scholarly journals Modelling Memory for Individual Re-identification in Decentralised Mobile Contact Tracing Applications

2021 ◽  
Vol 5 (1) ◽  
pp. 1-21
Author(s):  
Luca Bedogni ◽  
Shakila Khan Rumi ◽  
Flora D. Salim
Keyword(s):  
Mitigation Strategies ◽  
Disease Spread ◽  
Contact Tracing ◽  
Initial Time ◽  
Human Beings ◽  
Time Period ◽  
Positive Individual ◽  
Technological Tools ◽  
Privacy Attack ◽  
Simulation Results

In 2020 the coronavirus outbreak changed the lives of people worldwide. After an initial time period in which it was unclear how to battle the virus, social distancing has been recognised globally as an effective method to mitigate the disease spread. This called for technological tools such as Mobile Contact Tracing Applications (MCTA), which are used to digitally trace contacts among people, and in case a positive case is found, people with the application installed which had been in contact will be notified. De-centralised MCTA may suffer from a novel kind of privacy attack, based on the memory of the human beings, which upon notification of the application can identify who is the positive individual responsible for the notification. Our results show that it is indeed possible to identify positive people among the group of contacts of a human being, and this is even easier when the sociability of the positive individual is low. In practice, our simulation results show that identification can be made with an accuracy of more than 90% depending on the scenario. We also provide three mitigation strategies which can be implemented in de-centralised MCTA and analyse which of the three are more effective in limiting this novel kind of attack.

scholarly journals Reopening universities during the COVID-19 pandemic: A testing strategy to minimize active cases and delay outbreaks

2020 ◽  
Author(s):  
Lior Rennert ◽  
Corey A. Kalbaugh ◽  
Lu Shi ◽  
Christopher McMahan
Keyword(s):  
Mitigation Strategies ◽  
Disease Spread ◽  
Contact Tracing ◽  
Infectious Period ◽  
University Campuses ◽  
Effective Strategies ◽  
Viral Spread ◽  
Extreme Risk ◽  
The Impact ◽  
Maximum Occupancy

AbstractBackgroundUniversity campuses present an ideal environment for viral spread and are therefore at extreme risk of serving as a hotbed for a COVID-19 outbreak. While active surveillance throughout the semester such as widespread testing, contact tracing, and case isolation, may assist in detecting and preventing early outbreaks, these strategies will not be sufficient should a larger outbreak occur. It is therefore necessary to limit the initial number of active cases at the start of the semester. We examine the impact of pre-semester NAT testing on disease spread in a university setting.MethodsWe implement simple dynamic transmission models of SARS-CoV-2 infection to explore the effects of pre-semester testing strategies on the number of active infections and occupied isolation beds throughout the semester. We assume an infectious period of 3 days and vary R0 to represent the effectiveness of disease mitigation strategies throughout the semester. We assume the prevalence of active cases at the beginning of the semester is 5%. The sensitivity of the NAT test is set at 90%.ResultsIf no pre-semester screening is mandated, the peak number of active infections occurs in under 10 days and the size of the peak is substantial, ranging from 5,000 active infections when effective mitigation strategies (R0 = 1.25) are implemented to over 15,000 active infections for less effective strategies (R0 = 3). When one NAT test is mandated within one week of campus arrival, effective (R0 = 1.25) and less effective (R0 = 3) mitigation strategies delay the onset of the peak to 40 days and 17 days, respectively, and result in peak size ranging from 1,000 to over 15,000 active infections. When two NAT tests are mandated, effective (R0 = 1.25) and less effective (R0 = 3) mitigation strategies delay the onset of the peak through the end of fall semester and 20 days, respectively, and result in peak size ranging from less than 1,000 to over 15,000 active infections. If maximum occupancy of isolation beds is set to 2% of the student population, then isolation beds would only be available for a range of 1 in 2 confirmed cases (R0 = 1.25) to 1 in 40 confirmed cases (R0 = 3) before maximum occupancy is reached.ConclusionEven with highly effective mitigation strategies throughout the semester, inadequate pre-semester testing will lead to early and large surges of the disease and result in universities quickly reaching their isolation bed capacity. We therefore recommend NAT testing within one week of campus return. While this strategy is sufficient for delaying the timing of the outbreak, pre-semester testing would need to be implemented in conjunction with effective mitigation strategies to reduce the outbreak size.

scholarly journals How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Konstantin D. Pandl ◽  
Scott Thiebes ◽  
Manuel Schmidt-Kraepelin ◽  
Ali Sunyaev
Keyword(s):  
Disease Spread ◽  
Contact Tracing ◽  
Behavioral Characteristics ◽  
Policy Makers ◽  
Detection Range ◽  
Proximity Detection ◽  
Effective Technology ◽  
Different Types ◽  
Effectiveness And Efficiency ◽  
The Impact

AbstractTo combat the COVID-19 pandemic, many countries around the globe have adopted digital contact tracing apps. Various technologies exist to trace contacts that are potentially prone to different types of tracing errors. Here, we study the impact of different proximity detection ranges on the effectiveness and efficiency of digital contact tracing apps. Furthermore, we study a usage stop effect induced by a false positive quarantine. Our results reveal that policy makers should adjust digital contact tracing apps to the behavioral characteristics of a society. Based on this, the proximity detection range should at least cover the range of a disease spread, and be much wider in certain cases. The widely used Bluetooth Low Energy protocol may not necessarily be the most effective technology for contact tracing.

scholarly journals COVID-19 mitigation strategies were associated with decreases in other respiratory virus infections

2021 ◽  
Author(s):  
Sinha Pranay ◽  
Katherine Reifler ◽  
Michael Rossi ◽  
Manish Sagar
Keyword(s):  
Respiratory Virus ◽  
Respiratory Infections ◽  
Respiratory Viruses ◽  
Mitigation Strategies ◽  
Virus Infections ◽  
Time Period ◽  
Viral Respiratory Infections ◽  
Respiratory Virus Infections ◽  
Viral Respiratory

Abstract Detection of diverse respiratory viruses in Boston was around 80% lower after practices were instituted to limit COVID-19 spread compared to the same time period during the previous five years. Continuing the strategies that lower COVID-19 dissemination may be useful in decreasing the incidence of other viral respiratory infections.

scholarly journals Uridylate trapping, induction of UTP deficiency, and stimulation of pyrimidine synthesis de novo by d-galactosone

1982 ◽  
Vol 206 (1) ◽  
pp. 139-146 ◽  
Author(s):  
Dietrich O. R. Keppler ◽  
Christa Schulz-Holstege ◽  
Joachim Fauler ◽  
Karl A. Reiffen ◽  
Friedhelm Schneider
Keyword(s):  
Rat Liver ◽  
De Novo ◽  
Combined Treatment ◽  
Hepatoma Cells ◽  
Nucleotide Metabolism ◽  
Phosphate Deficiency ◽  
Initial Time ◽  
Pyrimidine Synthesis ◽  
Pyrimidine Nucleotide ◽  
Time Period

d-Galactosone (d-lyxo-2-hexosulose) is phosphorylated and metabolized to the uridine diphosphate derivative in AS-30D hepatoma cells and rat liver. These reactions were catalysed in vitro by galactokinase and hexose-1-phosphate uridylyltransferase. Nucleotide analyses by high-performance liquid chromatography and enzymic assays revealed that this galactose analogue interferes with cellular pyrimidine nucleotide metabolism leading to a deficiency of UTP. [14C]Uridine labelling of hepatoma cells indicated a division of [14C]uridylate from UTP into UDP-galactosone; the latter was formed at a rate of more than 1.7mmol×h−1×(kg AS-30D or liver wet wt.)−1. As a consequence of UTP deficiency, d-galactosone (1mmol/1 or 1mmol/kg body wt.) strongly enhanced the rate of pyrimidine synthesis de novo as evidenced by incorporation of 14CO2 into uridylate and by an expansion of the uridylate pool. This resulted in a doubling of the total acid-soluble uridylate pool within 70min in the hepatoma cells and within 110min in rat liver. Combined treatment of hepatoma cells with d-galactosone and N-(phosphonoacetyl)-l-aspartate, an inhibitor of aspartate carbamoyltransferase, prevented the expansion of the uridylate pool and led to a synergistic reduction of UTP to 10% of the content in control cells. Hepatic UTP deficiency was selective with respect to other nucleotide 5′-triphosphates but was associated with reduced contents of UDP-glucose, UDP-glucuronate, and UDP-N-acetylhexosamines. Isolation of the UDP derivative of d-galactosone revealed an extremely alkali-labile UDP-sugar, probably an isomerization product of UDP-galactosone, that was degraded by elimination of UDP with a half-life of 45min at pH7.5 and 37°C. The instability of UDP-galactosone may contribute in vivo to limit the time period of severe uridine phosphate deficiency in addition to the compensatory role of pyrimidine synthesis de novo. During the initial time period, however, d-galactosone is effective as a powerful uridylate-trapping sugar analogue.

scholarly journals A Data Driven Change-point Epidemic Model for Assessing the Impact of Large Gathering and Subsequent Movement Control Order on COVID-19 Spread in Malaysia

2020 ◽  
Author(s):  
Sarat C. Dass ◽  
Wai M. Kwok ◽  
Gavin J. Gibson ◽  
Balvinder S. Gill ◽  
Bala M. Sundram ◽  
...  
Keyword(s):  
Change Point ◽  
Movement Control ◽  
Disease Spread ◽  
Time Period ◽  
Before And After ◽  
Quantitative Understanding ◽  
Control Order ◽  
Short Time ◽  
The Impact ◽  
Second Wave

AbstractThe second wave of COVID-19 in Malaysia is largely attributed to a mass gathering held in Sri Petaling between February 27, 2020 and March 1, 2020, which contributed to an exponential rise of COVID-19 cases in the country. Starting March 18, 2020, the Malaysian government introduced four consecutive phases of a Movement Control Order (MCO) to stem the spread of COVID-19. The MCO was implemented through various non-pharmaceutical interventions (NPIs). The reported number of cases reached its peak by the first week of April and then started to reduce, hence proving the effectiveness of the MCO. To gain a quantitative understanding of the effect of MCO on the dynamics of COVID-19, this paper develops a class of mathematical models to capture the disease spread before and after MCO implementation in Malaysia. A heterogeneous variant of the Susceptible-Exposed-Infected-Recovered (SEIR) model is developed with additional compartments for asymptomatic transmission. Further, a change-point is incorporated to model the before and after disease dynamics, and is inferred based on data. Related statistical analyses for inference are developed in a Bayesian framework and are able to provide quantitative assessments of (1) the impact of the Sri Petaling gathering, and (2) the extent of decreasing transmission during the MCO period. The analysis here also quantitatively demonstrates how quickly transmission rates fall under effective NPI implemention within a short time period.

scholarly journals Locating the Epidemic Source in Complex Networks with Sparse Observers

2019 ◽  
Vol 9 (18) ◽  
pp. 3644 ◽  
Author(s):  
Xiang Li ◽  
Xiaojie Wang ◽  
Chengli Zhao ◽  
Xue Zhang ◽  
Dongyun Yi
Keyword(s):  
Complex Networks ◽  
Source Localization ◽  
Disease Spread ◽  
Initial Time ◽  
Epidemic Spread ◽  
Localization Accuracy ◽  
General Network ◽  
Maximum Spanning Tree ◽  
Comparison Algorithms ◽  
Empirical Networks

Epidemic source localization is one of the most meaningful areas of research in complex networks, which helps solve the problem of infectious disease spread. Limited by incomplete information of nodes and inevitable randomness of the spread process, locating the epidemic source becomes a little difficult. In this paper, we propose an efficient algorithm via Bayesian Estimation to locate the epidemic source and find the initial time in complex networks with sparse observers. By modeling the infected time of observers, we put forward a valid epidemic source localization method for tree network and further extend it to the general network via maximum spanning tree. The numerical analyses in synthetic networks and empirical networks show that our algorithm has a higher source localization accuracy than other comparison algorithms. In particular, when the randomness of the spread path enhances, our algorithm has a better performance. We believe that our method can provide an effective reference for epidemic spread and source localization in complex networks.

Design and Simulation Analysis of Vibration Energy Harvesting System Based on ADAMS

2019 ◽  
Author(s):  
Ziheng Zhu ◽  
Lin Xu ◽  
Mohamed A. A. Abdelkareem ◽  
Junyi Zou ◽  
Jia Mi
Keyword(s):  
Energy Harvesting ◽  
Vibration Energy ◽  
Bench Test ◽  
Test Results ◽  
Human Beings ◽  
Vibration Energy Harvesting ◽  
Wide Range ◽  
Harvesting Efficiency ◽  
Simulation Results ◽  
Energy Harvesting Efficiency

Abstract With the recent energy crisis, the new energy harvesting technologies have become one of the hot spots in engineering academic research and industrial applications. By its wide range of application fields, vibration energy harvesting technologies have been gradually developed and utilized in which an efficient and stable harvester technology is one of the recent key problems. In order to improve energy harvesting efficiency and reduce energy loss caused by motor inertial commutation, many mechanical structures or hydraulic structures that convert reciprocating vibration energy into single direction rotation of motor are proposed. Although these methods can improve energy harvesting efficiency, they can have negative effects in some cases, especially in the case of vibration energy harvesting from human beings. This paper proposes a vibration harvesting mechanism with mechanical rectification filter function applied to backpack. The prototype model of the system was established in SolidWorks and imported into ADAMS. Thereafter, dynamic analyses of mechanical rectification filtering characteristics and meshing characteristics of one-way clutch were simulated in ADAMS. Based on ADAMS, parametric design analysis and its influence on the mechanical rectification characteristics were investigated. The simulation results were validated by bench test results. Simulation results is done by ADAMS and the results match well with bench test results.

scholarly journals Topological and Thermodynamic Entropy Measures for COVID-19 Pandemic through Graph Theory

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1992
Author(s):  
G. Kirithiga Nandini ◽  
R. Sundara Rajan ◽  
A. Arul Shantrinal ◽  
T. M. Rajalaxmi ◽  
Indra Rajasingh ◽  
...  
Keyword(s):  
Biological Evolution ◽  
Genetic Network ◽  
Topological Indices ◽  
Mitigation Strategies ◽  
Contact Tracing ◽  
Topological Characterization ◽  
Christmas Trees ◽  
Global Pandemic ◽  
Mathematical Techniques ◽  
Underlying Mechanisms

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the global pandemic, coronavirus disease-2019 (COVID-19) which has resulted in 60.4 million infections and 1.42 million deaths worldwide. Mathematical models as an integral part of artificial intelligence are designed for contact tracing, genetic network analysis for uncovering the biological evolution of the virus, understanding the underlying mechanisms of the observed disease dynamics, evaluating mitigation strategies, and predicting the COVID-19 pandemic dynamics. This paper describes mathematical techniques to exploit and understand the progression of the pandemic through a topological characterization of underlying graphs. We have obtained several topological indices for various graphs of biological interest such as pandemic trees, Cayley trees, Christmas trees, and the corona product of Christmas trees and paths. We have also obtained an analytical expression for the thermodynamic entropies of pandemic trees as a function of R0, the reproduction number, and the level of spread, using the nested wreath product groups. Our plots of entropy and logarithms of topological indices of pandemic trees accentuate the underlying severity of COVID-19 over the 1918 Spanish flu pandemic.

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