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.

scholarly journals A Mathematical Model of Contact Tracing during the 2014–2016 West African Ebola Outbreak

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 608
Author(s):  
Danielle Burton ◽  
Suzanne Lenhart ◽  
Christina J. Edholm ◽  
Benjamin Levy ◽  
Michael L. Washington ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Disease Management ◽  
Ebola Virus ◽  
Virus Disease ◽  
Infected Individual ◽  
Vital Role ◽  
West African ◽  
Contact Tracing ◽  
The Novel ◽  
Using Data

The 2014–2016 West African outbreak of Ebola Virus Disease (EVD) was the largest and most deadly to date. Contact tracing, following up those who may have been infected through contact with an infected individual to prevent secondary spread, plays a vital role in controlling such outbreaks. Our aim in this work was to mechanistically represent the contact tracing process to illustrate potential areas of improvement in managing contact tracing efforts. We also explored the role contact tracing played in eventually ending the outbreak. We present a system of ordinary differential equations to model contact tracing in Sierra Leonne during the outbreak. Using data on cumulative cases and deaths, we estimate most of the parameters in our model. We include the novel features of counting the total number of people being traced and tying this directly to the number of tracers doing this work. Our work highlights the importance of incorporating changing behavior into one’s model as needed when indicated by the data and reported trends. Our results show that a larger contact tracing program would have reduced the death toll of the outbreak. Counting the total number of people being traced and including changes in behavior in our model led to better understanding of disease management.

scholarly journals COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society

2021 ◽  
pp. 0272989X2110030
Author(s):  
Serin Lee ◽  
Zelda B. Zabinsky ◽  
Judith N. Wasserheit ◽  
Stephen M. Kofsky ◽  
Shan Liu
Keyword(s):  
Large City ◽  
Face Mask ◽  
School Closure ◽  
Contact Tracing ◽  
The Novel ◽  
Agent Based ◽  
Social Distancing ◽  
Variable Compliance ◽  
Novel Coronavirus ◽  
Nonpharmaceutical Interventions

As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.

scholarly journals Investigation of the genetic variation in ACE2 on the structural recognition by the novel coronavirus (SARS-CoV-2)

2020 ◽  
Author(s):  
Xingyi Guo ◽  
Zhishan Chen ◽  
Yumin Xia ◽  
Weiqiang Lin ◽  
Hongzhi Li
Keyword(s):  
Genetic Variation ◽  
The Novel ◽  
S Protein ◽  
Angiotensin Converting Enzyme 2 ◽  
Missense Variants ◽  
Catalytic Metal ◽  
Using Data ◽  
Novel Coronavirus ◽  
Insight Into

Abstract Background: The outbreak of coronavirus disease (COVID-19) was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), through its surface spike glycoprotein (S-protein) recognition on the receptor Angiotensin-converting enzyme 2 (ACE2) in humans. However, it remains unclear how genetic variations in ACE2 may affect its function and structure, and consequently alter the recognition by SARS-CoV-2. Methods: We have systemically characterized missense variants in the gene ACE2 using data from the Genome Aggregation Database (gnomAD; N = 141,456). To investigate the putative deleterious role of missense variants, six existing functional prediction tools were applied to evaluate their impact. We further analyzed the structural flexibility of ACE2 and its protein-protein interface with the S-protein of SARS-CoV-2 using our developed Legion Interfaces Analysis (LiAn) program.Results: Here, we characterized a total of 12 ACE2 putative deleterious missense variants. Of those 12 variants, we further showed that p.His378Arg could directly weaken the binding of catalytic metal atom to decrease ACE2 activity and p.Ser19Pro could distort the most important helix to the S-protein. Another seven missense variants may affect secondary structures (i.e. p.Gly211Arg; p.Asp206Gly; p.Arg219Cys; p.Arg219His, p.Lys341Arg, p.Ile468Val, and p.Ser547Cys), whereas p.Ile468Val with AF = 0.01 is only present in Asian.Conclusions: We provide strong evidence of putative deleterious missense variants in ACE2 that are present in specific populations, which could disrupt the function and structure of ACE2. These findings provide novel insight into the genetic variation in ACE2 which may affect the SARS-CoV-2 recognition and infection, and COVID-19 susceptibility and treatment.

scholarly journals Forecasting COVID-19 cases in Algeria using logistic growth and polynomial regression models

2021 ◽  
Author(s):  
Mohamed LOUNIS ◽  
Babu Malavika
Keyword(s):  
Regression Model ◽  
Logistic Model ◽  
Polynomial Regression ◽  
Logistic Growth ◽  
The Novel ◽  
Logistic Growth Model ◽  
Polynomial Regression Models ◽  
Using Data ◽  
Novel Coronavirus ◽  
Polynomial Regression Model

Abstract The novel Coronavirus respiratory disease 2019 (COVID-19) is still expanding through the world since it started in Wuhan (China) on December 2019 reporting a number of more than 84.4 millions cases and 1.8 millions deaths on January 3rd 2021.In this work and to forecast the COVID-19 cases in Algeria, we used two models: the logistic growth model and the polynomial regression model using data of COVID-19 cases reported by the Algerian ministry of health from February 25th to December 2nd, 2020. Results showed that the polynomial regression model fitted better the data of COVID-19 in Algeria the Logistic model. The first model estimated the number of cases on January, 19th 2021 at 387673 cases. This model could help the Algerian authorities in the fighting against this disease.

Contact Tracing Applications Against COVID-19: A Systematic Review (Preprint)

2021 ◽  
Author(s):  
Ahmad Nabeel ◽  
Salman AlSabah ◽  
Eliana Al Haddad ◽  
Hutan Ashrafian
Keyword(s):  
Systematic Review ◽  
Critical Mass ◽  
Population Level ◽  
Ease Of Use ◽  
Contact Tracing ◽  
The Novel ◽  
Scientific Databases ◽  
Manual Methods ◽  
Novel Coronavirus ◽  
Transmission Of Disease

BACKGROUND The novel coronavirus 2019 (COVID-19) pandemic has triggered public anxiety around the world. So far, the evidence suggests that prevention on a public scale is the most effective health measure for thwarting the progress of COVID-19. Another critical aspect of preventing COVID-19 is contact tracing. OBJECTIVE We aimed to investigate the effectiveness of contact tracing applications currently available in the context of the COVID-19 pandemic. METHODS We undertook a systematic review and narrative synthesis of all literature relating to contact tracing applications in the context of COVID-19. We searched 3 major scientific databases. Only articles that were published in English and were available as full-text articles were selected for review. Data were extracted and narrative syntheses conducted. RESULTS Five studies relating to COVID-19 were included in the review. Our results suggest that digitalized contact tracing methods can be beneficial for impeding the progress of COVID-19. Three key themes were generated from this systematic review. First, the critical mass of application adoption must be attained at the population level before the sensitivity and positive predictive value of the solution can be increased. Second, usability factors such as access, ease of use and the elimination of barriers are essential in driving this uptake. Third, privacy must be ensured where possible as it is the single most significant barrier against achieving critical mass. CONCLUSIONS The COVID-19 pandemic has claimed more than 2 million lives globally, with over 100 million confirmed cases. Contact tracing can rapidly identify potentially infected individuals before the emergence of severe or critical symptoms, and it can also prevent the subsequent transmission of disease from secondary cases when implemented efficiently. Contact tracing methods have proved to be beneficial for impeding the progress of COVID-19 as compared to older, more labor intensive manual methods.

Face masks are an essential tool to mitigate the ongoing SARS-CoV-2 pandemic: a call to action

2020 ◽  
Vol 3 (3) ◽  
pp. 157-159
Author(s):  
P. Dehgani-Mobaraki ◽  
A. Kamber Zaidi ◽  
J.M. Levy ◽  
Keyword(s):  
Upper Airway ◽  
World Health ◽  
Contact Tracing ◽  
The Novel ◽  
Call To Action ◽  
Public Health Emergencies ◽  
Current Spread ◽  
The World ◽  
Health And Disease ◽  
Novel Coronavirus

Over the past several months, an increasing volume of infor- mation has expanded awareness regarding the transmission of SARS-CoV-2, the novel coronavirus associated with COVID-19. Following the pandemic declaration by the World Health Orga- nization (WHO), global authorities immediately took measures to reduce the transmission and subsequent morbidity associa- ted with this highly contagious disease. However, despite initial success in “flattening the curve” of viral transmission, many areas of the world are currently experiencing an increase in com- munity transmission, threatening to replicate the early public health emergencies experienced by Italy (1,2). In addition, the possibility of contact tracing through geosocial applications and public service platforms have been met with variable interest (3). Given current spread and the upcoming influenza season, it is essential that we use our voices as experts in upper airway health and disease to educate and encourage all communities to adopt appropriate protective measures, including the routine use of facemasks.

scholarly journals Situation analysis of novel Coronavirus (2019-nCoV) cases in Nepal

2020 ◽  
Vol 1 (1) ◽  
pp. 9-14
Author(s):  
Kiran Paudel ◽  
Prashamsa Bhandari ◽  
Yadav Prasad Joshi
Keyword(s):  
South Asian ◽  
Case Fatality ◽  
Cumulative Number ◽  
The Novel ◽  
Asian Countries ◽  
Primary Case ◽  
The Status ◽  
Exponential Trend ◽  
Using Data ◽  
Novel Coronavirus

The Novel Coronavirus (2019-nCoV) is currently a major threat to global health in an unprecedented manner. The global pandemic of COVID-19 has affected 215 countries and territories including Nepal. Until 1st June 2020, altogether 1,811 COVID-19 positive cases were diagnosed using RT-PCR. This study aimed to analyze the status of COVID-19 cases in Nepal and South Asian countries. A retrospective study from 23rd January to 1st June 2020 was conducted using data of the Ministry of Home Affairs, Nepal and Worldometer homepages. The primary case records during the pre and post lockdown periods were examined. Spatial distribution was observed. An exponential trend line was plotted and COVID-19 situation in South Asian countries was assessed. Of 1,811 COVID-19 cases, the highest number (38.3%) was reported in Province 2. Out of 77 districts, 59 were affected. In Fifty-eight districts, primary cases appeared during the lockdown period. The cumulative number of COVID-19 cases showed the exponential pattern of distribution in Nepal. In South Asian countries, India had the highest number of cases and case fatality rate (CFR). There were no cases of CFR in Bhutan. The Novel Coronavirus emergence in Nepal has become a serious challenge to the various sectors including public health. The emergence of primary cases even in the lockdown period needs a detailed study in the future.

scholarly journals Exploring the role and mechanism of COVID-19 apps in fighting the current pandemic

2020 ◽  
Vol 0 ◽  
pp. 1-6
Author(s):  
Karthikeyan P. Iyengar ◽  
Rachit Jain ◽  
David Ananth Samy ◽  
Vijay Kumar Jain ◽  
Raju Vaishya ◽  
...  
Keyword(s):  
Data Privacy ◽  
Viral Transmission ◽  
Contact Tracing ◽  
The Novel ◽  
Test Track ◽  
The World ◽  
Novel Coronavirus ◽  
And Control ◽  
Second Wave ◽  
Transmission Test

As COVID-19 pandemic spread worldwide, policies have been developed to contain the disease and prevent viral transmission. One of the key strategies has been the principle of “‘test, track, and trace” to minimize spread of the virus. Numerous COVID-19 contact tracing applications have been rolled around the world to monitor and control the spread of the disease. We explore the characteristics of various COVID-19 applications and especially the Aarogya Setu COVID-19 app from India in its role in fighting the current pandemic. We assessed the current literature available to us using conventional search engines, including but not limited to PubMed, Google Scholar, and Research Gate in May 2020 till the time of submission of this article. The search criteria used MeSH keywords such as “COVID-19,” “pandemics,” “contact tracing,” and “mobile applications.” A variable uptake of different COVID-19 applications has been noted with increasing enrolment around the world. Security concerns about data privacy remain. The various COVID-19 applications will complement manual contact tracing system to assess and prevent viral transmission. Test, track, trace, and support policy will play a key role in avoidance of a “second wave” of the novel coronavirus severe acute respiratory syndrome coronavirus 2 outbreak.

scholarly journals Social Insurance, Welfare Codes, and the Spread of Covid-19

2021 ◽  
Vol 8 (1) ◽  
pp. 41-52
Author(s):  
Tadashi Adino ◽  
Moein Mirani Ahangar Kolaei ◽  
Eser Demir ◽  
Tolga Constantinou ◽  
Mostafa Toranji ◽  
...  
Keyword(s):  
Social Insurance ◽  
Fixed Effect Model ◽  
Daily Basis ◽  
The Novel ◽  
Disadvantaged Population ◽  
Criteria Pollutants ◽  
Effect Model ◽  
Using Data ◽  
Novel Coronavirus ◽  
Low Educated

This paper explores disparities in the effect of pollution on confirmed cases of Covid-19 based on counties’ socioeconomic and demographic characteristics. Using data on all US counties on a daily basis over the year 2020 and applying a rich panel data fixed effect model, we document that: 1) there are discernible social and demographic disparities in the spread of Covid-19. Blacks, low educated, and poorer people are at higher risks of being infected by the new disease. 2) The criteria pollutants including Ozone, CO, PM10, and PM2.5 have the potential to accelerate the outbreak of the novel coronavirus. 3) The disadvantaged population is more vulnerable to the effects of pollution on the spread of coronavirus. Specifically, the effects of pollution on confirmed cases become larger for blacks, low educated, and counties with lower average wages in 2019.

scholarly journals Effective Reproduction Number and Dispersion under Contact Tracing and Lockdown on COVID-19 in Karnataka

2020 ◽  
Author(s):  
Siva Athreya ◽  
Nitya Gadhiwala ◽  
Abhiti Mishra
Keyword(s):  
Individual Variation ◽  
Reproduction Number ◽  
Contact Tracing ◽  
The Novel ◽  
Secondary Infections ◽  
The Government ◽  
Novel Coronavirus

We analyze the data provided in the Novel Coronavirus (COVID-19) media bulletins of the Government of Karnataka. We classify the patients of COVID-19 into clusters and study the Reproduction number and Dispersion for eight specific clusters. We find that it is uniformly less than one, indicating the benefits of contact tracing, lockdown and quarantine measures. However, the Dispersion is low indicating individual variation in secondary infections and the occurrence of Super-spreading events. Finally, we analyze the surge in infections after 27th June and find it unlikely that it was caused solely by the large Migration in May and June 2020.

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