scholarly journals Aether - A Novel Method to Eliminate False Positives in Private Automated Contact Tracing

2020 ◽  
Author(s):  
Satvik Dasari
Keyword(s):  
False Positives ◽  
Contact Tracing ◽  
Novel Method

scholarly journals Genetic Algorithm based Predictive model for COVID 19 – Theoretical Model based on an evolutionary approach

2021 ◽  
Author(s):  
Srikanth Rangarajan ◽  
Srikanth Poranki ◽  
Bahgat Sammakia
Keyword(s):  
Genetic Algorithm ◽  
Real Time ◽  
State Of The Art ◽  
Contact Tracing ◽  
Reproductive Number ◽  
Time Data ◽  
Proposed Model ◽  
Fitness Value ◽  
Real Time Data ◽  
Novel Method

Abstract In this manuscript we propose a novel method that models the evolution, spread and transmission of COVID 19 pandemic. The proposed model is inspired partly from the evolutionary based state of the art genetic algorithm. The rate of virus evolution, spread and transmission of the COVID 19 and its associated recovery and death rate are modeled using the principle inspired from evolutionary algorithm. Furthermore, the interaction within a community and interaction outside the community is modeled. Using this model, the maximum healthcare threshold is fixed as a constraint. Our evolutionary based model distinguishes between individuals in the population depending on the severity of their symptoms/infection based on the fitness value of the individuals. There is a need to differentiate between virus infected diagnosed (Self isolated) and virus infected non-diagnosed (Highly interacting) sub populations/group. In this study the model results does not compare the number outcomes with any actual real time data based curves. However, the results from the model demonstrates that a strict lockdown, social-distancing measures in conjunction with more number of testing and contact tracing is required to flatten the ongoing COVID-19 pandemic curve. A reproductive number of 2.4 during the initial spread of virus is predicted from the model for the randomly considered population. The proposed model has the potential to be further fine-tuned and matched accurately against real time data.

scholarly journals On Analyzing Capnogram as a Novel Method for Screening COVID-19: A Review on Assessment Methods for COVID-19

Life ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1101
Author(s):  
M. B. Malarvili ◽  
Mushikiwabeza Alexie ◽  
Nadhira Dahari ◽  
Anhar Kamarudin
Keyword(s):  
Rapid Test ◽  
Diagnostic Methods ◽  
Contact Tracing ◽  
Early Screening ◽  
Gold Standard Method ◽  
Asthmatic Patients ◽  
Testing Tools ◽  
Novel Method ◽  
Novel Coronavirus ◽  
Carbon Dioxide Co2

In November 2019, the novel coronavirus disease COVID-19 was reported in Wuhan city, China, and was reported in other countries around the globe. COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Strategies such as contact tracing and a vaccination program have been imposed to keep COVID-19 under control. Furthermore, a fast, noninvasive and reliable testing device is needed urgently to detect COVID-19, so that contact can be isolated and ringfenced before the virus spreads. Although the reverse transcription polymerase chain reaction (RT-PCR) test is considered the gold standard method for the diagnosis of SARS-CoV-2 infection, this test presents some limitations which cause delays in detecting the disease. The antigen rapid test (ART) test, on the other hand, is faster and cheaper than PCR, but is less sensitive, and may limit SARS-CoV-2 detection. While other tests are being developed, accurate, noninvasive and easy-to-use testing tools are in high demand for the rapid and extensive diagnosis of the disease. Therefore, this paper reviews current diagnostic methods for COVID-19. Following this, we propose the use of expired carbon dioxide (CO2) as an early screening tool for SARS-CoV-2 infection. This system has already been developed and has been tested on asthmatic patients. It has been proven that expired CO2, also known as capnogram, can help differentiate between respiratory conditions and, therefore, could be used to detect SARS-CoV-2 infection, as it causes respiratory tract-related diseases.

scholarly journals Normalization of transposon-mutant library sequencing datasets to improve identification of conditionally essential genes

2016 ◽  
Vol 14 (03) ◽  
pp. 1642004 ◽  
Author(s):  
Michael A. DeJesus ◽  
Thomas R. Ioerger
Keyword(s):  
Geometric Distribution ◽  
Read Count ◽  
False Positives ◽  
Type I ◽  
Type I Errors ◽  
Coding Regions ◽  
Transposon Insertion ◽  
Novel Method ◽  
Insertion Sites ◽  
Generation Sequencing

Sequencing of transposon-mutant libraries using next-generation sequencing (TnSeq) has become a popular method for determining which genes and non-coding regions are essential for growth under various conditions in bacteria. For methods that rely on quantitative comparison of counts of reads at transposon insertion sites, proper normalization of TnSeq datasets is vitally important. Real TnSeq datasets are often noisy and exhibit a significant skew that can be dominated by high counts at a small number of sites (often for non-biological reasons). If two datasets that are not appropriately normalized are compared, it might cause the artifactual appearance of Differentially Essential (DE) genes in a statistical test, constituting type I errors (false positives). In this paper, we propose a novel method for normalization of TnSeq datasets that corrects for the skew of read-count distributions by fitting them to a Beta-Geometric distribution. We show that this read-count correction procedure reduces the number of false positives when comparing replicate datasets grown under the same conditions (for which no genuine differences in essentiality are expected). We compare these results to results obtained with other normalization procedures, and show that it results in greater reduction in the number of false positives. In addition we investigate the effects of normalization on the detection of DE genes.

scholarly journals Using next generation matrices to estimate the proportion of cases that are not detected in an outbreak

2021 ◽  
Author(s):  
H Juliette T Unwin ◽  
Anne Cori ◽  
Natsuko Imai ◽  
Katy A M Gaythorpe ◽  
Sangeeta Bhatia ◽  
...  
Keyword(s):  
New Zealand ◽  
Disease Outbreaks ◽  
Credible Interval ◽  
Contact Tracing ◽  
Surveillance Systems ◽  
Next Generation ◽  
Outbreak Response ◽  
Disease Response ◽  
Infectious Disease Outbreaks ◽  
Novel Method

Contact tracing, where exposed individuals are followed up to break ongoing transmission chains, is a key pillar of outbreak response for many infectious disease outbreaks, such as Ebola and SARS-CoV-2. Unfortunately, these systems are not fully effective, and cases can still go undetected as people may not know or remember all of their contacts or contacts may not be able to be traced. A large proportion of undetected cases suggests poor contact tracing and surveillance systems, which could be a potential area of improvement for a disease response. In this paper, we present a novel method for estimating the proportion of cases that are not detected during an outbreak. Our method uses next generation matrices that are parameterized by linked contact tracing and case line-lists. We use this method to investigate the proportion of undetected cases in two case studies: the SARS-CoV-2 outbreak in New Zealand during 2020 and the West African Ebola outbreak in Guinea during 2014. We estimate that only 6% of SARS-CoV-2 cases were not detected in New Zealand (95% credible interval: 1.31 - 16.7%), but over 60% of Ebola cases were not detected in Guinea (95% credible interval: 15 - 90%).

A novel method of partitioning regions in lungs and their usage in feature extraction for reducing false positives

2008 ◽  
Author(s):  
Mausumi Acharyya ◽  
Dinesh M. Siddu ◽  
Alexandra Manevitch ◽  
Jonathan Stoeckel
Keyword(s):  
Feature Extraction ◽  
False Positives ◽  
Novel Method

scholarly journals Predictive model for COVID 19 curve - An evolutionary approach

2020 ◽  
Author(s):  
Srikanth Rangarajan ◽  
Srikanth Poranki ◽  
Bahgat Sammakia
Keyword(s):  
Real Time ◽  
State Of The Art ◽  
Virus Evolution ◽  
Contact Tracing ◽  
Reproductive Number ◽  
Time Data ◽  
Proposed Model ◽  
Fitness Value ◽  
Real Time Data ◽  
Novel Method

Abstract In this manuscript we propose a novel method that models the evolution, spread and transmission of COVID 19 pandemic. The proposed model is inspired partly from the evolutionary based state of the art genetic algorithm. The rate of virus evolution, spread and transmission of the COVID 19 and its associated recovery and death rate are modeled using the principle inspired from evolutionary algorithm. Furthermore, the interaction within a community and interaction outside the community is modeled. Using this model, the maximum healthcare threshold is fixed as a constraint. Our evolutionary based model distinguishes between individuals in the population depending on the severity of their symptoms/infection based on the fitness value of the individuals. There is a need to differentiate between virus infected diagnosed (Self isolated) and virus infected non-diagnosed (Highly interacting) sub populations/group. In this study the model results does not compare the number outcomes with any actual real time data based curves. However, the results from the model demonstrates that a strict lockdown, social-distancing measures in conjunction with more number of testing and contact tracing is required to flatten the ongoing COVID-19 pandemic curve. A reproductive number of 2.4 during the initial spread of virus is predicted from the model for the randomly considered population. The proposed model has the potential to be further fine-tuned and matched accurately against real time data.

scholarly journals The short infectious period of COVID-19 indicates the efficiency of fast switching periodic protocols

2021 ◽  
Author(s):  
Eugenio Lippiello ◽  
Lucilla de Arcangelis ◽  
Giuseppe Petrillo
Keyword(s):  
Infected Individual ◽  
Accurate Estimate ◽  
Contact Tracing ◽  
Infectious Period ◽  
Average Value ◽  
Fast Switching ◽  
Generation Times ◽  
Italian Regions ◽  
Novel Method ◽  
One Year

Abstract The Covid-19 disease pandemic is showing the importance of an accurate quantification of transmissibility in order to design and tune public health responses. Transmissibility is usually quantified in terms of the reproduction number Rt, the average number of secondary cases caused by an infected individual. Here we show the central role also played by w(z), the distribution of generation times z, namely the time between successive infections in a transmission chain. We obtain an accurate estimate of w(z) by means of a novel method which allows us to simultaneously obtain its evaluation together with the measure of Rt, over the course of an epidemic, and the number of exogenous infected cases. We use one year of data from COVID-19 officially reported cases in the 21 Italian regions, since the first confirmed case on February 2020. We find that w(z) is a distribution very peaked around its average value z ≃ 6 days with a standard deviation σ smaller than one day. This estimate of σ is much smaller than previous ones obtained by means of contact tracing from the distribution of serial intervals. We perform extended numerical simulations to demonstrate that, because of the small value of σ, post-lockdown mitigation policies such as fast periodic switching and/or alternating quarantine can be extremely efficient.

The removal and morphology of intact biofilms from implanted venous access devices

1995 ◽  
Vol 53 ◽  
pp. 1020-1021
Author(s):  
M.A. Gregory ◽  
G.P. Hadley
Keyword(s):  
Patient Selection ◽  
Surgical Oncology ◽  
Venous Access ◽  
Common Procedure ◽  
Indwelling Catheters ◽  
Careful Patient ◽  
Novel Method ◽  
The Subject ◽  
Vascular Catheters ◽  
Venous Access Devices

The insertion of implanted venous access systems for children undergoing prolonged courses of chemotherapy has become a common procedure in pediatric surgical oncology. While not permanently implanted, the devices are expected to remain functional until cure of the primary disease is assured. Despite careful patient selection and standardised insertion and access techniques, some devices fail. The most commonly encountered problems are colonisation of the device with bacteria and catheter occlusion. Both of these difficulties relate to the development of a biofilm within the port and catheter. The morphology and evolution of biofilms in indwelling vascular catheters is the subject of ongoing investigation. To date, however, such investigations have been confined to the examination of fragments of biofilm scraped or sonicated from sections of catheter. This report describes a novel method for the extraction of intact biofilms from indwelling catheters.15 children with Wilm’s tumour and who had received venous implants were studied. Catheters were removed because of infection (n=6) or electively at the end of chemotherapy.

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