scholarly journals On the Effectiveness of Digital Contact Tracing and Contact Prevention Under Varying COVID-19 Infection Detection Rates

2021 ◽  
Author(s):  
German José Soldano ◽  
Juan Andrés Fraire ◽  
Jorge Manuel Finochietto ◽  
Rodrigo Quiroga
Keyword(s):  
Response Time ◽  
Time Delays ◽  
Data Privacy ◽  
Developed Countries ◽  
Contact Tracing ◽  
Detection Rates ◽  
Agent Based ◽  
Infection Detection ◽  
Available Technology ◽  
Novel Strategy

Abstract A plethora of measures are being combined in the attempt to reduce SARS-CoV-2 spread. Due to its sustainability over time, contact tracing is one of the most frequently applied interventions worldwide, albeit with mixed results. In this work, we evaluate the perfomance of contact tracing for different infection detection rates and response time delays. We also introduce and analyze a novel strategy we call contact prevention. We model the effect of both strategies on contagion dynamics in SERIA, an agent-based simulation platform that implements realistic population-dependent statistical distributions. Results show that diagnostic/response time delays and low infection detection rates greatly impair the effect of contact tracing strategies, while contact prevention remains effective in these scenarios. Therefore, contact prevention could play a significant role in pandemic mitigation, specially in under-developed countries where diagnostic and tracing capabilities are insufficient. Contact prevention could thus sustainably reduce the propagation of respiratory viruses while relying on available technology, respecting data privacy, and most importantly, promoting community-based awareness and social responsibility. Depending on infection detection and app adoption rates, applying a combination of contact tracing and contact prevention could reduce pandemic-related mortality by 20%-56%.

scholarly journals COVID-19 mitigation by digital contact tracing and contact prevention (app-based social exposure warnings)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Germán J. Soldano ◽  
Juan A. Fraire ◽  
Jorge M. Finochietto ◽  
Rodrigo Quiroga
Keyword(s):  
Response Time ◽  
Time Delays ◽  
Data Privacy ◽  
Contact Tracing ◽  
Detection Rates ◽  
High Exposure ◽  
Infection Detection ◽  
Available Technology ◽  
Novel Strategy ◽  
Social Exposure

AbstractA plethora of measures are being combined in the attempt to reduce SARS-CoV-2 spread. Due to its sustainability, contact tracing is one of the most frequently applied interventions worldwide, albeit with mixed results. We evaluate the performance of digital contact tracing for different infection detection rates and response time delays. We also introduce and analyze a novel strategy we call contact prevention, which emits high exposure warnings to smartphone users according to Bluetooth-based contact counting. We model the effect of both strategies on transmission dynamics in SERIA, an agent-based simulation platform that implements population-dependent statistical distributions. Results show that contact prevention remains effective in scenarios with high diagnostic/response time delays and low infection detection rates, which greatly impair the effect of traditional contact tracing strategies. Contact prevention could play a significant role in pandemic mitigation, especially in developing countries where diagnostic and tracing capabilities are inadequate. Contact prevention could thus sustainably reduce the propagation of respiratory viruses while relying on available technology, respecting data privacy, and most importantly, promoting community-based awareness and social responsibility. Depending on infection detection and app adoption rates, applying a combination of digital contact tracing and contact prevention could reduce pandemic-related mortality by 20–56%.

scholarly journals Investigating Dynamics of COVID-19 Spread and Containment with Agent-Based Modeling

2021 ◽  
Vol 11 (12) ◽  
pp. 5367
Author(s):  
Amirarsalan Rajabi ◽  
Alexander V. Mantzaris ◽  
Ece C. Mutlu ◽  
Ozlem O. Garibay
Keyword(s):  
Disease Model ◽  
Agent Based Modeling ◽  
Contact Tracing ◽  
Test Bed ◽  
Policy Makers ◽  
Agent Based ◽  
Contact Behavior ◽  
Epidemic Curve ◽  
Behavioral Adaptations ◽  
Travel Restrictions

Governments, policy makers, and officials around the globe are working to mitigate the effects of the COVID-19 pandemic by making decisions that strive to save the most lives and impose the least economic costs. Making these decisions require comprehensive understanding of the dynamics by which the disease spreads. In traditional epidemiological models, individuals do not adapt their contact behavior during an epidemic, yet adaptive behavior is well documented (i.e., fear-induced social distancing). In this work we revisit Epstein’s “coupled contagion dynamics of fear and disease” model in order to extend and adapt it to explore fear-driven behavioral adaptations and their impact on efforts to combat the COVID-19 pandemic. The inclusion of contact behavior adaptation endows the resulting model with a rich dynamics that under certain conditions reproduce endogenously multiple waves of infection. We show that the model provides an appropriate test bed for different containment strategies such as: testing with contact tracing and travel restrictions. The results show that while both strategies could result in flattening the epidemic curve and a significant reduction of the maximum number of infected individuals; testing should be applied along with tracing previous contacts of the tested individuals to be effective. The results show how the curve is flattened with testing partnered with contact tracing, and the imposition of travel restrictions.

scholarly journals Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jonatan Almagor ◽  
Stefano Picascia
Keyword(s):  
High Rate ◽  
Contact Tracing ◽  
Agent Based Model ◽  
Agent Based ◽  
The Social ◽  
Behavioural Factors ◽  
The Impact ◽  
Different Levels ◽  
User Rate

AbstractA contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.

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 Do You Have COVID-19?: How to Increase the Use of Diagnostic and Contact-Tracing Apps

2021 ◽  
Author(s):  
Déborah Martínez ◽  
Cristina Parilli ◽  
Ana María Rojas ◽  
Carlos Scartascini ◽  
Alberto Simpser
Keyword(s):  
Data Privacy ◽  
Contact Tracing ◽  
Survey Experiment ◽  
Promotion Policy ◽  
Percentage Points ◽  
Willingness To Adopt ◽  
Mexican Adults

Diagnostic and contact tracing apps are an important weapon against contagion during a pandemic. We study how the content of the messages used to promote the apps influences adoption by conducting a survey experiment on approximately 23,000 Mexican adults. Respondents were randomly assigned to one of three different prompts, or a control condition, before stating their willingness to adopt a diagnostic app and contact-tracing app. The prompt emphasizing government efforts to ensure data privacy, which has been one of the most common strategies, reduced willingness to adopt the diagnostic app by about 4 percentage points and the contact tracing app by 3 percentage points. An effective app promotion policy must understand individuals' reservations and be wary of unintended reactions to naive reassurances.

scholarly journals How effective was Newfoundland & Labrador’s travel ban to prevent the spread of COVID-19? An agent-based analysis

2021 ◽  
Author(s):  
Dionne M. Aleman ◽  
Benjamin Z. Tham ◽  
Sean J. Wagner ◽  
Justin Semelhago ◽  
Asghar Mohammadi ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Spatial Location ◽  
Contact Tracing ◽  
Infection Rates ◽  
Case Scenario ◽  
Agent Based ◽  
Individual Level ◽  
Transmission Rates ◽  
Imported Cases ◽  
The Uk

AbstractBackgroundTo prevent the spread of COVID-19 in Newfoundland & Labrador (NL), NL implemented a wide travel ban in May 2020. We estimate the effectiveness of this travel ban using a customized agent-based simulation (ABS).MethodsWe built an individual-level ABS to simulate the movements and behaviors of every member of the NL population, including arriving and departing travellers. The model considers individual properties (spatial location, age, comorbidities) and movements between environments, as well as age-based disease transmission with pre-symptomatic, symptomatic, and asymptomatic transmission rates. We examine low, medium, and high travel volume, traveller infection rates, and traveller quarantine compliance rates to determine the effect of travellers on COVID spread, and the ability of contact tracing to contain outbreaks.ResultsInfected travellers increased COVID cases by 2-52x (8-96x) times and peak hospitalizations by 2-49x (8-94x), with (without) contact tracing. Although contact tracing was highly effective at reducing spread, it was insufficient to stop outbreaks caused by travellers in even the best-case scenario, and the likelihood of exceeding contact tracing capacity was a concern in most scenarios. Quarantine compliance had only a small impact on COVID spread; travel volume and infection rate drove spread.InterpretationNL’s travel ban was likely a critically important intervention to prevent COVID spread. Even a small number of infected travellers can play a significant role in introducing new chains of transmission, resulting in exponential community spread and significant increases in hospitalizations, while outpacing contact tracing capabilities. With the presence of more transmissible variants, e.g., the UK variant, prevention of imported cases is even more critical.

scholarly journals CLINICAL FEATURES, DIAGNOSIS AND TREATMENT OF COVID-19

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
J Ali ◽  
Q Ali ◽  
MM Hafeez ◽  
A Malik
Keyword(s):  
Clinical Microbiology ◽  
Respiratory Diseases ◽  
Developed Countries ◽  
Respiratory Disorder ◽  
Rt Pcr ◽  
Research Facility ◽  
Agent Based ◽  
Worldwide Population ◽  
Test Outcomes

The COVID-19 has affected worldwide population at every level from advance to under developed countries and also majorly affected clinical microbiology labs. This critique covers current issues furthermore, challenges for the research facility determination of diseases brought about by extreme intense respiratory disorder coronavirus 2 (SARS-CoV-2). In the pre analytical stage, gathering the best possible respiratory diseases information at the time from the privilege has become fundamental for a brief and exact basic finding of COVID-19. Appropriate measures are required to protect lab staffs, performing the test outcomes for COVID-19. In the investigative stage, constant converse translation PCR (RT-PCR) tests remain the basic trial of decision for the etiologic determination of SARS-CoV-2 contamination while counteracting agent-based procedures are being presented as supplemental tests. In the post-analytical stage, testing results ought to be cautiously deciphered utilizing both basic and serological findings. At long last, arbitrary access, testing kits accessible for the purpose of care with versatile limits are encouraging the fast and exact finding and observing of SARS-CoV-2 contaminations and extraordinarily aid the control of this episode.

scholarly journals Active case detection methods for crusted scabies and leprosy: A systematic review

2021 ◽  
Vol 15 (7) ◽  
pp. e0009577
Author(s):  
Miriam Glennie ◽  
Karen Gardner ◽  
Michelle Dowden ◽  
Bart J. Currie
Keyword(s):  
Systematic Review ◽  
Disease Control ◽  
Detection Methods ◽  
Contact Tracing ◽  
Case Detection ◽  
Community Screening ◽  
Detection Rates ◽  
Active Case Detection ◽  
Active Case ◽  
Crusted Scabies

Background Crusted scabies is endemic in some remote Aboriginal communities in the Northern Territory (NT) of Australia and carries a high mortality risk. Improvement in active case detection (ACD) for crusted scabies is hampered by a lack of evidence about best practice. We therefore conducted a systematic review of ACD methods for leprosy, a condition with similar ACD requirements, to consider how findings could be informative to crusted scabies detection. Methods and principle findings We conducted systematic searches in MEDLINE, CINAHL, Scopus and the Cochrane Database for Systematic Reviews for studies published since 1999 that reported at least one comparison rate (detection or prevalence rate) against which the yield of the ACD method could be assessed. The search yielded 15 eligible studies from 511. Study heterogeneity precluded meta-analysis. Contact tracing and community screening of marginalised ethnic groups yielded the highest new case detection rates. Rapid community screening campaigns, and those using less experienced screening personnel, were associated with lower suspect confirmation rates. There is insufficient data to assess whether ACD campaigns improve treatment outcomes or disease control. Conclusion This review demonstrates the importance of ACD campaigns in communities facing the highest barriers to healthcare access and within neighbourhoods of index cases. The potential benefit of ACD for crusted scabies is not quantified, however, lessons from leprosy suggest value in follow-up with previously identified cases and their close contacts to support for scabies control and to reduce the likelihood of reinfection in the crusted scabies case. Skilled screening personnel and appropriate community engagement strategies are needed to maximise screening uptake. More research is needed to assess ACD cost effectiveness, impact on disease control, and to explore ACD methods capable of capturing the homeless and highly mobile who may be missed in household centric models.

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