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Anthony Cooper
Anthony Cooper

Matteo Badder Than Bad


To be useful in ending lockdown measures, active viral tests need to maximise the sensitivity. High sensitivity reduces the chance of missing people who have the virus who may go on to infect others. There is an additional risk that an infected person who has been incorrectly told they do not have the disease, when in fact they do, may behave in a more reckless manner than if their disease status were uncertain.




Matteo Badder Than Bad


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The model simulates these rates of transition for a year, with a sensitivity and specificity of 90% for active virus tests. The specifics of all the runs are detailed in Table 5. Fig 8 shows five analyses, with increasing capacity for the active virus tests. In each, the 3 incremental transition rates are applied with a range of targeting capabilities. The value of 0.8 used previously represents an unrealistically extreme case of effective targeting. The PPV, as discussed above, has a greater dependence on the prevalence (at lower values) in the tested population than it does on the sensitivity of the tests, the same is true of the specificity and the NPV.


The 1% release rate scenario indicates that a slow release by itself is sufficient to lower peak infections, but potentially extends the duration of elevated infections. The first graph of the top row in Fig 8 shows that the slow release rate causes a plateau at a significantly lower number of infections compared to the other release rates. Poorly targeted tests at capacities less than 100,000 show similar consistent levels of infections. However, with a targeted test having a prevalence of 30% or more, the 1% release rate indicates that even with 50,000 tests per day continuous suppression of the infection may be possible.


Please submit your revised manuscript by Aug 21 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at gro.solp@enosolp. When you're ready to submit your revision, log on to and select the 'Submissions Needing Revision' folder to locate your manuscript file.


We believe R1 has not fully understood the research questions we are trying to explore and in this confusion asks for further justification of the simple model we present against more detailed SIR models that also include the dynamics of diagnosis and quarantine strategies. R1 suggests two papers, Lipsitch et al. (2003) and Giordano et al. (2020), as having better models than the one that we employ, however neither of these models would be able to answer the question we are trying to answer.


Lipsitch et al. implement quarantine in their model but do not incorporate the effects on the dynamics from imperfect testing, nor do they consider how the quality and scale of an available test affect the spread of a disease. Diagnostic uncertainty plays no part in the model they present. Likewise, Giordano et al. reduce diagnosis to two parameters, ε and θ, which confound test capacity, test targeting, and diagnostic uncertainty. Again, they do not investigate the role that diagnostic uncertainty plays in the spread of a disease. The analysis presented in our manuscript could be considered an in-depth look into these specific parameters using a simpler model than the SIDARTHE model used by Giordano et al. The intent of our paper is not to create a more sophisticated SIR model, but to investigate how diagnostic uncertainty affects the dynamics of an epidemic.


R1 takes issue with the amount of review material in the paper, something about which we are acutely self-conscious. But readers of the preprint have praised the fact that PPV and NPV are so clearly explained, and we believe this is essential to motivate the implications of the uncertainty about the model parameters. For instance, a journal club at Manchester University including Paul Klapper, Professor of Clinical Virology, strongly lauded the clarity of re-stating the definitions of these terms which are so important to the intent of the manuscript.( =1819 ) We feel this is a reasonable justification to retain the explanation of these terms which amounts to less than a page of the text.


We agree that the tone of the paper takes a more colloquial tone, and that popular media citations were frequent and distracting. We have taken pains to remove all of these citations other than those which we felt were important for the context of the manuscript. Tonally we feel that the manuscript achieves the desired purpose, and again we may point to the digestibility noted by the Manchester University journal club as supportive of the approach taken.


We thank the reviewers for their thoughtful comments. We feel the changes made to respond to their suggestions have significantly improved the manuscript, which we are pleased to resubmit for your consideration.


10 Feb 2021: Gray N,Calleja D,Wimbush A,Miralles-Dolz E,Gray A, et al. (2021) Correction: Is no test better than a bad test: Impact of diagnostic uncertainty on the spread of COVID-19.PLOS ONE 16(2): e0247129. View correction


The rapid development and scaling of new diagnostic systems invites error, particularly as labs are converted from other purposes and technicians are placed under pressure, and variation in test collection quality, reagent quality, sample preservation and storage, and sample registration and provenance. Assessing the magnitude of these errors on the performance of tests is challenging in real time. Point-of-care tests are not immune to these errors and are often seen as less accurate than laboratory based tests [36, 37].


This analysis does support the assertion that a bad test is potentially worse than no tests, but a good test is only effective in a carefully designed strategy. More is not necessarily better and over estimation of the test accuracy could be extremely detrimental.


  • This analysis is not a prediction; the numbers used in this analysis are estimates and the SIRQ model used is unlikely to be detailed enough to inform policy decisions. As such, the authors are not drawing firm conclusions about the absolute necessary capacity of tests. Nor do they wish to make specific statements about the necessary sensitivity or specificity of tests or the recommended rate of release from quarantine. The authors do, however, propose some conclusions that would broadly apply when testing and quarantining regimes are used to suppress epidemics, and therefore believe they should be considered by policy makers when designing strategies to tackle COVID-19.Diagnostic uncertainty can have a large effect on the dynamics of an epidemic. And, sensitivity, specificity, and the capacity for testing alone are not sufficient to design effective testing procedures. Policy makers need to be aware of the accuracy of the tests, the prevelence of the disease at increased granularity and the characteristics of the target population, when deciding on testing strategies.

  • Caution should be exercised in the use of antibody testing. Assuming that the prevalence of antibodies is low, it is unlikely antibody testing at any scale will support the end of lockdown measures. And, un-targeted antibody screening at the population level could cause more harm than good.

  • Antibody testing, with a high specificity may be useful on an individual basis, it has scientific value, and could reduce risk for key workers. But any belief that these tests would be useful to relax lockdown measures for the majority of the population is misguided.

  • The incremental relaxation to lockdown measures, with all else equal, would significantly dampen the increase in peak infections, by 1 order of magnitude with a faster relaxation, and 2 orders of magnitude with a slower relaxation.

  • As the prevelence of the disease is suppressed in different regions, it may be the case that small spikes in cases could be the result of false positives. This problem is potentially exacerbated by increased testing in localities in response to small increases in positive tests. Policy decisions that depend on small changes in the number of positive tests may, therefore, be flawed.

  • For infection screening to be used to relax quarantine measures the capacity needs to be sufficiently large but also well targeted to be effective. For example this could be achieved through effective contact tracing. Untargeted mass screening at any capacity would be ineffectual and may prolong the necessary implementation of lockdown measures.



At the end of Season 5, Kim suggested to Jimmy that they come up with a plan to sabotage Howard (Patrick Fabian). Yet, it felt as though Jimmy was less than eager to pursue such a feat with Kim who until recently, had been walking a fair and just path in her career. As their story picks back up, the couple is still in their hotel room used to escape potential harm from Lalo (Tony Dalton) and his crew after their tense exchange with the cartel man.


On the review aggregator website Rotten Tomatoes, 100% of ten reviews are positive, with an average rating of 9.0/10.[10] David Segal of The New York Times described the episode as "strong, twisty and gripping" and said the writing "must be hailed as a masterly curtain raiser, one that managed to pick up the story right where it was left, two years ago, and hurl it forward at a promising pace." Segal also praised Morris's direction in the opening scene but criticized Kim's con against Howard at the country club, calling it "dimmer and daffier than the rest of the show" and "pointlessly cruel".[11] Reviewing "Wine and Roses" and "Carrot and Stick" together, The A.V. Club's Kimberly Potts graded them with an "A" and gave positive notes to Gould's screenplay and the performances of the cast, especially those of Rhea Seehorn as Kim and Michael Mando as Nacho.[12]


An estimated 1.42 million viewers watched "Wine and Roses" during its first broadcast on AMC on April 18, 2022.[17] It was the number one cable drama premiere of 2022 at the time of its airing. According to AMC, the two-episode premiere generated over half a million engagements across social platforms including Twitter and Facebook, an increase of more than 60% compared to "Magic Man", the premiere of the show's fifth season. Social analytics tracker ListenFirst said a 10-hour national trend on Twitter made the show the "#1 television drama in social engagement, organic search, conversation, and content shares." The premiere also resulted in the biggest day of new subscriber sign-ups for AMC+.[18] 041b061a72


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