4 research outputs found
A pooled testing strategy for identifying SARS-CoV-2 at low prevalence
Suppressing infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will probably require the rapid identification and isolation of individuals infected with the virus on an ongoing basis. Reverse-transcription polymerase chain reaction (RT-PCR) tests are accurate but costly, which makes the regular testing of every individual expensive. These costs are a challenge for all countries around the world, but particularly for low-to-middle-income countries. Cost reductions can be achieved by pooling (or combining) subsamples and testing them in groups1-7. A balance must be struck between increasing the group size and retaining test sensitivity, as sample dilution increases the likelihood of false-negative test results for individuals with a low viral load in the sampled region at the time of the test8. Similarly, minimizing the number of tests to reduce costs must be balanced against minimizing the time that testing takes, to reduce the spread of the infection. Here we propose an algorithm for pooling subsamples based on the geometry of a hypercube that, at low prevalence, accurately identifies individuals infected with SARS-CoV-2 in a small number of tests and few rounds of testing. We discuss the optimal group size and explain why, given the highly infectious nature of the disease, largely parallel searches are preferred. We report proof-of-concept experiments in which a positive subsample was detected even when diluted 100-fold with negative subsamples (compared with 30-48-fold dilutions described in previous studies9-11). We quantify the loss of sensitivity due to dilution and discuss how it may be mitigated by the frequent re-testing of groups, for example. With the use of these methods, the cost of mass testing could be reduced by a large factor. At low prevalence, the costs decrease in rough proportion to the prevalence. Field trials of our approach are under way in Rwanda and South Africa. The use of group testing on a massive scale to monitor infection rates closely and continually in a population, along with the rapid and effective isolation of people with SARS-CoV-2 infections, provides a promising pathway towards the long-term control of coronavirus disease 2019 (COVID-19).info:eu-repo/semantics/publishe
Accounting for proof test data in Reliability Based Design Optimization
Thesis (MSc)--Stellenbosch University, 2015.ENGLISH ABSTRACT: Recent studies have shown that considering proof test data in a Reliability
Based Design Optimization (RBDO) environment can result in design improvement.
Proof testing involves the physical testing of each and every component
before it enters into service. Considering the proof test data as part of the
RBDO process allows for improvement of the original design, such as weight
savings, while preserving high reliability levels.
Composite Over-Wrapped Pressure Vessels (COPV) is used as an example
application of achieving weight savings while maintaining high reliability levels.
COPVs are light structures used to store pressurized fluids in space shuttles, the
international space station and other applications where they are maintained at
high pressure for extended periods of time. Given that each and every COPV
used in spacecraft is proof tested before entering service and any weight savings
on a spacecraft results in significant cost savings, this thesis put forward an
application of RBDO that accounts for proof test data in the design of a COPV.
The method developed in this thesis shows that, while maintaining high
levels of reliability, significant weight savings can be achieved by including
proof test data in the design process. Also, the method enables a designer
to have control over the magnitude of the proof test, making it possible to
also design the proof test itself depending on the desired level of reliability for
passing the proof test.
The implementation of the method is discussed in detail. The evaluation
of the reliability was based on the First Order Reliability Method (FORM)
supported by Monte Carlo Simulation. Also, the method is implemented in a
versatile way that allows the use of analytical as well as numerical (in the form
of finite element) models. Results show that additional weight savings can be
achieved by the inclusion of proof test data in the design process.AFRIKAANSE OPSOMMING: Onlangse studies het getoon dat die gebruik van ontwerp spesifieke proeftoets
data in betroubaarheids gebaseerde optimering (BGO) kan lei tot 'n
verbeterde ontwerp. BGO behels vele aspekte in die ontwerpsgebied. Die
toevoeging van proeftoets data in ontwerpsoptimering bring te weë; die toetsing
van 'n ontwerp en onderdele voor gebruik, die aangepaste en verbeterde
ontwerp en gewig-besparing met handhawing van hoë betroubaarsheidsvlakke.
'n Praktiese toepassing van die BGO tegniek behels die ontwerp van drukvatte
met saamgestelde materiaal bewapening. Die drukvatontwerp is 'n ligte
struktuur wat gebruik word in die berging van hoë druk vloeistowwe in bv.
in ruimtetuie, in die internasionale ruimtestasie en in ander toepassings waar
hoë druk oor 'n tydperk verlang word. Elke drukvat met saamgestelde materiaal
bewapening wat in ruimtevaartstelsels gebruik word, word geproeftoets
voor gebruik. In ruimte stelselontwerp lei massa besparing tot 'n toename in
loonvrag.
Die tesis beskryf 'n optimeringsmetode soos ontwikkel en gebaseer op 'n
BGO tegniek. Die metode word toegepas in die ontwerp van drukvatte met
saamgestelde materiaal bewapening. Die resultate toon dat die gebruik van
proeftoets data in massa besparing optimering onderhewig soos aan hoë betroubaarheidsvlakke
moontlik is. Verdermeer, die metode laat ook ontwerpers
toe om die proeftoetsvlak aan te pas om sodoende by ander betroubaarheidsvlakke
te toets.
In die tesis word die ontwikkeling en gebruik van die optimeringsmetode
uiteengelê. Die evaluering van betroubaarheidsvlakke is gebaseer op 'n eerste
orde betroubaarheids-tegniek wat geverifieer word met talle Monte Carlo
simulasie resultate. Die metode is ook so geskep dat beide analitiese sowel
as eindige element modelle gebruik kan word. Ten slotte, word 'n toepassing getoon waar resultate wys dat die gebruik van die optimeringsmetode met die
insluiting van proeftoets data wel massa besparing kan oplewer
Author Correction: A pooled testing strategy for identifying SARS-CoV-2 at low prevalence (Nature, (2021), 589, 7841, (276-280), 10.1038/s41586-020-2885-5)
In Fig. 2 of this Article, the Ct values for the orf1ab gene (shown in Fig. 2b) in samples B16121 and B16122 at 20×, 50× and 100× dilution were accidental duplications of those of the N gene (shown in Fig. 2a). The Ct values for orf1ab have been corrected in Fig. 2 of the original Article, and Fig. 1 of this Amendment shows the original and corrected Fig. 2b, for transparency. As B16121 and B16122 are both low-Ct samples, this change has no effect on our conclusion that typical samples are easily detected after 100-fold dilution. In Extended Data Table 2 of this Article, which presents the source data for Fig. 2, the orf1ab Ct values for sample B16121 were incorrectly given as 29, 29.74 and 30.54 for 20×, 50× and 100× dilution, respectively, instead of 31, 30.51 and 30.95, respectively. In addition, the orf1ab Ct values for sample B16122 were incorrectly given as 26.81, 27.75 and 29.07 for 20×, 50× and 100× dilution, respectively, instead of 28.5, 29.4 and 30.2, respectively. Extended Data Table 2 of the original Article has been corrected online. We thank T. Carey for drawing this error to our attention. The original Article has been corrected online. (Figure presented.).SCOPUS: er.jinfo:eu-repo/semantics/publishe