scholarly journals Modeling the effects of contact-tracing apps on the spread of the coronavirus disease: Mechanisms, conditions, and efficiency

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256151
Author(s):  
Asako Chiba
Keyword(s):  
High Efficiency ◽  
Census Data ◽  
Comprehensive Analysis ◽  
Contact Tracing ◽  
High Type ◽  
Agent Based ◽  
Current Testing ◽  
Disease Mechanisms ◽  
Testing Technology ◽  
Better Than

This study simulates the spread of the coronavirus disease (COVID-19) using a detailed agent-based model and the census data of Japan to provide a comprehensive analysis of the effects of contact-tracing apps. The model assumes two types of response to the app notification: the notified individuals quarantine themselves (type-Q response) or they get tested (type-T response). The results reveal some crucial characteristics of the apps. First, type-Q response is successful in achieving containment; however, type-T response has a limited curve-flattening effect. Second, type-Q response performs better than type-T response because it involves quarantine of those who are infected but have not become infectious yet, and the current testing technology cannot detect the virus in these individuals. Third, if the download rate of the apps is extremely high, type-Q response can achieve virus containment with a small number of quarantined people and thereby high efficiency. Finally, given a fixed download rate, increasing the number of tests per day enhances the effectiveness of the apps, although the degree of improved effectiveness is not proportional to the change in the number of tests.

scholarly journals A data driven agent-based model that recommends non-pharmaceutical interventions to suppress Coronavirus disease 2019 resurgence in megacities

2021 ◽  
Vol 18 (181) ◽  
pp. 20210112
Author(s):  
Ling Yin ◽  
Hao Zhang ◽  
Yuan Li ◽  
Kang Liu ◽  
Tianmu Chen ◽  
...  
Keyword(s):  
Census Data ◽  
Herd Immunity ◽  
Risk Tolerance ◽  
Contact Tracing ◽  
Agent Based Model ◽  
Agent Based ◽  
Shenzhen City ◽  
Other World ◽  
Work Class ◽  
Pharmaceutical Interventions

Before herd immunity against Coronavirus disease 2019 (COVID-19) is achieved by mass vaccination, science-based guidelines for non-pharmaceutical interventions are urgently needed to reopen megacities. This study integrated massive mobile phone tracking records, census data and building characteristics into a spatially explicit agent-based model to simulate COVID-19 spread among 11.2 million individuals living in Shenzhen City, China. After validation by local epidemiological observations, the model was used to assess the probability of COVID-19 resurgence if sporadic cases occurred in a fully reopened city. Combined scenarios of three critical non-pharmaceutical interventions (contact tracing, mask wearing and prompt testing) were assessed at various levels of public compliance. Our results show a greater than 50% chance of disease resurgence if the city reopened without contact tracing. However, tracing household contacts, in combination with mandatory mask use and prompt testing, could suppress the probability of resurgence under 5% within four weeks. If household contact tracing could be expanded to work/class group members, the COVID resurgence could be avoided if 80% of the population wear facemasks and 40% comply with prompt testing. Our assessment, including modelling for different scenarios, helps public health practitioners tailor interventions within Shenzhen City and other world megacities under a variety of suppression timelines, risk tolerance, healthcare capacity and public compliance.

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 High-Efficiency Intracavity Continuous-Wave Green-Light Generation by Quasiphase Matching in a Bulk Periodically Poled MgO:LiNbO3 Crystal

2008 ◽  
Vol 2008 ◽  
pp. 1-4 ◽  
Author(s):  
Shaowei Chu ◽  
Ying Zhang ◽  
Bin Wang ◽  
Yong Bi
Keyword(s):  
High Efficiency ◽  
Continuous Wave ◽  
Green Light ◽  
Frequency Doubling ◽  
Green Laser ◽  
Periodically Poled ◽  
Output Stability ◽  
532 Nm ◽  
Better Than ◽  
Quasiphase Matching

908 mW of green light at 532 nm were generated by intracavity quasiphase matching in a bulk periodically poled MgO:LiNbO3 (PPMgLN) crystal. A maximum optical-to-optical conversion efficiency of 33.5% was obtained from a 0.5 mm thick, 10 mm long, and 5 mol% MgO:LiNbO3 crystal with an end-pump power of 2.7 W at 808 nm. The temperature bandwidth between the intracavity and single-pass frequency doubling was found to be different for the PPMgLN. Reliability and stability of the green laser were evaluated. It was found that for continuous operation of 100 hours, the output stability was better than 97.5% and no optical damage was observed.

scholarly journals A hybrid computational framework for intelligent inter-continent SARS-CoV-2 sub-strains characterization and prediction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Moses Effiong Ekpenyong ◽  
Mercy Ernest Edoho ◽  
Udoinyang Godwin Inyang ◽  
Faith-Michael Uzoka ◽  
Itemobong Samuel Ekaidem ◽  
...  
Keyword(s):  
State Of The Art ◽  
Close Association ◽  
Contact Tracing ◽  
Genome Diversity ◽  
Cognitive Approach ◽  
Computational Framework ◽  
Machine Learning Methods ◽  
Global Initiative ◽  
Future Direction ◽  
Better Than

AbstractWhereas accelerated attention beclouded early stages of the coronavirus spread, knowledge of actual pathogenicity and origin of possible sub-strains remained unclear. By harvesting the Global initiative on Sharing All Influenza Data (GISAID) database (https://www.gisaid.org/), between December 2019 and January 15, 2021, a total of 8864 human SARS-CoV-2 complete genome sequences processed by gender, across 6 continents (88 countries) of the world, Antarctica exempt, were analyzed. We hypothesized that data speak for itself and can discern true and explainable patterns of the disease. Identical genome diversity and pattern correlates analysis performed using a hybrid of biotechnology and machine learning methods corroborate the emergence of inter- and intra- SARS-CoV-2 sub-strains transmission and sustain an increase in sub-strains within the various continents, with nucleotide mutations dynamically varying between individuals in close association with the virus as it adapts to its host/environment. Interestingly, some viral sub-strain patterns progressively transformed into new sub-strain clusters indicating varying amino acid, and strong nucleotide association derived from same lineage. A novel cognitive approach to knowledge mining helped the discovery of transmission routes and seamless contact tracing protocol. Our classification results were better than state-of-the-art methods, indicating a more robust system for predicting emerging or new viral sub-strain(s). The results therefore offer explanations for the growing concerns about the virus and its next wave(s). A future direction of this work is a defuzzification of confusable pattern clusters for precise intra-country SARS-CoV-2 sub-strains analytics.

Recent Patents on Third Generation Bearing Testing Machine

2021 ◽  
Vol 15 ◽  
Author(s):  
Yanling Zhao ◽  
Huanqing Zhang
Keyword(s):  
Large Scale ◽  
High Efficiency ◽  
Testing Machine ◽  
Theoretical Research ◽  
Third Generation ◽  
Existing Problems ◽  
Military Equipment ◽  
Bearing Life ◽  
The Future ◽  
Testing Technology

Background: Bearing testing machine is the key equipment for bearing design, theoretical research and improvement, and it plays an important role in the performance of bearing life, fatigue, vibration and working temperature. With the requirements of aerospace, military equipment, automobile manufacturing and other industrial fields of the bearing are becoming higher and higher. There is an urgent need for high-precision and high-efficiency bearing testing machines to monitor and analyze the performance of bearings. Objective: By analyzing the recent patents, the characteristics and existing problems of the current bearing testing machine are summarized to provide references for the development of bearing test equipment in the future. Methods: This paper reviews various representative patents related to the third generation bearing testing machines. Results: Although the structure of bearing testing machines is different, the main problems in the structure and design principle of bearing testing machine have been summarized and analyzed, and the development of trend and direction of the future bearing testing machine have been discussed. Conclusion: Bearing testing machines for health monitoring of bearing life cycle is of great significance. The current bearing testing machine has basically achieved the monitoring and analysis However, due to the emergence of new types of bearings, further improvement is still needed. With the development of testing technology towards intelligent and big data-driven direction, bearing testing machine is moving towards the type of cloud computing and large-scale testing.

scholarly journals Silica Nanoflowers-Stabilized Pickering Emulsion as a Robust Biocatalysis Platform for Enzymatic Production of Biodiesel

Catalysts ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 1026 ◽  
Author(s):  
Lihui Wang ◽  
Xinlong Liu ◽  
Yanjun Jiang ◽  
Peng Liu ◽  
Liya Zhou ◽  
...  
Keyword(s):  
High Efficiency ◽  
Pickering Emulsion ◽  
Biodiesel Production ◽  
Candida Antarctica Lipase ◽  
Waste Oil ◽  
Enzymatic Production ◽  
Mild Conditions ◽  
Experimental Yield ◽  
Optimized Conditions ◽  
Better Than

Enzymatic production of biodiesel had attracted much attention due to its high efficiency, mild conditions and environmental protection. However, the high cost of enzyme, poor solubility of methanol in oil and adsorption of glycerol onto the enzyme limited the popularization of the process. To address these problems, we developed a silica nanoflowers-stabilized Pickering emulsion as a biocatalysis platform with Candida antarctica lipase B (CALB) as model lipase for biodiesel production. Silica nanoflowers (SNFs) were synthesized in microemulsion and served as a carrier for CALB immobilization and then used as an emulsifier for constructing Pickering emulsion. The structure of SNFs and the biocatalytic Pickering emulsion (CALB@SNFs-PE) were characterized in detail. Experimental data about the methanolysis of waste oil to biodiesel was evaluated by response surface methodology. The highest experimental yield of 98.5 ± 0.5% was obtained under the optimized conditions: methanol/oil ratio of 2.63:1, a temperature of 45.97 °C, CALB@SNFs dosage of 33.24 mg and time of 8.11 h, which was closed to the predicted value (100.00%). Reusability test showed that CALB@SNFs-PE could retain 76.68% of its initial biodiesel yield after 15 cycles, which was better than that of free CALB and N435.

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.

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