scholarly journals Demystifying COVID-19 Digital Contact Tracing: A Survey on Frameworks and Mobile Apps

2020 ◽  
Vol 2020 ◽  
pp. 1-29
Author(s):  
Tania Martin ◽  
Georgios Karopoulos ◽  
José L. Hernández-Ramos ◽  
Georgios Kambourakis ◽  
Igor Nai Fovino
Keyword(s):  
Mobile Apps ◽  
Global Scale ◽  
Contact Tracing ◽  
Network Technology ◽  
Full Spectrum ◽  
Ongoing Effort ◽  
Modus Vivendi ◽  
Model Section ◽  
Client Side ◽  
Adversary Model

The coronavirus pandemic is a new reality, and it severely affects the modus vivendi of the international community. In this context, governments are rushing to devise or embrace novel surveillance mechanisms and monitoring systems to fight the outbreak. The development of digital tracing apps, which among others are aimed at automatising and globalising the prompt alerting of individuals at risk in a privacy-preserving manner, is a prominent example of this ongoing effort. Very promptly, a number of digital contact tracing architectures have been sprouted, followed by relevant app implementations adopted by governments worldwide. Bluetooth, specifically its Low Energy (BLE) power-conserving variant, has emerged as the most promising short-range wireless network technology to implement the contact tracing service. This work offers the first to our knowledge full-fledged review of the most concrete contact tracing architectures proposed so far in a global scale. This endeavour does not only embrace the diverse types of architectures and systems, namely, centralised, decentralised, or hybrid, but also equally addresses the client side, i.e., the apps that have been already deployed in Europe by each country. There is also a full-spectrum adversary model section, which does not only amalgamate the previous work in the topic but also brings new insights and angles to contemplate upon.

scholarly journals A first look at Android applications in Google Play related to COVID-19

2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Jordan Samhi ◽  
Kevin Allix ◽  
Tegawendé F. Bissyandé ◽  
Jacques Klein
Keyword(s):  
Mobile Apps ◽  
Contact Tracing ◽  
Location Tracking ◽  
Response Effort ◽  
Sensitive Data ◽  
Android Apps ◽  
Digital World ◽  
Public Health Organizations ◽  
Android Applications ◽  
Google Play

AbstractDue to the convenience of access-on-demand to information and business solutions, mobile apps have become an important asset in the digital world. In the context of the COVID-19 pandemic, app developers have joined the response effort in various ways by releasing apps that target different user bases (e.g., all citizens or journalists), offer different services (e.g., location tracking or diagnostic-aid), provide generic or specialized information, etc. While many apps have raised some concerns by spreading misinformation or even malware, the literature does not yet provide a clear landscape of the different apps that were developed. In this study, we focus on the Android ecosystem and investigate Covid-related Android apps. In a best-effort scenario, we attempt to systematically identify all relevant apps and study their characteristics with the objective to provide a first taxonomy of Covid-related apps, broadening the relevance beyond the implementation of contact tracing. Overall, our study yields a number of empirical insights that contribute to enlarge the knowledge on Covid-related apps: (1) Developer communities contributed rapidly to the COVID-19, with dedicated apps released as early as January 2020; (2) Covid-related apps deliver digital tools to users (e.g., health diaries), serve to broadcast information to users (e.g., spread statistics), and collect data from users (e.g., for tracing); (3) Covid-related apps are less complex than standard apps; (4) they generally do not seem to leak sensitive data; (5) in the majority of cases, Covid-related apps are released by entities with past experience on the market, mostly official government entities or public health organizations.

scholarly journals What do users think of the UK’s three COVID-19 contact-tracing apps? A comparative analysis

2021 ◽  
Vol 28 (1) ◽  
pp. e100320
Author(s):  
Vahid Garousi ◽  
David Cutting
Keyword(s):  
Mobile Apps ◽  
Analysis Data ◽  
End Users ◽  
Contact Tracing ◽  
User Reviews ◽  
The Public ◽  
Engineering Teams ◽  
Technical Issues ◽  
The Uk ◽  
The Right

ObjectivesOur goal was to gain insights into the user reviews of the three COVID-19 contact-tracing mobile apps, developed for the different regions of the UK: ‘NHS COVID-19’ for England and Wales, ‘StopCOVID NI’ for Northern Ireland and ‘Protect Scotland’ for Scotland. Our two research questions are (1) what are the users’ experience and satisfaction levels with the three apps? and (2) what are the main issues (problems) that users have reported about the apps?MethodsWe assess the popularity of the apps and end users’ perceptions based on user reviews in app stores. We conduct three types of analysis (data mining, sentiment analysis and topic modelling) to derive insights from the combined set of 25 583 user reviews of the aforementioned three apps (submitted by users until the end of 2020).ResultsResults show that end users have been generally dissatisfied with the apps under study, except the Scottish app. Some of the major issues that users have reported are high battery drainage and doubts on whether apps are really working.DiscussionTowards the end of 2020, the much-awaited COVID-19 vaccines started to be available, but still, analysing the users’ feedback and technical issues of these apps, in retrospective, is valuable to learn the right lessons to be ready for similar circumstances in future.ConclusionOur results show that more work is needed by the stakeholders behind the apps (eg, apps’ software engineering teams, public-health experts and decision makers) to improve the software quality and, as a result, the public adoption of these apps. For example, they should be designed to be as simple as possible to operate (need for usability).

scholarly journals Digital Tracing during the COVID-19 Pandemic: User Appraisal, Emotion, and Continuance Intention

2021 ◽  
Vol 13 (2) ◽  
pp. 608
Author(s):  
Ayoung Suh ◽  
Mengjun Li
Keyword(s):  
Mobile Apps ◽  
Contact Tracing ◽  
The Novel ◽  
Personal Privacy ◽  
Continuance Intention ◽  
Infectious Disease Outbreak ◽  
Using Data ◽  
Novel Coronavirus ◽  
Technological Affordances ◽  
Method Approach

This study explores how people appraise the use of contact tracing apps during the novel coronavirus (COVID-19) pandemic in South Korea. Despite increasing attention paid to digital tracing for health disasters, few studies have empirically examined user appraisal, emotion, and their continuance intention to use contact tracing apps for disaster management during an infectious disease outbreak. A mixed-method approach combining qualitative and quantitative inquiries was employed. In the qualitative study, by conducting interviews with 25 people who have used mobile apps for contact tracing, the way users appraise contact tracing apps for COVID-19 was explored. In the quantitative study, using data collected from 506 users of the apps, the interplay among cognitive appraisal (threats and opportunities) and its association with user emotion, and continuance intention was examined. The findings indicate that once users experience loss emotions, such as anger, frustration, and disgust, they are not willing to continue using the apps. App designers should consider providing technological affordances that enable users to have a sense of control over the technology so that they do not experience loss emotions. Public policymakers should also consider developing measures that can balance public health and personal privacy.

Predictors to use mobile apps for monitoring COVID-19 symptoms and contact tracing: A survey among Dutch citizens. (Preprint)

2021 ◽  
Author(s):  
Stephanie Maria Jansen-Kosterink ◽  
Marian Hurmuz ◽  
Marjolein den Ouden ◽  
Lex van Velsen
Keyword(s):  
Mobile Applications ◽  
Mobile Application ◽  
Online Survey ◽  
Reproduction Number ◽  
Mobile Apps ◽  
Contact Tracing ◽  
Snowball Sampling ◽  
Final Model ◽  
Symptom Recognition ◽  
Personal Connections

UNSTRUCTURED Background: eHealth applications have been recognized as a valuable tool to reduce COVID-19’s effective reproduction number. In this paper, we report on an online survey among Dutch citizens with the goal to identify antecedents of acceptance of a mobile application for COVID-19 symptom recognition and monitoring, and a mobile application for contact tracing. Methods: Next to the demographics, the online survey contained questions focussing on perceived health, fear of COVID-19 and intention to use. We used snowball sampling via posts on social media and personal connections. To identify antecedents of acceptance of the two mobile applications we conducted multiple linear regression analyses. Results: In total, 238 Dutch adults completed the survey. Almost 60% of the responders were female and the average age was 45.6 years (SD±17.4). For the symptom app, the final model included the predictors age, attitude towards technology and fear of COVID-19. The model had an R2 of 0.141. The final model for the tracing app included the same predictors and had an R2 of 0.156. The main reason to use both mobile applications was to control the spread of the COVID-19 virus. Concerns about privacy was mentioned as the main reason not to use the mobile applications. Conclusion: Age, attitude towards technology and fear of COVID-19 are important predictors of the acceptance of COVID-19 mobile applications for symptom recognition and monitoring and for contact tracing. These predictors should be taken into account during the development and implementation of these mobile applications to secure acceptance. Discussion: Age, attitude towards technology and fear of COVID-19 are important predictors of the acceptance of COVID-19 mobile applications for symptom recognition and monitoring and for contact tracing. These predictors should be taken into account during the development and implementation of these mobile applications to secure acceptance. Age, attitude towards technology and fear of COVID-19 are important predictors of the acceptance of COVID-19 mobile applications for symptom recognition and monitoring and for contact tracing. These predictors should be taken into account during the development and implementation of these mobile applications to secure acceptance.

The Role of Trust in Covid Tracing Apps: Estonian Case Study (Preprint)

2021 ◽  
Author(s):  
Sonia Sousa ◽  
Tiina Kalju
Keyword(s):  
Minority Groups ◽  
Mobile Apps ◽  
Control Measures ◽  
Security And Privacy ◽  
Contact Tracing ◽  
P Value ◽  
Sensitive Data ◽  
Convenience Sample ◽  
The World ◽  
Wide Availability

BACKGROUND The COVID-19 pandemic has caused changes on how we use technology across the world, both socially and economically. Due to the urgency and severity of the crisis different virus control measures were explored. One of the means how technology could help in this situation was by helping trace the contacts of people to prevent the spread of the disease. Many governments and public health authorities across the world have launched a number of contact tracing mobile apps (CTA). By the end of 2020, there are more than 50 contact tracing apps in both Google Play and iOS App Store [1]. Despite the wide availability, the download rates are low and usage rates are even lower [2][3]. There could be many reasons why the adoption is so low, but most certainly one variable that has been overlooked is the level of trust that potential users need to feel comfortable using an app. In Estonia, the CTA named HOIA has been developed as a means of digital contact tracing. By the middle of January 2021, there have been approximately 250 000 downloads but only 1763 (around 4,7% of all COVID-19 positive in Estonia by that time) people have registered as being tested COVID-19 positive [4]. It shows that HOIA has not proved to be efficient means to reduce the spread of the pandemic. Modeling evidence suggests that in order to be effective, the use of contact tracing apps would need to be very high, at least 80% of smartphone users to stop the pandemic [5]. 40% of Estonian people who don’t have HOIA do not believe that HOIA is effective and does what is promised. The concern about security and privacy was in the second place [6]. OBJECTIVE The goal of this study was to assess Estonian's trust towards the HOIA app and what has caused the shortage in trust. Namely, assess how much Estonians trust Covid-19 contact tracing app HOIA and what aspects are perceived as distrust by them. The study contributes to designers' understanding and awareness of designing trustworthy technology. METHODS The study comprised of measuring trust in HOIA CTA application using human-computer Trust psychometric scale [22]. A convenience sample was used in data collection, this includes all potential HOIA among the Estonian population. RESULTS Results indicate significant positive correlations between participants' trust towards the Estonian COVID tracing application (HOIA) and their perceptions of risk (p-value 0.000), competency (P-value 0.000), Benevolence (P-value=0.025), and reciprocity (P-value 0.015). CONCLUSIONS With the COVID-19 crisis, the new phenomenon of contact tracing apps was introduced to fight against the pandemic. CTAs were hoped to be a technological breakthrough to decrease the spread of the virus. However, this has not happened around the world. The same has happened in Estonia and evidence shows, that one of the reasons could be the low level of trust. The results of the study confirm, that trust in HOIA among Estonian habitants does affect their predisposition to use and indicated that participants do not believe HOIA is able to fulfill the main goal and decrease the spread of the virus. The result of this work is not only limited to HOIA but can be implemented by other CTAs as well. The results of this study contribute to designers' understanding and awareness of designing trustworthy technology. Eventually helps to provide design recommendations that ensure trustworthiness in the CTAs AI ability to use highly sensitive data and serve society. Regarding the limitations of this study, the survey was able to gather insight about the perceptions of HOIA, was enough to make a statistical generalization about the users’ perception and usage habits but more data needs to be collected if the intention is to generalize the results to the whole population of Estonia. Also, we should pay attention to the different minority groups to reach a valid conclusion. CLINICALTRIAL no trial registration.

scholarly journals Early Acceptability of a Mobile App for Contact Tracing During the COVID-19 Pandemic in France: National Web-Based Survey (Preprint)

2021 ◽  
Author(s):  
Rajae Touzani ◽  
Emilien Schultz ◽  
Seth M Holmes ◽  
Stéphanie Vandentorren ◽  
Pierre Arwidson ◽  
...  
Keyword(s):  
Health Literacy ◽  
Multinomial Logistic Regression ◽  
Mobile Apps ◽  
Mobile App ◽  
Perceived Usefulness ◽  
Contact Tracing ◽  
Structural Determinants ◽  
Multinomial Logistic Regression Analysis ◽  
Factors Associated ◽  
Literacy Survey

BACKGROUND Several countries have implemented mobile apps in an attempt to trace close contacts of patients with COVID-19 and, in turn, reduce the spread of SARS-CoV-2. However, the effectiveness of this approach depends on the adherence of a large segment of the population. OBJECTIVE The aims of this study were to evaluate the acceptability of a COVID-19 contact tracing mobile app among the French population and to investigate the barriers to its use. METHODS The Health Literacy Survey 2019 questioned 1003 people in France during the COVID-19 pandemic on the basis of quota sampling. The survey collected sociodemographic characteristics and health literacy data, as well as information on participants’ communication with caregivers, trust in institutions, and COVID-19 knowledge and preventive behaviors. The acceptability of a mobile app for contact tracing was measured by a single question, the responses to which were grouped into three modalities: app-supporting, app-willing, and app-reluctant. Multinomial logistic regression analysis was performed to identify the factors associated with the acceptability of a mobile app during the COVID-19 pandemic. RESULTS Only 19.2% (193/1003) of all participants were app-supporting, whereas half of them (504/1003, 50.3%) were reluctant. The factors associated with willingness or support toward the contact tracing app included lower financial deprivation (app-willing: adjusted odds ratio [aOR] 0.8, 95% CI 0.69-0.93; app-supporting: aOR 0.7, 95% CI 0.58-0.84) and higher perceived usefulness of using a mobile app to send completed health questionnaires to doctors (app-willing: aOR 2.3, 95% CI 1.70-3.26; app-supporting: aOR 3.1, 95% CI 2.04-4.82). Furthermore, the likelihood of supporting the mobile app increased with age over 60 years (aOR 1.9, 95% CI 1.13-3.22), trust in political representatives (aOR 2.7, 95% CI 1.72-4.23), feeling concerned about the pandemic situation (aOR 2.2, 95% CI 1.47-3.32), and knowledge about the transmission of COVID-19 (aOR 2.0, 95% CI 1.39-2.96). CONCLUSIONS The most socioeconomically precarious people, who are at a higher risk of SARS-CoV-2 infection, are also the most reluctant to using a contact tracing mobile app. Therefore, optimal adherence can only be effective with a targeted discourse on public health benefits to adopt such an app, which should be combined with a reduction in inequalities by acting on structural determinants.

scholarly journals A fair efficacy formula for assessing the effectiveness of contact tracing applications

2020 ◽  
Author(s):  
Adam Fowler
Keyword(s):  
Mobile Applications ◽  
Mobile Apps ◽  
Time Windows ◽  
Real Life ◽  
Contact Tracing ◽  
Proximity Detection ◽  
Epidemiological Risk ◽  
Efficacy Measure ◽  
Impact Of Technology ◽  
The Impact

AbstractMobile contact tracing apps have been developed by many countries in response to the COVID-19 pandemic. Trials have focussed on unobserved population trials or staged scenarios aimed to simulate real life. No efficacy measure has been developed that assesses the fundamental ability of any proximity detection protocol to accurately detect, measure, and therefore assess the epidemiological risk that a mobile phone owner has been placed at. This paper provides a fair efficacy formula that can be applied to any mobile contact tracing app, using any technology, allowing it’s likely epidemiological effectiveness to be assessed. This paper defines such a formula and provides results for several simulated protocols as well as one real life protocol tested according to the standard methodology set out in this paper. The results presented show that protocols that use time windows greater than 30 seconds or that bucket their distance analogue (E.g. RSSI for Bluetooth) provide poor estimates of risk, showing an efficacy rating of less than 6%. The fair efficacy formula is shown in this paper to be able to be used to calculate the ‘Efficacy of contact tracing’ variable value as used in two papers on using mobile applications for contact tracing [6]. The output from the formulae in this paper, therefore, can be used to directly assess the impact of technology on the spread of a disease outbreak. This formula can be used by nations developing contact tracing applications to assess the efficacy of their applications. This will allow them to reassure their populations and increase the uptake of contact tracing mobile apps, hopefully having an effect on slowing the spread of COVID-19 and future epidemics.

scholarly journals Technology, Privacy, and User Opinions of COVID-19 Mobile Apps for Contact Tracing: Systematic Search and Content Analysis

10.2196/23467 ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. e23467
Author(s):  
Mahmoud Elkhodr ◽  
Omar Mubin ◽  
Zainab Iftikhar ◽  
Maleeha Masood ◽  
Belal Alsinglawi ◽  
...  
Keyword(s):  
New Zealand ◽  
Personal Information ◽  
Mobile Apps ◽  
The United States ◽  
Contact Tracing ◽  
Policy Makers ◽  
App Store ◽  
Technical Issues ◽  
Google Play ◽  
Privacy Issues

Background Many countries across the globe have released their own COVID-19 contact tracing apps. This has resulted in the proliferation of several apps that used a variety of technologies. With the absence of a standardized approach used by the authorities, policy makers, and developers, many of these apps were unique. Therefore, they varied by function and the underlying technology used for contact tracing and infection reporting. Objective The goal of this study was to analyze most of the COVID-19 contact tracing apps in use today. Beyond investigating the privacy features, design, and implications of these apps, this research examined the underlying technologies used in contact tracing apps. It also attempted to provide some insights into their level of penetration and to gauge their public reception. This research also investigated the data collection, reporting, retention, and destruction procedures used by each of the apps under review. Methods This research study evaluated 13 apps corresponding to 10 countries based on the underlying technology used. The inclusion criteria ensured that most COVID-19-declared epicenters (ie, countries) were included in the sample, such as Italy. The evaluated apps also included countries that did relatively well in controlling the outbreak of COVID-19, such as Singapore. Informational and unofficial contact tracing apps were excluded from this study. A total of 30,000 reviews corresponding to the 13 apps were scraped from app store webpages and analyzed. Results This study identified seven distinct technologies used by COVID-19 tracing apps and 13 distinct apps. The United States was reported to have released the most contact tracing apps, followed by Italy. Bluetooth was the most frequently used underlying technology, employed by seven apps, whereas three apps used GPS. The Norwegian, Singaporean, Georgian, and New Zealand apps were among those that collected the most personal information from users, whereas some apps, such as the Swiss app and the Italian (Immuni) app, did not collect any user information. The observed minimum amount of time implemented for most of the apps with regard to data destruction was 14 days, while the Georgian app retained records for 3 years. No significant battery drainage issue was reported for most of the apps. Interestingly, only about 2% of the reviewers expressed concerns about their privacy across all apps. The number and frequency of technical issues reported on the Apple App Store were significantly more than those reported on Google Play; the highest was with the New Zealand app, with 27% of the reviewers reporting technical difficulties (ie, 10% out of 27% scraped reviews reported that the app did not work). The Norwegian, Swiss, and US (PathCheck) apps had the least reported technical issues, sitting at just below 10%. In terms of usability, many apps, such as those from Singapore, Australia, and Switzerland, did not provide the users with an option to sign out from their apps. Conclusions This article highlighted the fact that COVID-19 contact tracing apps are still facing many obstacles toward their widespread and public acceptance. The main challenges are related to the technical, usability, and privacy issues or to the requirements reported by some users.

scholarly journals Superspreading k-cores at the center of COVID-19 pandemic persistence

2020 ◽  
Author(s):  
Matteo Serafino ◽  
Higor S. Monteiro ◽  
Shaojun Luo ◽  
Saulo D. S. Reis ◽  
Carles Igual ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Large Scale ◽  
Mobile Apps ◽  
Human Mobility ◽  
Contact Tracing ◽  
Weak Links ◽  
Contact Network ◽  
Transmission Network ◽  
Before And After ◽  
High Betweenness

The spread of COVID-19 caused by the recently discovered SARS-CoV-2 virus has become a worldwide problem with devastating consequences. To slow down the spread of the pandemic, mass quarantines have been implemented globally, provoking further social and economic disruptions. Here, we address this problem by implementing a large-scale contact tracing network analysis to find the optimal quarantine protocol to dismantle the chain of transmission of coronavirus with minimal disruptions to society. We track billions of anonymized GPS human mobility datapoints from a compilation of hundreds of mobile apps deployed in Latin America to monitor the evolution of the contact network of disease transmission before and after the confinements. As a consequence of the lockdowns, people's mobility across the region decreases by ~53%, which results in a drastic disintegration of the transmission network by ~90%. However, this disintegration did not halt the spreading of the disease. Our analysis indicates that superspreading k-core structures persist in the transmission network to prolong the pandemic. Once the k-cores are identified, the optimal strategy to break the chain of transmission is to quarantine a minimal number of 'weak links' with high betweenness centrality connecting the large k-cores. Our results demonstrate the effectiveness of an optimal tracing strategy to halt the pandemic. As countries race to build and deploy contact tracing apps, our results could turn into a valuable resource to help deploy protocols with minimized disruptions.

scholarly journals A modelling framework to assess the likely effectiveness of facemasks in combination with ‘lock-down’ in managing the COVID-19 pandemic

2020 ◽  
Vol 476 (2238) ◽  
pp. 20200376 ◽  
Author(s):  
Richard O. J. H. Stutt ◽  
Renata Retkute ◽  
Michael Bradley ◽  
Christopher A. Gilligan ◽  
John Colvin
Keyword(s):  
Mobile Apps ◽  
Population Level ◽  
Disease Spread ◽  
Contact Tracing ◽  
Lower Efficiency ◽  
The Public ◽  
Molecular Tests ◽  
Modelling Framework ◽  
Increased Risk ◽  
The Impact

COVID-19 is characterized by an infectious pre-symptomatic period, when newly infected individuals can unwittingly infect others. We are interested in what benefits facemasks could offer as a non-pharmaceutical intervention, especially in the settings where high-technology interventions, such as contact tracing using mobile apps or rapid case detection via molecular tests, are not sustainable. Here, we report the results of two mathematical models and show that facemask use by the public could make a major contribution to reducing the impact of the COVID-19 pandemic. Our intention is to provide a simple modelling framework to examine the dynamics of COVID-19 epidemics when facemasks are worn by the public, with or without imposed ‘lock-down’ periods. Our results are illustrated for a number of plausible values for parameter ranges describing epidemiological processes and mechanistic properties of facemasks, in the absence of current measurements for these values. We show that, when facemasks are used by the public all the time (not just from when symptoms first appear), the effective reproduction number, R e , can be decreased below 1, leading to the mitigation of epidemic spread. Under certain conditions, when lock-down periods are implemented in combination with 100% facemask use, there is vastly less disease spread, secondary and tertiary waves are flattened and the epidemic is brought under control. The effect occurs even when it is assumed that facemasks are only 50% effective at capturing exhaled virus inoculum with an equal or lower efficiency on inhalation. Facemask use by the public has been suggested to be ineffective because wearers may touch their faces more often, thus increasing the probability of contracting COVID-19. For completeness, our models show that facemask adoption provides population-level benefits, even in circumstances where wearers are placed at increased risk. At the time of writing, facemask use by the public has not been recommended in many countries, but a recommendation for wearing face-coverings has just been announced for Scotland. Even if facemask use began after the start of the first lock-down period, our results show that benefits could still accrue by reducing the risk of the occurrence of further COVID-19 waves. We examine the effects of different rates of facemask adoption without lock-down periods and show that, even at lower levels of adoption, benefits accrue to the facemask wearers. These analyses may explain why some countries, where adoption of facemask use by the public is around 100%, have experienced significantly lower rates of COVID-19 spread and associated deaths. We conclude that facemask use by the public, when used in combination with physical distancing or periods of lock-down, may provide an acceptable way of managing the COVID-19 pandemic and re-opening economic activity. These results are relevant to the developed as well as the developing world, where large numbers of people are resource poor, but fabrication of home-made, effective facemasks is possible. A key message from our analyses to aid the widespread adoption of facemasks would be: ‘my mask protects you, your mask protects me’.

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