deploy machine learning models (using traditional methods) at the edge, for instance, for disease prediction. Federated learning (FL) has been proposed as a possible solution to these limitations. However, the P2P PHS architecture challenges current FL solutions because they use centralized engines (or random entities that could pose privacy concerns) for model update aggregation. Consequently, we propose a novel conceptual FL framework, CareNetFL, that is suitable for P2P PHS multi-tier and hybrid architecture and leverages existing trust structures in health care systems to ensure scalability, trust, and security. Entrusted parties (practitioners’ nodes) are used in CareNetFL to aggregate local model updates in the network hierarchy for their patients instead of random entities that could actively become malicious. Involving practitioners in their patients’ FL model training increases trust and eases access to medical data. The proposed concepts mitigate communication latency and improve FL performance through patient–practitioner clustering, reducing skewed and imbalanced data distributions and system heterogeneity challenges of FL at the edge. The framework also ensures end-to-end security and accountability through leveraging identity-based systems and privacy-preserving techniques that only guarantee security during training.
... There are several studies on the technicalities of COVID-19 apps (mainly contact-tracing apps), either focusing on a single app or on comparing multiple to each other. Reelfs et al. (2020) present and analyze the basic concepts of the German Corona-Warn-App. The authors focus on the app's hosting infrastructure and its generated traffic, especially during local COVID-19 outbreaks. ...
The COVID-19 virus has caused a global pandemic that has heavily impacted daily life. Rapid advances in testing and vaccinating led to an additional use case besides the well-known contact-tracing apps: certificate-verification systems. Verification systems are often commissioned by local authorities to enable more public life, and are often developed by smaller organizations or startups. So, the development of verification systems differs from other software projects, featuring interesting and unique properties. In this article, we present an experience report on the development of one verification system by a German startup, focusing on three properties: working in a pandemic, developing a product for handling a pandemic, and the startup context. To this end, we surveyed nine startup developers and analyzed the results with two experts from the startup. We found that the developers focused on fast delivery to cope with the time pressure of releasing the verification system, which is why some phases of typical development processes were hardly carried out. As a result, while the verification system is successful, we also identified negative effects of the properties (e.g., programming mistakes, well-being). We discuss our findings to guide researchers and practitioners in preparing for software engineering in future emergencies.
... This in turn, results in significant negative socio-economic impacts with political disruption and ramifications [40]- [42]. Evidence suggests that the likelihood of repeat pandemic has increased in the past century [14], [43], [44]. These have been attributed to the increased (im)migration [45], global integration [46], urbanization [47], technological advances [48]- [50], land-use changes [51]- [53], and exploitation of natural environment vis-à-vis its resources [54]- [56]. ...
As competitive market and globalization continue to ripple a range of issues across the asset chain (i.e. safety, quality, tracing, and overall management efficiency). Pandemics are bound to occur without warning and has revealed the unpreparedness of many nations. Thus, the Nigerian Government aiming to shore up revenue/monetization via customs exercise duties to augment the nosedive in revenue of the oil sector-must formulate policies and adapt technology to harness its inherent benefits therein. Study advances a sensor-based blockchain NiCuSBlockIoT, which will provision a decision-support scheme for cargo goods traceability and asset movement on a value-chain by first ensuring that accurate records of cargo goods are registered, tagged and reported using the sensor-based units. These are then broadcasted on to the NiCuSBlockIoT as record and/or blocks via a P2P chain on the network as a decentralized framework executed on a distributed hyper-ledger fabric via smart-contract transaction logic. Result show model eliminate fraud that often accompanies a centralized scheme via its sensor-layered model that reports all such errors as data on NiCuSBlockIoT supply value chain.
... More research has focused on analyzing different tracing apps from a technical or ethical point of view (Garousi and Cutting, 2021;Morley et al., 2020;Sun et al., 2021;Ahmed et al., 2020;Abuhammad et al., 2020;Gupta et al., 2021;Erikson, 2021;Liang, 2020). In this context, the study of Reelfs et al. (2020) is the closest one to our own, since the authors study the Corona-Warn-App Germany. Still, none of these works provides detailed insights into the actual development processes, good practices, or challenges. ...
... These devices are used in industrial areas for maintaining social distancing between workers (Reelfs, Hohlfeld & Poese, 2020). As it is wearable and can be placed on the hat or the body of the worker, it produces sound upon closing a worker with another worker and allows workers in putting more focus on work rather than being worried about another colleague. ...
The COVID-19 pandemic caused millions of infections and deaths globally requiring effective solutions to fight the pandemic. The Internet of Things (IoT) provides data transmission without human intervention and thus mitigates infection chances. A road map is discussed in this study regarding the role of IoT applications to combat COVID-19. In addition, a real-time solution is provided to identify and monitor COVID-19 patients. The proposed framework comprises data collection using IoT-based devices, a health or quarantine center, a data warehouse for artificial intelligence (AI)-based analysis, and healthcare professionals to provide treatment. The efficacy of several machine learning models is also analyzed for the prediction of the severity level of COVID-19 patients using real-time IoT data and a dataset named ‘COVID Symptoms Checker’. The proposed ensemble model combines random forest and extra tree classifiers using a soft voting criterion and achieves superior results with a 0.922 accuracy score. The use of IoT applications is found to support medical professionals in investigating the features of the contagious disease and support managing the COVID pandemic more efficiently.
... Similar to the Belgium application, Coronalert, the German application was intended to disturb the infection chains using Bluetooth to notify users if they came less than 1.5 m from each other for a period of 10 minutes or more. In addition, it allowed users to know if they were in contact with an infected individual in the past 14 days, providing the estimated time and distance of exposure [10]. ...
Background
Contact tracing applications were introduced during the COVID-19 pandemic to mitigate the spread of the infection in several countries. In Saudi Arabia, the Tawakkalna application was developed. The Tawakkalna application is a mobile health solution aimed to track infection cases, save lives, and reduce the burden on health facilities. This study aims to explore the public’s attitude to and acceptance levels of the Tawakkalna application and to evaluate its effectiveness regarding privacy and security. The main objective of this study is to investigate the user acceptability of contact tracing applications and explore the safety and privacy effectiveness of the COVID-19 contact tracing application, the Tawakkalna application. In addition, the study analyzes factors associated with acceptance levels and compares the results obtained to similar studies in other countries using similar applications.
Methodology
This study used a valid and reliable online survey that was used in similar studies conducted in other countries to assess the acceptability of the application. The survey was conducted from September to November 2021, and the final dataset included 205 participants. To investigate the privacy and security performance of the Tawakkalna application, we followed the investigation method used by similar research that investigated 28 contact tracing applications across Europe.
Results
Out of the 205 participants, 84.87% were in favor of the opt-in voluntary installation of the Tawakkalna application, and 49.75% of the participants were in favor of the opt-out automatic installation. Individuals’ trust in the government had a huge impact on acceptance, with 60.98% of the participants supporting the application because they believed that the Tawakkalna application would help them stay healthy during the COVID-19 pandemic. Overall, 49% of the participants supporting the application also agreed to the de-identification of their collected data and providing it for research. The Tawakkalna application ranked at the top compared to other contact tracing applications regarding privacy and security.
Conclusions
The Tawakkalna application developed by the Saudi Data and Artificial Intelligence Authority was a response to the COVID-19 pandemic, which is considered the biggest public health crisis in recent times. The Saudi Arabian government gained the population’s acceptance through effective endorsement and the spread of educational content through media channels. By complying with privacy policies, the Tawakkalna application is an effective tool to combat public health infectious diseases.
... In an effort to trace coronavirus infection chains, Germany launched an open-source smartphone contact tracing app ("Corona-Warn-App") in June 2020. The Corona-Warn-App (CWA) informs users who were exposed to a person later tested positive on the basis of Exposure Notification APIs [2]. The CWA works independently and, in particular, does not rely on the health offices, which has the advantage that it can warn people even if the health offices are overloaded. ...
The World Health Organization declared the emergence of the novel coronavirus (SARS-CoV-2) in January 2020. To trace infection chains, Germany launched its smartphone contact tracing app, the “Corona-Warn-App” (CWA), in June 2020. In order to be successful as a tool for fighting the pandemic, a high adoption rate is required in the population. We analyse the respective factors influencing app adoption based on the health belief model (HBM) with a cross-sectional online study including 1752 participants from Germany. The study was conducted with a certified panel provider from the end of December 2020 to January 2021. This model is primarily known from evaluations of medical treatments, such as breast cancer screenings, but it was rarely applied in prior work for a health-related information system such as the CWA. Our results indicate that intrinsic and extrinsic motivation to use the CWA are the strongest drivers of app use. In contrast, technical barriers, privacy concerns and lower income are the main inhibitors. Our findings contribute to the literature on the adoption of contact tracing apps by questioning actual users and non-users of the CWA, and we provide valuable insights for policymakers regarding influences of adoption and potential user groups of disease prevention technologies in times of pandemics.
... Reducing and controlling human movement has been of the utmost importance in containing the pandemic spread and to track infections. To this end, many applications have been developed to monitor and establish contact tracing systems (e.g., Corona-Warn-App, Immuni and Radar COVID are examples respectively adopted by Germany [5], Italy and Spain) [4]. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. ...
As a response to the global outbreak of the SARS-COVID-19 pandemic, authorities have enforced a number of measures including social distancing, travel restrictions that lead to the "temporary" closure of activities stemming from public services, schools, industry to local businesses. In this poster we draw the attention to the impact of such measures on urban environments and activities. For this, we use crowdsensed information available from datasets like Google Popular Times and Apple Maps to shed light on the changes undergone during the outbreak and the recovery.
... The Corona-Warn-App in Germany's was monitored nation-wide adoption starting on day 1. Measured interest in the CWA was obtained by monitoring the CWA app, which provided aggregated perspectives on the app's general interest without compromising users' privacy by utilizing NetFlow traces captured directly at its hosting infrastructure [4]. The TraceTogether and COVIDSafe apps were studied in terms of their nature of work and the number of times they were downloaded in addition to studying all the reasons that might cause the app to fail [3]. ...
The impact of the COVID-19 pandemic has led to the use of M-Health apps for tracking COVID-19 infected people.So, the aim of this study was to develop a model that explains the adoption of M-Health apps for tracking COVID-19 infected people in developing countries. We tested the model based on data collected using an online survey with 283 participants. For data analysis , the partial least squares technique was used. The results revealed that the intention to use the Aman application was positively influenced by performance expectancy, social influence, Aman application quality, perceived self-efficacy, facilitating conditions, and perceived credibility. Moreover, it was negatively influenced by the perceived financial cost and the effort expectancy. M-Health apps are found as an approach to fighting COVID-19. Therefore, it is imperative to address the reasons that prevent the use of these apps. The implications of this are discussed.
... In this context, due to the ever-increasing availability of digital information, leveraging crisis information systems (CIS) has been identified as a promising tool to manage, respond, and counteract those public health crises (Pan et al., 2012;Thomas et al., 2020). in particular demonstrated that location data and the associated surveillance of citizens with the help of mobile apps have become successful means of tackling the ongoing crisis (Trang et al., 2020). However, as the pandemic progressed, a potential mismanagement emerged that prompted several questions: the crisis of COVID-19 began in 2019 (New York Times, 2021), a governmentbased app was released 7 month later (Reelfs et al., 2020), leading to a 1-year delay before contacttracing gained any real traction among the population (Grill et al., 2021;Simon and Rieder, 2021;Statista, 2021). A period which has led to a surge in disease cases and deaths (AJMC, 2021;MHB, 2021). ...
COVID-19 served to teach governments many painful lessons about their pitfalls and challenges in managing public health crises. Although both practitioners and academics have been aware that crisis information systems (CIS) constitute a valuable tool for crisis prevention and management, their implementation to counteract COVID-19 lagged by months. To analyze this crisis management mismatch, in this paper, we examine and identify the structural challenges and shortcomings of government-initiated crisis management through CIS. This paper analyzes two CIS projects tackling the COVID-19 crisis, funded by the German government. Drawing on a complexity-lens and the NASSS-framework, key shortcomings are identified. We derive propositions for future CIS projects to enable crisis preparedness. Our outcomes suggest that adopting a complexity perspective in planning, initiating, and developing governmental CIS provides a promising avenue for achieving successful crisis management. We contribute to literature by highlighting the suitability of the complexity-lens in health crises.
Recommended Citation:
Diesterhöft, Till Ole; Thole, Daniel Christian; Aslan, Aycan; and Vogel, Stefan, "Nobody Said IT Was Easy -
Managing Government-Initiated Information Systems in Addressing and Preparing for Health Crises"
(2022). ECIS 2022 Research Papers. 133.
https://aisel.aisnet.org/ecis2022_rp/133
... Mobile CrowdSensing (MCS) has become a popular paradigm to perform sensing campaigns using sensors embedded in mobile devices like smartphones . To combat the epidemic, many applications have been developed to monitor and establish contact tracing systems (Kendall et al., 2020;Reelfs et al., 2020;Whitelaw et al., 2020). Corona-Warn-App, Immuni, and Radar COVID are examples respectively adopted by Germany, Italy, and Spain, and subscribers of the latter helped identify that loss of smell and taste could indicate the presence of the infection (Menni et al., 2020). ...
The global outbreak of the SARS-COVID-19 pandemic has changed our lives, driving an unprecedented transformation of our habits. In response, the authorities have enforced several measures, including social distancing and travel restrictions that lead to the temporary closure of activities centered around schools, companies, local businesses to those pertaining to the recreation category. As such, with a mobility reduction, the life of our cities during the outbreak changed significantly. In this paper, we aim at drawing attention to this problem and perform an analysis for multiple cities through crowdsensed information available from datasets such as Apple Maps, to shed light on the changes undergone during both the outbreak and the recovery. Specifically, we exploit data characterizing many mobility modes like driving, walking, and transit. With the use of Gaussian Processes and clustering techniques, we uncover patterns of similarity between the major European cities. Further, we perform a prediction analysis that permits forecasting the trend of the recovery process and exposes the deviation of each city from the trend of the cluster. Our results unveil that clusters are not typically formed by cities with geographical ties, but rather on the spread of the infection, lockdown measures, and citizens’ reactions.
... Reducing and controlling human movement has been of the utmost importance in containing the pandemic spread and to track infections. To this end, many applications have been developed to enforce contact tracing systems (e.g., Corona-Warn-App, Immuni and Radar COVID are examples respectively adopted by Germany [5], Italy and Spain) [4]. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. ...
As a response to the global outbreak of the SARS-COVID-19 pandemic, authorities have enforced a number of measures including social distancing, travel restrictions that lead to the "temporary" closure of activities stemming from public services, schools, industry to local businesses. In this poster we draw the attention to the impact of such measures on urban environments and activities. For this, we use crowdsensed information available from datasets like Google Popular Times and Apple Maps to shed light on the changes undergone during the outbreak and the recovery.
The COVID-19 Pandemic has punched a devastating blow on the majority of the world’s population. Millions of people have been infected while hundreds of thousands have died of the disease throwing many families into mourning and other psychological torments. It has also crippled the economy of many countries of the world leading to job losses, high inflation, and dwindling Gross Domestic Product (GDP). The duo of social distancing and contact tracing are the major technological-based non-pharmaceutical public health intervention strategies adopted for combating the dreaded disease. These technologies have been deployed by different countries around the world to achieve effective and efficient means of maintaining appropriate distance and tracking the transmission pattern of the diseases or identifying those at high risk of infecting others. This paper aims to synthesize the research efforts on contact tracing and social distancing to minimize the spread of COVID-19. The paper critically and comprehensively reviews contact tracing technologies, protocols, and mobile applications (apps) that were recently developed and deployed against the coronavirus disease. Furthermore, the paper discusses social distancing technologies, appropriate methods to maintain distances, regulations, isolation/quarantine, and interaction strategies. In addition, the paper highlights different security/privacy vulnerabilities identified in contact tracing and social distancing technologies and solutions against these vulnerabilities. We also x-rayed the strengths and weaknesses of the various technologies concerning their application in contact tracing and social distancing. Finally, the paper proposed insightful recommendations and open research directions in contact tracing and social distancing that could assist researchers, developers, and governments in implementing new technological methods to combat the menace of COVID-19.
Digital contact tracing apps have been introduced globally as an instrument to contain the COVID-19 pandemic. Yet, privacy by design impedes both the evaluation of these tools and the deployment of evidence-based interventions to stimulate uptake. We combine an online panel survey with mobile tracking data to measure the actual usage of Germany’s official contact tracing app and reveal higher uptake rates among respondents with an increased risk of severe illness, but lower rates among those with a heightened risk of exposure to COVID-19. Using a randomized intervention, we show that informative and motivational video messages have very limited effect on uptake. However, findings from a second intervention suggest that even small monetary incentives can strongly increase uptake and help make digital contact tracing a more effective tool. Combining mobile tracking data and a survey experiment, Munzert et al. show that Germany’s contact tracing app is underused by those who socially distance less; however, even small cash incentives increased app uptake in the cohort.
Background:
In the global outbreak of coronavirus disease 2019 (COVID-19), new digital solutions have been developed for infection control. In particular, contact tracing mobile applications provide a means for governments to manage both health and economic concerns. However, public reception of these applications is paramount to success, and global take-up rates have been low.
Objective:
In this study, we sought to identify characteristics of an individual or the situation that may be associated with voluntary downloads of a contact tracing mobile application in Singapore.
Methods:
A sample of 505 adults from the general community completed an online survey. As the primary outcome measure, participants indicated whether they had downloaded a contact tracing application introduced at the national level ("TraceTogether"). As predictor variables, we assessed: (1) participant demographics; (2) behavioral changes on account of the pandemic; and (3) pandemic severity (the number of cases and lockdown status).
Results:
Within our dataset, the strongest predictor of digital contact tracing take-up was the extent to which individuals had already adjusted their lifestyles because of the pandemic (Z = 13.56, P < .001). Network analyses revealed that take-up was most related to: using hand sanitizers, avoiding public transport, and preferring outdoor over indoor venues during the pandemic. However, demographic and situational characteristics was not significantly associated with application downloads.
Conclusions:
Efforts to introduce contact tracing applications could capitalize on pandemic-related behavioral adjustments that individuals have made. Given that critical mass is needed for contact tracing to be effective, we urge further research to understand how citizens respond to contact tracing applications.
Clinicaltrial:
ClinicalTrials.gov NCT04468581.
Instantaneous contact tracing
New analyses indicate that severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) is more infectious and less virulent than the earlier SARS-CoV-1, which emerged in China in 2002. Unfortunately, the current virus has greater epidemic potential because it is difficult to trace mild or presymptomatic infections. As no treatment is currently available, the only tools that we can currently deploy to stop the epidemic are contact tracing, social distancing, and quarantine, all of which are slow to implement. However imperfect the data, the current global emergency requires more timely interventions. Ferretti et al. explored the feasibility of protecting the population (that is, achieving transmission below the basic reproduction number) using isolation coupled with classical contact tracing by questionnaires versus algorithmic instantaneous contact tracing assisted by a mobile phone application. For prevention, the crucial information is understanding the relative contributions of different routes of transmission. A phone app could show how finite resources must be divided between different intervention strategies for the most effective control.
Science , this issue p. eabb6936
The most widely used technique for IP geolocation consists in building a database to keep the mapping between IP blocks and a geographic location. Several databases are available and are frequently used by many services and web sites in the Internet. Contrary to widespread belief, geolocation databases are far from being as reliable as they claim. In this paper, we conduct a comparison of several current geolocation databases -both commercial and free- to have an insight of the limitations in their usability.
First, the vast majority of entries in the databases refer only to a few popular countries (e.g., U.S.). This creates an imbalance in the representation of countries across the IP blocks of the databases. Second, these entries do not reflect the original allocation of IP blocks, nor BGP announcements. In addition, we quantify the accuracy of geolocation databases on a large European ISP based on ground truth information. This is the first study using a ground truth showing that the overly fine granularity of database entries makes their accuracy worse, not better. Geolocation databases can claim country-level accuracy, but certainly not city-level.
Berlin-Neukölln: Low income and migrant families in coronavirus lockdown
- Deutsche Welle
Germany maps out coronavirus regulations on domestic travel
- Deutsche Welle
Germany puts two western districts on lockdown
- Deutsche Welle
Warn App FAQ: My risk status hasn't been updated for over a day. An internet connection was available what's wrong?
- Corona