Design and Implementation of a Social Distancing and Contact Tracing Wearable

2020 ◽  
Author(s):  
Yannick Verbelen ◽  
Suresh Kaluvan ◽  
Ulrike Haller ◽  
Morgan Boardman ◽  
Tom B. Scott
Keyword(s):  
Contact Tracing ◽  
Social Distancing ◽  
Design And Implementation

Are social networking platforms the key to effective social distancing for COVID-19? (Preprint)

2020 ◽  
Author(s):  
Viknesh Sounderajah ◽  
Hutan Ashrafian ◽  
Sheraz Markar ◽  
Ara Darzi
Keyword(s):  
Operating System ◽  
Social Networking ◽  
Contact Tracing ◽  
Text Data ◽  
Social Distancing ◽  
Web Mapping ◽  
Viral Spread ◽  
Behavioural Insights ◽  
Mapping Software ◽  
Incidence And Mortality

UNSTRUCTURED If health systems are to effectively employ social distancing measures to in response to further COVID-19 peaks, they must adopt new behavioural metrics that can supplement traditional downstream measures, such as incidence and mortality. Access to mobile digital innovations may dynamically quantify compliance to social distancing (e.g. web mapping software) as well as establish personalised real-time contact tracing of viral spread (e.g. mobile operating system infrastructure through Google-Apple partnership). In particular, text data from social networking platforms can be mined for unique behavioural insights, such as symptom tracking and perception monitoring. Platforms, such as Twitter, have shown significant promise in tracking communicable pandemics. As such, it is critical that social networking companies collaborate with each other in order to (1) enrich the data that is available for analysis, (2) promote the creation of open access datasets for researchers and (3) cultivate relationships with governments in order to affect positive change.

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.

High national acceptance for COVID-19 contact tracing technologies in Taiwan (Preprint)

2021 ◽  
Author(s):  
Paul M. Garrett ◽  
Yuwen Wang ◽  
Joshua P. White ◽  
Yoshihisa Kashima ◽  
Simon Dennis ◽  
...  
Keyword(s):  
Technology Acceptance ◽  
Contact Tracing ◽  
Virus Spread ◽  
Security Measures ◽  
Contributing Factors ◽  
Privacy And Security ◽  
Social Distancing ◽  
The Public ◽  
Privacy Measures ◽  
Credible Intervals

BACKGROUND Governments worldwide have introduced COVID-19 tracing technologies. Taiwan, a world leader in controlling the virus’ spread, has introduced the Taiwan ‘Social Distancing App’ to facilitate COVID-19 contact tracing. However, for these technologies to be effective, they must be accepted and used by the public. OBJECTIVE Our study aimed to determine public acceptance for three hypothetical tracing technologies: a centralized Government App, a decentralized Bluetooth App (e.g., Taiwan’s Social Distancing App), and a Telecommunication tracing technology; and model what factors contributed to their acceptance. METHODS Four nationally representative surveys were conducted in April 2020 sampling 6,000 Taiwanese residents. Perceptions and impacts of COVID-19, government effectiveness, worldviews, and attitudes towards and acceptance of one-of-three hypothetical tracing technologies were assessed. RESULTS Technology acceptance was high across all hypothetical technologies (67% - 73%) and improved with additional privacy measures (82% - 88%). Bayesian modelling (using 95% highest density credible intervals) showed data sensitivity and perceived poor COVID-19 policy compliance inhibited technology acceptance. By contrast, technology benefits (e.g., returning to activities, reducing virus spread, lowering the likelihood of infection), higher education, and perceived technology privacy, security, and trust, were all contributing factors to overall acceptance. Bayesian ordinal probit models revealed higher COVID-19 concern for other people than for one’s self. CONCLUSIONS Taiwan is currently using a range of technologies to minimize the spread of COVID-19 as the country returns to normal economic and social activities. We observed high acceptance for COVID-19 tracing technologies among the Taiwanese public, a promising and necessary finding for the successful introduction of Taiwan’s new ‘Social Distancing App’. Policy makers may capitalize on this acceptance by focusing attention towards the App’s benefits, privacy and security measures, making the App’s privacy measures transparent to the public, and emphasizing App uptake and compliance among the public. CLINICALTRIAL Not applicable.

scholarly journals Evaluating the effectiveness of social distancing interventions against COVID-19

2020 ◽  
Author(s):  
Laura Matrajt ◽  
Tiffany Leung
Keyword(s):  
Mathematical Model ◽  
Contact Tracing ◽  
Old Adults ◽  
Social Distancing ◽  
The Us

AbstractSARS-CoV-2 has infected over 140,000 people as of March 14, 2020. We use a mathematical model to investigate the effectiveness of social distancing interventions lasting six weeks in a middle-sized city in the US. We explore four social distancing strategies by reducing the contacts of adults over 60 years old, adults over 60 years old and children, all adults (25, 75 or 95% compliance), and everyone in the population. Our results suggest that social distancing interventions can avert cases by 20% and hospitalizations and deaths by 90% even with modest compliance within adults as long as the intervention is kept in place, but the epidemic is set to rebound once the intervention is lifted. Our models suggest that social distancing interventions will buy crucial time but need to occur in conjunction with testing and contact tracing of all suspected cases to mitigate transmission of SARS-CoV-2.

scholarly journals Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China

Science ◽  
2020 ◽  
Vol 368 (6498) ◽  
pp. 1481-1486 ◽  
Author(s):  
Juanjuan Zhang ◽  
Maria Litvinova ◽  
Yuxia Liang ◽  
Yan Wang ◽  
Wei Wang ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Odds Ratio ◽  
School Closure ◽  
Hunan Province ◽  
Contact Tracing ◽  
Transmission Model ◽  
Social Distancing ◽  
Susceptibility To Infection ◽  
Contact Patterns ◽  
The Impact

Intense nonpharmaceutical interventions were put in place in China to stop transmission of the novel coronavirus disease 2019 (COVID-19). As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact survey data for Wuhan and Shanghai before and during the outbreak and contact-tracing information from Hunan province. Daily contacts were reduced seven- to eightfold during the COVID-19 social distancing period, with most interactions restricted to the household. We find that children 0 to 14 years of age are less susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection than adults 15 to 64 years of age (odds ratio 0.34, 95% confidence interval 0.24 to 0.49), whereas individuals more than 65 years of age are more susceptible to infection (odds ratio 1.47, 95% confidence interval 1.12 to 1.92). Based on these data, we built a transmission model to study the impact of social distancing and school closure on transmission. We find that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. Although proactive school closures cannot interrupt transmission on their own, they can reduce peak incidence by 40 to 60% and delay the epidemic.

scholarly journals Epidemiological trend of COVID-19 in Nepal and the importance of social distancing to contain the virus

2020 ◽  
Vol 1 (1) ◽  
pp. 15-25
Author(s):  
Amod K. Pokhrel ◽  
Yadav P. Joshi ◽  
Sopnil Bhattarai
Keyword(s):  
Mitigation Measures ◽  
Contact Tracing ◽  
Limited Information ◽  
Social Distancing ◽  
Mobility Data ◽  
Epidemiological Trend ◽  
Reproduction Numbers ◽  
The Government ◽  
Testing Case ◽  
The Impact

There is limited information on the epidemiology and the effects of mitigation measures on the spread of COVID-19 in Nepal. Using publicly available databases, we analyzed the epidemiological trend, the people's movement trends at different intervals across different categories of places and evaluated implications of social mobility on COVID-19. We also estimated the epidemic peak. As of June 9, 2020, Provinces 2 and 5 have most of the cases. People between 15 and 54 years are vulnerable to becoming infected, and more males than females are affected. The cases are growing exponentially. The growth rate of 0.13 and >1 reproduction numbers (R0) over time (median: 1.48; minimum: 0.58, and maximum: 3.71) confirms this trend. The case doubling time is five days. Google's community mobility data suggest that people strictly followed social distancing measures for one month after the lockdown. By around the 4th week of April, the individual's movement started rising, and social contacts increased. The number of cases peaked on May 12, with 83 confirmed cases in one day. The Susceptible-Exposed-Infectious-Removed (SEIR) model suggests that the epidemic will peak approximately on day 41 (July 21, 2020), and start to plateau after day 80. To contain the spread of the virus, people should maintain social distancing. The Government needs to continue active surveillance, more PCR-based testing, case detection, contact tracing, isolation, and quarantine. The Government should also provide financial support and safety-nets to the citizen to limit the impact of COVID-19.

scholarly journals Response to COVID-19 in South Korea and implications for lifting stringent interventions

BMC Medicine ◽  
2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Amy Dighe ◽  
Lorenzo Cattarino ◽  
Gina Cuomo-Dannenburg ◽  
Janetta Skarp ◽  
Natsuko Imai ◽  
...  
Keyword(s):  
South Korea ◽  
High Volume ◽  
Individual Case ◽  
Metropolitan Region ◽  
Contact Tracing ◽  
Social Distancing ◽  
Early Adoption ◽  
The Usa ◽  
Sharp Growth ◽  
Seoul Metropolitan Region

Abstract Background After experiencing a sharp growth in COVID-19 cases early in the pandemic, South Korea rapidly controlled transmission while implementing less stringent national social distancing measures than countries in Europe and the USA. This has led to substantial interest in their “test, trace, isolate” strategy. However, it is important to understand the epidemiological peculiarities of South Korea’s outbreak and characterise their response before attempting to emulate these measures elsewhere. Methods We systematically extracted numbers of suspected cases tested, PCR-confirmed cases, deaths, isolated confirmed cases, and numbers of confirmed cases with an identified epidemiological link from publicly available data. We estimated the time-varying reproduction number, Rt, using an established Bayesian framework, and reviewed the package of interventions implemented by South Korea using our extracted data, plus published literature and government sources. Results We estimated that after the initial rapid growth in cases, Rt dropped below one in early April before increasing to a maximum of 1.94 (95%CrI, 1.64–2.27) in May following outbreaks in Seoul Metropolitan Region. By mid-June, Rt was back below one where it remained until the end of our study (July 13th). Despite less stringent “lockdown” measures, strong social distancing measures were implemented in high-incidence areas and studies measured a considerable national decrease in movement in late February. Testing the capacity was swiftly increased, and protocols were in place to isolate suspected and confirmed cases quickly; however, we could not estimate the delay to isolation using our data. Accounting for just 10% of cases, individual case-based contact tracing picked up a relatively minor proportion of total cases, with cluster investigations accounting for 66%. Conclusions Whilst early adoption of testing and contact tracing is likely to be important for South Korea’s successful outbreak control, other factors including regional implementation of strong social distancing measures likely also contributed. The high volume of testing and the low number of deaths suggest that South Korea experienced a small epidemic relative to other countries. Caution is needed in attempting to replicate the South Korean response in populations with larger more geographically widespread epidemics where finding, testing, and isolating cases that are linked to clusters may be more difficult.

scholarly journals De-Escalation by Reversing the Escalation with a Stronger Synergistic Package of Contact Tracing, Quarantine, Isolation and Personal Protection: Feasibility of Preventing a COVID-19 Rebound in Ontario, Canada, as a Case Study

Biology ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 100 ◽  
Author(s):  
Biao Tang ◽  
Francesca Scarabel ◽  
Nicola Luigi Bragazzi ◽  
Zachary McCarthy ◽  
Michael Glazer ◽  
...  
Keyword(s):  
Time Series Data ◽  
Necessary Conditions ◽  
Reproduction Number ◽  
Contact Tracing ◽  
Series Data ◽  
Personal Protection ◽  
Dynamics Model ◽  
Social Distancing ◽  
Canadian Provinces

Since the beginning of the COVID-19 pandemic, most Canadian provinces have gone through four distinct phases of social distancing and enhanced testing. A transmission dynamics model fitted to the cumulative case time series data permits us to estimate the effectiveness of interventions implemented in terms of the contact rate, probability of transmission per contact, proportion of isolated contacts, and detection rate. This allows us to calculate the control reproduction number during different phases (which gradually decreased to less than one). From this, we derive the necessary conditions in terms of enhanced social distancing, personal protection, contact tracing, quarantine/isolation strength at each escalation phase for the disease control to avoid a rebound. From this, we quantify the conditions needed to prevent epidemic rebound during de-escalation by simply reversing the escalation process.

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