scholarly journals Stochastic sampling effects favor manual over digital contact tracing

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Marco Mancastroppa ◽  
Claudio Castellano ◽  
Alessandro Vezzani ◽  
Raffaella Burioni
Keyword(s):  
Network Dynamics ◽  
Privacy Preserving ◽  
Equal Probability ◽  
Contact Tracing ◽  
Model Parameters ◽  
Agent Behavior ◽  
Stochastic Sampling ◽  
Multiple Contacts ◽  
Hybrid Protocols ◽  
Better Than

AbstractIsolation of symptomatic individuals, tracing and testing of their nonsymptomatic contacts are fundamental strategies for mitigating the current COVID-19 pandemic. The breaking of contagion chains relies on two complementary strategies: manual reconstruction of contacts based on interviews and a digital (app-based) privacy-preserving contact tracing. We compare their effectiveness using model parameters tailored to describe SARS-CoV-2 diffusion within the activity-driven model, a general empirically validated framework for network dynamics. We show that, even for equal probability of tracing a contact, manual tracing robustly performs better than the digital protocol, also taking into account the intrinsic delay and limited scalability of the manual procedure. This result is explained in terms of the stochastic sampling occurring during the case-by-case manual reconstruction of contacts, contrasted with the intrinsically prearranged nature of digital tracing, determined by the decision to adopt the app or not by each individual. The better performance of manual tracing is enhanced by heterogeneity in agent behavior: superspreaders not adopting the app are completely invisible to digital contact tracing, while they can be easily traced manually, due to their multiple contacts. We show that this intrinsic difference makes the manual procedure dominant in realistic hybrid protocols.

scholarly journals Privacy-preserving contact tracing in 5G-integrated and blockchain-based medical applications

2021 ◽  
Vol 77 ◽  
pp. 103520
Author(s):  
Can Zhang ◽  
Chang Xu ◽  
Kashif Sharif ◽  
Liehuang Zhu
Keyword(s):  
Privacy Preserving ◽  
Contact Tracing ◽  
Medical Applications

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.

scholarly journals Using the LIST model to Estimate the Effects of Contact Tracing on COVID-19 Endemic Equilibria in England and its Regions

2020 ◽  
Author(s):  
Rosalyn J. Moran ◽  
Alexander J. Billig ◽  
Maell Cullen ◽  
Adeel Razi ◽  
Jean Daunizeau ◽  
...  
Keyword(s):  
Endemic Equilibrium ◽  
Contact Tracing ◽  
Model Parameters ◽  
Infection Rates ◽  
Stable States ◽  
Medium Term ◽  
The Stability ◽  
Lower Death Rate ◽  
The Impact ◽  
List Model

AbstractGovernments across Europe are preparing for the emergence from lockdown, in phases, to prevent a resurgence in cases of COVID-19. Along with social distancing (SD) measures, contact tracing – find, track, trace and isolate (FTTI) policies are also being implemented. Here, we investigate FTTI policies in terms of their impact on the endemic equilibrium. We used a generative model – the dynamic causal ‘Location’, ‘Infection’, ‘Symptom’ and ‘Testing’ (LIST) model to identify testing, tracing, and quarantine requirements. We optimised LIST model parameters based on time series of daily reported cases and deaths of COVID-19 in England— and based upon reported cases in the nine regions of England and in all 150 upper tier local authorities. Using these optimised parameters, we forecasted infection rates and the impact of FTTI for each area—national, regional, and local. Predicting data from early June 2020, we find that under conditions of medium-term immunity, a ‘40%’ FTTI policy (or greater), could reach a distinct endemic equilibrium that produces a significantly lower death rate and a decrease in ICU occupancy. Considering regions of England in isolation, some regions could substantially reduce death rates with 20% efficacy. We characterise the accompanying endemic equilibria in terms of dynamical stability, observing bifurcation patterns whereby relatively small increases in FTTI efficacy result in stable states with reduced overall morbidity and mortality. These analyses suggest that FTTI will not only save lives, even if only partially effective, and could underwrite the stability of any endemic steady-state we manage to attain.

scholarly journals A New Flexible Version of the Lomax Distribution with Applications

2018 ◽  
Vol 7 (5) ◽  
pp. 120
Author(s):  
T. H. M. Abouelmagd
Keyword(s):  
Estimation Method ◽  
Good Alternative ◽  
Model Parameters ◽  
Data Sets ◽  
Suitable Model ◽  
Lifetime Data ◽  
New Model ◽  
The Right ◽  
New Distribution ◽  
Better Than

A new version of the Lomax model is introduced andstudied. The major justification for the practicality of the new model isbased on the wider use of the Lomax model. We are also motivated tointroduce the new model since the density of the new distribution exhibitsvarious important shapes such as the unimodal, the right skewed and the leftskewed. The new model can be viewed as a mixture of the exponentiated Lomaxdistribution. It can also be considered as a suitable model for fitting thesymmetric, left skewed, right skewed, and unimodal data sets. The maximumlikelihood estimation method is used to estimate the model parameters. Weprove empirically the importance and flexibility of the new model inmodeling two types of aircraft windshield lifetime data sets. The proposedlifetime model is much better than gamma Lomax, exponentiated Lomax, Lomaxand beta Lomax models so the new distribution is a good alternative to thesemodels in modeling aircraft windshield data.

scholarly journals Towards Large-Scale and Privacy-Preserving Contact Tracing in COVID-19 pandemic: A Blockchain Perspective

2020 ◽  
pp. 1-1
Author(s):  
Wenzhe Lv ◽  
Sheng Wu ◽  
Chunxiao Jiang ◽  
Yuanhao Cui ◽  
Xuesong Qiu ◽  
...  
Keyword(s):  
Large Scale ◽  
Privacy Preserving ◽  
Contact Tracing

scholarly journals Use of regional climate model simulations as input for hydrological models for the Hindukush-Karakorum-Himalaya region

2009 ◽  
Vol 13 (7) ◽  
pp. 1075-1089 ◽  
Author(s):  
M. Akhtar ◽  
N. Ahmad ◽  
M. J. Booij
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Model Parameters ◽  
Hydrological Models ◽  
Calibration And Validation ◽  
Model Experiments ◽  
Hbv Model ◽  
Better Than

Abstract. The most important climatological inputs required for the calibration and validation of hydrological models are temperature and precipitation that can be derived from observational records or alternatively from regional climate models (RCMs). In this paper, meteorological station observations and results of the PRECIS (Providing REgional Climate for Impact Studies) RCM driven by the outputs of reanalysis ERA 40 data and HadAM3P general circulation model (GCM) results are used as input in the hydrological model. The objective is to investigate the effect of precipitation and temperature simulated with the PRECIS RCM nested in these two data sets on discharge simulated with the HBV model for three river basins in the Hindukush-Karakorum-Himalaya (HKH) region. Six HBV model experiments are designed: HBV-Met, HBV-ERA and HBV-Had, HBV-MetCRU-corrected, HBV-ERABenchmark and HBV-HadBenchmark where HBV is driven by meteorological stations data, data from PRECIS nested in ERA-40 and HadAM3P, meteorological stations CRU corrected data, ERA-40 reanalysis and HadAM3P GCM data, respectively. Present day PRECIS simulations possess strong capacity to simulate spatial patterns of present day climate characteristics. However, also some quantitative biases exist in the HKH region, where PRECIS RCM simulations underestimate temperature and overestimate precipitation with respect to CRU observations. The calibration and validation results of the HBV model experiments show that the performance of HBV-Met is better than the HBV models driven by other data sources. However, using input data series from sources different from the data used in the model calibration shows that HBV-Had is more efficient than other models and HBV-Met has the least absolute relative error with respect to all other models. The uncertainties are higher in least efficient models (i.e. HBV-MetCRU-corrected and HBV-ERABenchmark) where the model parameters are also unrealistic. In terms of both robustness and uncertainty ranges the HBV models calibrated with PRECIS output performed better than other calibrated models except for HBV-Met which has shown a higher robustness. This suggests that in data sparse regions such as the HKH region data from regional climate models may be used as input in hydrological models for climate scenarios studies.

ObSecure Logging (OSLo): A Framework to Protect and Evaluate the Web Search Privacy in Health Care Domain

2019 ◽  
Vol 9 (6) ◽  
pp. 1181-1190 ◽  
Author(s):  
Mohib Ullah ◽  
Muhammad Arshad Islam ◽  
Rafiullah Khan ◽  
Muhammad Aleem ◽  
Muhammad Azhar Iqbal
Keyword(s):  
Web Search ◽  
Medical Information ◽  
Privacy Preserving ◽  
Exposure Level ◽  
Query Log ◽  
Search Queries ◽  
Internet Users ◽  
Privacy Analysis ◽  
The Web ◽  
Better Than

Users around the world send queries to the Web Search Engine (WSE) to retrieve data from the Internet. Users usually take primary assistance relating to medical information from WSE via search queries. The search queries relating to diseases and treatment is contemplated to be the most personal facts about the user. The search queries often contain identifiable information that can be linked back to the originator, which can compromise the privacy of a user. In this work, we are proposing a distributed privacy-preserving protocol (OSLo) that eliminates limitation in the existing distributed privacy-preserving protocols and a framework, which evaluates the privacy of a user. The OSLo framework asses the local privacy relative to the group of users involved in forwarding query to the WSE and the profile privacy against the profiling of WSE. The privacy analysis shows that the local privacy of a user directly depends on the size of the group and inversely on the number of compromised users. We have performed experiments to evaluate the profile privacy of a user using a privacy metric Profile Exposure Level. The OSLo is simulated with a subset of 1000 users of the AOL query log. The results show that OSLo performs better than the benchmark privacy-preserving protocol on the basis of privacy and delay. Additionally, results depict that the privacy of a user depends on the size of the group.

Hybrid Lateral Aerodynamic Modeling Based on WNN and Kernel Principal Components Feature Extraction

2013 ◽  
Vol 763 ◽  
pp. 242-245
Author(s):  
Xu Sheng Gan ◽  
Hao Lin Cui ◽  
Ya Rong Wu ◽  
Yue Bo Meng
Keyword(s):  
Neural Network ◽  
Principal Components ◽  
Model Parameters ◽  
Aerodynamic Modeling ◽  
Aerodynamic Model ◽  
Training Samples ◽  
Components Analysis ◽  
Kernel Principal Components Analysis ◽  
Basic Features ◽  
Better Than

In order to better describe the dynamic characteristics of aircraft through aerodynamic modeling, a Wavelet Neural Network (WNN) aerodynamic modeling method based on Kernel Principal Components Analysis (KPCA) is proposed. Firstly, the training samples are used to execute KPCA for extracting basic features of samples, and then using the extracted basic features, WNN aerodynamic model was established. The simulation result shows that, the modeling ability of the method proposed is better than that of another 3 methods. It can easily determine of model parameters. This enables it to be effective and feasible to establish the aerodynamic modeling for aircraft.

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