Talk:COVID-19 testing/Archive 2

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Will a country that only tests people admitted to hospitals have a lower "Positive / million people" than a country that tests everybody?

The column “positive/million people” will be higher in a country that only tests people admitted to hospitals, compared to a country that tests all citizens whether or not they are showing symptoms. The population of people being admitted to the hospital contains a higher percentage of people who actually have the disease, compared to the entire population of the country. Those admitted to the hospital are not a random cross section of the population but rather consist of those who have symptoms, and a group of people with symptoms will have a higher percentage of infected people than a group of people, most of whom do not have symptoms. A higher positive / hundred tests, means that there must also be a higher “positive / million people.”

Let’s take Albania. The column “Pos/mill” bears the same ratio to “Positive” as “Tests/mill” bears to “Tests,” which equals roughly 213. Let’s assume that this example represents a country that only tests people admitted to hospitals. Now let’s assume that the same country performed the same number of tests but tested everybody. They would have a lower number testing positive. Let’s assume 305 (about half). The number in the "% (Percentage of positive tests)" column would be roughly 5%, the number of “Tests/mill” would be the same, the number of “Pos/mill” would be roughly 107. So the “Pos/mill” is higher in the “only hospital testing” example. Swood100 (talk) 17:21, 22 April 2020 (UTC)

@Swood100:A country where only the hospitalized are tested will have a higher real pos/million ratio than another country with wide range of tests provided that those two countries have the same ratio on the table. And pos/million ratio is lower on the table in a country with limited tests provided that two countries have the same real ratio.
I think that's the fundamental confusion of the statement. As it state that In countries with similar spread of infection, I will assume that means countries with similar real ratio. Atzhh (talk) 19:32, 22 April 2020 (UTC)
Atzhh: What is the difference between “real ratio” and “ratio on the table”? The two examples I gave both involve Albania, which has the same spread of infection as itself. The only difference is which portion of the population is being sampled, the portion with a higher rate of infection or the portion with the lower rate of infection. Can you give me an example, using Albania for both, in which the sample with the lower rate of infection results in a higher pos/million figure? How would such a thing make sense? Swood100 (talk) 22:33, 22 April 2020 (UTC)
@Swood100: Let's speak in this way. Two countries A and B both have 1M population and 10K infections, so both have real ratio 10k per million. Assuming among 10k, 2k think they should go to hospital. A tested everyone who go to hospital and B tested everyone in the country. Then A could caught 2k positives and have the ratio on the table 2k per million and B could caught 10k positives with the ratio on the table 10k per million. The other way around, if both countries detect 2k positives (so ratio on table 2k per million), since B have tested everyone it's real ratio is again 2k. But A haven't caught anyone asymptomatic, the real infections is higher than 2k and thus real ratio is higher as well.
I read your argument again and realize that what you messed up is really the following: When a country is considering testing everyone, that means they can test everyone who need a test at hospital at first. They are not strategies of same amount of tests. A country could have a wide range of tests only if its capacity surplus its critical needs.Atzhh (talk) 23:34, 22 April 2020 (UTC)
Atzhh: Skip the following and read my response to UnladenSwallow below. Swood100 (talk) 17:53, 23 April 2020 (UTC)
Atzhh: Country B tests a sample of 1000 people at random from the community. B finds that 100 people in that sample are infected. This is 10%, since it is testing a truly random sample. Since the population is 1,000,000, B reports that the pos / million in that country is 100,000 / million.
A tests a sample of 1000 people who go to the hospital. Since A’s sample includes a higher proportion of people who are infected A finds that 300 people in that sample are infected. This is 30%. Since the population is 1,000,000 A reports that the pos / million in that country is 300,000 / million.
The pos / million is higher for the country whose sample has a higher rate of infection: those admitted to hospitals. Swood100 (talk) 14:52, 23 April 2020 (UTC)
@Swood100: Consider two countries with similar spread of infection: Country A with 100 million people that only tests people admitted to hospitals and Country B with 10 million people that tests all citizens whether or not they are showing symptoms. Let's assume the spread of infection is 1%. So there are 1 million infected people in Country A and 100,000 infected people in Country B. Further, let's assume that 75% are asymptomatic, 15% are mild cases, and 10% require hospitalization (the exact rates are not important, it just makes it easier to follow the argument). So there are 750,000 asymptomatic, 150,000 mild cases, and 100,000 hospitalized in Country A. Since Country A only tests those hospitalized, it performs 100,000 tests and gets 100,000 positives, which works out to 1,000 positives / million population. Country B has 75,000 asymptomatic, 15,000 mild cases, and 10,000 hospitalized. It tests all hospitalized (10,000 positives), some mild cases (let's say 1⁄3 for 5,000 positives), and some asymptomatic cases via contact tracing (let's say 1⁄15 for 5,000 positives) for a total of 20,000 positives, which works out to 2,000 positives / million population. As you can see, even though the population of Country A is 10 times that of Country B, and the countries have similar spread of infection, the positives / million population figure for Country B is actually 2 times that for Country A. That's because Country B does not restrict itself to testing only hospitalized cases and thus catches a larger share of infections. — UnladenSwallow (talk) 23:43, 22 April 2020 (UTC)
UnladenSwallow: I created the new section before I saw the existing section. I think I see what you’re saying. The column pos/million only has meaning in relation to its own tests/million and a comparison with any other country’s pos/million is meaningless because of the difference in population sizes. You’re right that for your Country A it comes to 1,000 pos /million but that is misleading since the typical reader will assume this means that the testing sample showed that 0.1% of the population is positive whereas the real number is 100%.
I don’t think that countries that only test people admitted to hospitals always have a lower pos/million. In your example if Country B created a truly random sample of 100,000 tests it would find 1,000 positives since its true rate of infection is 1%. This would give it a test/mill of 10,000 and a pos/mill of 100.
I think that the column pos/mill creates more confusion than clarity. I would remove that column entirely. In the alternative I would try to provide some explanation for what it means but I can’t think of any explanation that either could easily be understood or that justifies that column’s presence in the table. I would replace Tests/mill with “% of population tested.” Swood100 (talk) 17:53, 23 April 2020 (UTC)Swood100 (talk) 19:05, 23 April 2020 (UTC)
Is this your table? Who decides what format it will have? If you agree with my change recommendations I'd be happy to help with the changes. Swood100 (talk) 21:26, 23 April 2020 (UTC)
@Swood100:
1. …that is misleading since the typical reader will assume this means that the testing sample showed that 0.1% of the population is positive whereas the real number is 100% But it does mean that. Let me try to explain this again. Among the population of Country A there are 0.75% asymptomatic cases, 0.15% mild cases, and 0.1% severe (hospitalized) cases. Country B has similar spread of infection, so among the population of Country B there are also 0.75% asymptomatic cases, 0.15% mild cases, and 0.1% severe cases. Since Country A only tests hospitalized cases, there's no way it will register more than 0.1% positive cases (= 1,000 positive / million people). Meanwhile, Country B, depending on how extensive its testing is, can potentially register up to 0.75% + 0.15% + 0.1% = 1% cases (= 10,000 positive / million people). In practice, it won't "catch them all", but it will still register more percentage-wise than Country A.
2. …if Country B created a truly random sample of 100,000 tests it would find 1,000 positives since its true rate of infection is 1%. This would give it a test/mill of 10,000 and a pos/mill of 100. That's right, but real countries are not doing random testing. They test hospitalized cases first, symptomatic cases second, possible contacts of confirmed cases third, high-risk employees (doctors, supermarket employees, etc.) fourth, and anyone who wants tested fifth (to the best of my knowledge, this last stage is only being done by Iceland and South Korea). More importantly, there's no mention of any limits on testing in the statement in question. Countries A and B both test as much as they want, but Country A limits itself to only testing hospitalized cases (cf. 7 below).
3. I think that the column pos/mill creates more confusion than clarity. I would remove that column entirely. The column was requested by multiple editors—that's why I've added it. I think its meaning is pretty clear: it's the number of positive cases per capita (expressed in millionths of country's population).
4. I would replace Tests/mill with “% of population tested.” That would result in many zeros after the decimal point for most countries. When the numbers grow sufficiently, it will make sense to change these columns to "/ 100,000 people", then "/ 10,000 people", etc.
5. Is this your table? Only pages starting with User:EditorsName may be considered "owned" by an editor (with certain limitations). Everything else belongs to everyone. Who decides what format it will have? Such decisions are supposed to be made collectively as a result of discussions on the tables' talk pages Template talk:COVID-19 testing by country and Template talk:COVID-19 testing by country subdivision. Since there were almost no discussions, I had to make those decisions myself based on suggestions of other editors.
6. When I first saw 77.59.125.228's comment in § Testing policy influence, I had a reaction similar to yours: wait, what? It took me some time to think it through. The statement is certainly not obvious.
7. If the amount of tests per capita is fixed and very limited (say, 100,000 for Country A and 10,000 for Country B in my example above), then your interpretation is actually the right one: Country A, by spending its test "budget" only on hospitals, will get a higher "Positive / million people" figure than Country B. But the statement in question doesn't say that the amount of tests is fixed.
8. Perhaps we can re-write the statement like this:
The figures below are influenced by a country's testing availability and policy. Among countries that have the same spread of infection:
  1. Countries that experience test shortages and therefore only test hospitalized cases, will have higher % (Percentage of positive tests) and lower Positive / million people figures, because they won't be registering mild and asymptomatic cases.
  2. Countries that have unlimited tests, but only test people with symptoms and those who were in contact with confirmed cases, will have mid-range % (Percentage of positive tests) and Positive / million people figures.
  3. Countries that have unlimited tests and test anyone who wants tested, will have lower % (Percentage of positive tests) and higher Positive / million people figures, because they will be registering the most asymptomatic cases.
— UnladenSwallow (talk) 14:47, 24 April 2020 (UTC)
UnladenSwallow: Take two countries that are like Country A in every respect except for whom they test. A1 only tests hospital admissions, A2 conducts its tests without regard to the symptoms of the person tested (and therefore conducts more random testing). At the beginning of testing, and as long as they perform the same number of tests A1 will have a greater Positive/million people. At some point A1 will run into a testing wall since it is limited to testing those who are symptomatic and who show up at the hospital. A2 will not have that wall and will go on testing and it will have a greater number of positives to find since it is not limited to those who are symptomatic. When A2 starts conducting a greater number of tests we have introduced a second difference between the countries, one known to result in a higher pos/mill. Eventually the number of positives A2 finds will exceed the number found by A1 and at that point its pos/mill will become larger.
The original intent of the explanatory text was simply to deal with the Percentage of positive tests issue, which will always favor A1. To try to incorporate the pos/mill issue into this would require that we discuss not just who is tested but how many tests are performed. We would have to explain the above crossover point or at least we couldn’t say that A1 always has a lower pos/mill since until it falls behind in number of tests performed that won’t be true. How about the following, which splits it up into two sentences, each of which only deals with one concept:
If two countries are alike in every respect, including having the same spread of infection, the country that only tests people admitted to hospitals will have a higher figure for “% (Percentage of positive tests)” than a country that tests all citizens, whether or not they are showing symptoms.
If two countries are alike in every respect, including which people they test, the one that tests more people will have a higher “Positive / million people.” Swood100 (talk) 14:02, 27 April 2020 (UTC)
@UnladenSwallow: Did you see my suggestion above? Swood100 (talk) 20:54, 28 April 2020 (UTC)
@Swood100: Apologies for the delayed response.
The first sentence in your suggestion is misleading without explicitly stating that the countries conduct the same number of tests.
But that does not matter because, again, real countries do not test people randomly. As I have explained in 2 above, They test hospitalized cases first, symptomatic cases second, possible contacts of confirmed cases third, high-risk employees (doctors, supermarket employees, etc.) fourth, and anyone who wants tested fifth (to the best of my knowledge, this last stage is only being done by Iceland and South Korea). Even countries that are casting a wider net now have started out by testing only cases with serious symptoms (plus their contacts and doctors). There are no countries like A2 in your example which would start out by doing completely random tests.
Honestly, I'm leaning towards deleting the section lede entirely—it's not supported by the given reference, and we shouldn't be adding original research per WP:OR. — UnladenSwallow (talk) 22:34, 3 May 2020 (UTC)
@UnladenSwallow: But the number of tests conducted is not relevant to the first sentence. One country with limited access to tests will typically test only the symptomatic. The second country with greater access to tests may start with the symptomatic and, as you say, expand out to those not showing symptoms. As soon as the second country starts testing people without symptoms (the condition stated in the text) it will have a lower Percentage of positive tests, which is caused by sampling/selection bias. What follows is the text that I think explains the concept here although it is talking about fatalities per case instead of infections per test. Does that make it original research? How about a reference to a generic explanation of selection bias?
"The main hypothesis considered was that varying degrees of sampling bias in COVID-19 testing are significantly impacting CFR estimates. Whilst some countries have focused COVID-19 testing mostly on the seriously ill, some other countries have tested much more widely. As it is known that most people who contract the virus only show mild symptoms or are asymptomatic, this varying approach to testing is likely significantly impacting CFR estimates. Countries that have tested more widely will likely have more accurate CFR estimates, as their testing involves less sampling bias. Conversely, countries that have focused their testing more narrowly on the seriously ill will likely be significantly under-estimating reported cases, and thus will be significantly overestimating CFRs calculated using these reported cases (reported deaths divided by reported cases)."
As far as the second sentence is concerned, if there are two countries identical in every respect, the one that does more testing will have a higher number of positive tests and therefore by definition a greater “Positive / million people.” If a reference is needed for that then is a reference needed for the “Positive / million people” calculation itself, and for each of the other calculations for that matter?
By the way, it is not invariably true that all countries begin their testing on those showing symptoms. The very first infection diagnosed in Italy was in the town of Vò. They immediately imposed a lockdown and conducted testing on a large portion of the population. So Italy did its first testing without regard to whether the people being tested were showing symptoms. Swood100 (talk) 01:16, 4 May 2020 (UTC)
@Swood100: But the number of tests conducted is not relevant to the first sentence. My apologies, I have erroneously read "% (Percentage of positive tests)" as "Positive / million people". The first sentence is correct.
Does that make it original research? I don't know whether this text is original research or not because you haven't supplied a reference for it. But we can't use it for the explanation of testing sampling bias anyway as it talks about CFR sampling bias. We need a reliable source that explicitly talks about testing sampling bias. Maybe try searching for one via Google Scholar?
As far as the second sentence is concerned, if there are two countries identical in every respect, the one that does more testing will have a higher number of positive tests and therefore by definition a greater “Positive / million people.” Well, strictly speaking, if a hypothetical country A3 was doing somewhat more testing (but not much more) and never tested people in hospitals, then it would have a lower number of positive tests. But this is such a contrived example that we can safely ignore it. So yes, I agree.
…is a reference needed for the “Positive / million people” calculation itself, and for each of the other calculations for that matter? Routine calculations are exempted from WP:OR per WP:CALC.
So Italy did its first testing without regard to whether the people being tested were showing symptoms. Point taken.
I still think it would be more useful to explain testing sample bias in terms of shortage vs. plentiful supply of tests, because that's the main factor in the real world. Countries that don't have enough tests have distorted figures (with rare exceptions, they don't do random testing because they need to focus their resources on symptomatic cases, contacts and doctors), while countries with plenty of tests have figures that are closer or even converge to their true infection rates. But again, we need a reliable source that says that. — UnladenSwallow (talk) 16:16, 4 May 2020 (UTC)
@UnladenSwallow: I don't know whether this text is original research or not because you haven't supplied a reference for it.
That came from the original reference. However, this article seems to explain the concept appropriately.
I still think it would be more useful to explain testing sample bias in terms of shortage vs. plentiful supply of tests, because that's the main factor in the real world.
How about the following:
If two countries are alike in every respect, including having the same spread of infection, and one of them has a shortage of testing capability it may only test those showing symptoms while the other country having greater access to testing may test both those showing symptoms and others chosen at random. A country that only tests people showing symptoms will have a higher figure for “% (Percentage of positive tests)” than a country that also tests people chosen at random. — Swood100 (talk) 17:59, 4 May 2020 (UTC)
Well, strictly speaking, if a hypothetical country A3 was doing somewhat more testing (but not much more) and never tested people in hospitals, then it would have a lower number of positive tests.
But that seems to be excluded by the phrase "including which people they test." — Swood100 (talk) 18:10, 4 May 2020 (UTC)
@Swood100: Apologies for the delayed response. I have no reservations about this version. The article by The Conversation explains the problem well, great find. Thank you for the discussion. — UnladenSwallow (talk) 20:36, 11 May 2020 (UTC)

testing a group at a time

As I've yet to read the article, I don't know if this is in it already; but I heard some news—maybe less than 72 hours ago—on CBC Radio that somewhere in the US that for people in presumed low-risked groups they are mixing their samples, 10 to 1, and testing it as one sample. If the combined sample shows positive, then each person is tested individually. If it's negative, it's presumed none have the virus, and are all passed. This could multiply the number of people that can be tested. I'll probably search for sources later. DMBFFF (talk) 15:37, 12 May 2020 (UTC)

Edit request Cypriot data

For the Cypriot statistics the number of cases reported on https://covid19.ucy.ac.cy/ relate to those in the unoccupied region of Cyprus (as can be viewed on the map in the website), whilst the denominator used to estimate the tests per million appears to consider the population in both the south unoccupied region and Turkish occupied region in the north. For the nominator and denominator to be consistent a population of 875,900 would be more appropriate based on official statistics from 2018. I'm providing links for references of the population:

Official Demographic statistics 2018 (page 4): https://www.mof.gov.cy/mof/cystat/statistics.nsf/All/6C25304C1E70C304C2257833003432B3/$file/Demographic_Statistics_Results-2018-EN-291119.pdf?OpenElement Official government epidemiology report as of 28 Apr, page 15 (in Greek): https://www.pio.gov.cy/coronavirus/pdf/en7052020.pdf Bsufiw (talk) 09:33, 9 May 2020 (UTC)

 Not done for now: please establish a consensus for this alteration before using the {{edit semi-protected}} template. I don’t see any problem with using the population of the whole island in the denominator. Most people are referring to both countries when they say “Cyprus,” not just the Republic of Cyprus. There are gaps in the data for reported cases in a lot of places; that’s part of what makes them “reported.” Instead of redefining the group of people we’re referring to, I believe we should focus on filling in the gaps in reported cases. I think data from Northern Cyprus would be useful if you can find it, and adding it to the article likely wouldn’t require a consensus. If you still want to make this change instead, you should establish a consensus on this talk page first. — Tartan357  (Talk) 16:03, 10 May 2020 (UTC)
Data from Northern Cyprus are published here: https://saglik.gov.ct.tr/COVID-19-GENEL-DURUM — Preceding unsigned comment added by Bsufiw (talk • contribs) 16:51, 10 May 2020 (UTC)
 Not done for now: Please follow Tartan357's instructions about attaining a consensus before submitting (or re-opening) another edit request. Thank you. Donna Spencertalk-to-me⛅ 01:48, 13 May 2020 (UTC)
@DonSpencer1: They did follow my suggestion to obtain Northern Cypriot data, so I reopened the request for them. I just haven’t gotten around to implementing it yet. Feel free to make the edit if you want. — Tartan357  (Talk) 05:35, 13 May 2020 (UTC)
check Partially implemented: Some parts of you edits have been added to the article. Thanks, Tartan357. Donna Spencertalk-to-me⛅ 14:22, 13 May 2020 (UTC)
@Bsufiw, Tartan357, and DonSpencer1: This is the wrong page to discuss the addition of Northern Cyprus to the table. The discussion should be held at Template talk:COVID-19 testing by country. — UnladenSwallow (talk) 21:44, 13 May 2020 (UTC)
@UnladenSwallow: We’re not discussing the creation of a new entry for Northern Cyprus - just the addition of data from Northern Cyprus to the “Cyprus” entry, which already contained a population denominator for the whole island, as pointed out by the original requester. — Tartan357  (Talk) 22:49, 13 May 2020 (UTC)
Perhaps there is some confusion here. I added the data from Northern Cyprus in a new entry for Northern Cyprus. More than happy to self revert. The data is already on Template:COVID-19 testing by country so if needed it can be moved easily. If so, I'll let another editor coordinate this to make sure its done according to request. @Bsufiw: let us know if we properly addressed your request after its completed. Thanks. Donna Spencertalk-to-me⛅ 23:00, 13 May 2020 (UTC)
@Tartan357: We’re not discussing the creation of a new entry for Northern Cyprus - just the addition of data from Northern Cyprus to the “Cyprus” entry It doesn't matter. The discussion should take place at Template talk:COVID-19 testing by country. That's where the table is discussed. — UnladenSwallow (talk) 10:57, 14 May 2020 (UTC)
@UnladenSwallow: Sure, but this was a simple edit request, not a discussion to establish a consensus. And it’s already been closed. Please remember that editors who aren’t auto-confirmed are very new to the encyclopedia and can’t be expected to know all the rules. This type of response scares off potentially useful contributors. There’s no reason to complain - the issue is moot. Policies are meant to be applied with common sense, and are flexible. Please see WP:Wikilawyering for more information. You can simply move this entire section over to the correct talk page if you want. I highly doubt anyone would take issue with that. — Tartan357  (Talk) 13:28, 14 May 2020 (UTC)
@Tartan357: Sure, but this was a simple edit request, not a discussion to establish a consensus. It was a simple edit request, indeed, and I wasn't planning on writing anything until you wrote this: If you still want to make this change instead, you should establish a consensus on this talk page first. Which is wrong, because the consensus should not be established on this talk page, but at Template talk:COVID-19 testing by country, hence my comment.
This type of response scares off potentially useful contributors. There is nothing "scary" in my response. In fact, it directs users to a page where they can make their edit themselves (Template:COVID-19 testing by country is not protected or semi-protected). Sometimes I fulfil edit requests here (1, 2, 3, 4, 5, 6), and other times I direct users to the template page (1, 2, 3, 4, 5)—there's nothing wrong or "scary" with that.
Please see WP:Wikilawyering for more information. No wikilawyering on my part, just correcting your incorrect advice to Bsufiw.
Also, please stop changing the indentation of my original comment—it's not a reply to DonSpencer1's comment. Indentation levels should only be changed when they are clearly wrong (e.g., a level 6 reply to a level 2 comment). Thank you! — UnladenSwallow (talk) 15:18, 14 May 2020 (UTC)

Title should be changed

COVID-19 is the name of the respiratory disease caused by the SARS-CoV-2 virus. The tests in question are not for the disease. They are testing for the virus. Most people who test positive do not develop severe COVID-19 symptoms. Many do not develop symptoms at all. The title should be changed to "SARS-CoV-2 testing" or 2019 Novel Coronavirus Testing" or something similar. --2604:2D80:D586:3000:FDFB:2F9D:EC2E:FF53 (talk) 01:52, 2 May 2020 (UTC)

Not all the tests are for the virus. Antibody tests are for antibodies generated in response to the virus. Swood100 (talk) 17:13, 3 May 2020 (UTC)
And CT scans are tests for the disease. Doc James (talk · contribs · email) 10:35, 6 May 2020 (UTC)
And I expect that not every nation tests the same way, to the same trigger level or reliability/quality of processing, even if it’s the same kind of test. This one seems minor compared to if the table is showing CT oranges the same as antibody apples. Cheers Markbassett (talk) 16:20, 15 May 2020 (UTC)

Why is the NEOKIT-COVID-19 not included on the Isothermal nucleic amplification section?

Argentina developed a Loop-mediated isothermal amplification based test named NEOKIT-COVID-19 which got approved by the National Administration of Medications, Food and Medical technology (abbreviated ANMAT in Spanish).

Sources here:

Questions:
  • One source says that it has a "certainty percentage" of 98%, but is that sensitivity or specificity? That same article says that that it detects the "presence of the antibody" but a Loop-mediated isothermal amplification test does not test for antibodies.
  • This source says that "this procedure needs a laboratory with biosafety cabinets." Is that really the case, because a Biosafety cabinet requirement means that the samples have to be sent off to a lab which adds a few days to the process, rendering the one hour actual testing time somewhat illusory. Yet this source calls it a "portable test kit." So it's portable but can only be used in a place with a Biosafety cabinet? This source shows a picture. Everything needed is in that little box?
  • This may supply some useful information to someone who speaks Spanish.
  • Is there any validation information available from the National Administration of Medicines, Food and Medical Technology (ANMAT)? It's odd that the developers have not made available any technical information. — Swood100 (talk) 20:18, 21 May 2020 (UTC)

Was the Stanford antibody test of MLB employees led by Jay Bhattacharya?

LetterOpener (talk · contribs) — It is true, as you point out, that the cited sfchronicle.com article reports that Bianca Mulaney, a Stanford medical student, was the lead author of the study. But there is a difference between who authored the study and who lead the study. I have added two additional references to support the proposition that Bhattacharya was the leader. In addition to those there are stories in The Athletic and sanfrancisco.cbslocal.com that report the same thing.

Then there are numerous articles like this one in smithsonianmag to the effect that Bhattacharya will be the one to analyze and publish the data, as well as the one to publish a peer-reviewed paper. Such articles indicate that it is actually his study. It would be very unusual for Mulaney, a medical student, to genuinely be the leader of such a study instead of a faculty member at the medical school such as Bhattacharya, even if she was listed as the lead author, and I can’t find any sources to that effect. — Swood100 (talk) 19:22, 20 May 2020 (UTC)

@Swood100: I concede in your two additional cited references that Dr. Jay Bhattacharya is leading the study, rather than lead author Bianca Mulaney. However, the listing of either the lead author or the leader of said study is likely irrelevant to the paragraph unless Dr. Bhattacharya being the lead is noteworthy enough to affect the results of the study. A quick search of Wikipedia does not turn up a page on the doctor, and this doctor does not appear to meet Wikipedia's notability standard for this study alone or for the other publications on their Stanford page. Also, the direct external linking to the external Stanford page "https://healthpolicy.fsi.stanford.edu/people/jay_bhattacharya" should not be done inline in the body of the article. See Wikipedia:Manual_of_Style#External_links. LetterOpener (talk) 04:56, 21 May 2020 (UTC)
@LetterOpener: The Wikipedia's notability standards relate to whether a topic deserves its own article. As far as that is concerned Bhattacharya is cited 8824 times in scholarly journals which, together with the positions he holds would likely qualify him for his own page. He has been much in the news recently concerning another COVID-19 study dealing with Santa Clara county. He was the principal source mentioned by all of the numerous articles about this study that I read. What is the objection to mentioning him by name (without the inline link)? — Swood100 (talk) 15:50, 21 May 2020 (UTC)
@Swood100: Number of citations in Google Scholar does not seem to be a comparable metric on how notable a person is. Both Deborah Birx and Anthony Fauci have zero results in Google Scholar, but they both have large amounts in Scolia. Their respective Scolia totals - Fauci: 1027, Birx: 224, and Bhattacharya: 3. I see your desire to include Dr. Bhattacharya, and I would encourage you to make him a Wikipedia page and use that as an inline internal link. Please include his Google Scholar results and a citation to his Stanford pages on that Wikipedia page when you create it. In the meantime, let's remove the external link because it is encouraging other inline external links on the page such as to FDA website, HHS website, and "additional testing sites can be found here as well as at state and local health department websites." —  LetterOpener (talk) 22:40, 21 May 2020 (UTC)

@LetterOpener: Also, why did you remove the sentence “Only 4.7% of the participants were age 65 or older”? This is a weakness of the study, in that there were so few old people, and was given by the authors as a possible reason why they received the results they did – why they found a rate of 0.7% whereas in a previous study they had found between 2.5 and 4.2% of Santa Clara County residents. It also could possibly explain why such a high percentage of those infected were asymptomatic. — Swood100 (talk) 20:33, 20 May 2020 (UTC)

@Swood100: The 4.7% sentence was the middle of three consecutive sentences with different percentages, and the first and third sentences talked about the employees with positive test results, while the sentence in question talked about all participants. "In a study led by Dr. Jay Bhattacharya of Stanford, an antibody test was conducted on 5,603 major league baseball employees and 0.7% tested positive, showing they had been infected in the past. Only 4.7% of the participants were age 65 or older. 70% of those who tested positive had had no symptoms." I see your point that the age of the participants could be relevant to the results, but the other quantifiers in your Los Angeles Times article might also be relevant to the study's outcome: "The researchers in the Major League Baseball study noted their participants were not representative of the population as a whole: 95% under the age of 65, 80% white, 60% male and 100% employed." Should we include all quantifiers of the study's participants? LetterOpener (talk) 04:56, 21 May 2020 (UTC)
@LetterOpener: I included the 4.7% because age has been cited as the most relevant variable when considering the impact COVID-19 has on people. I acknowledge that citing that figure without explaining its relevance fell short of the optimal presentation of the material. Race, sex and employment do not have nearly the relevance and one has to cut it off somewhere. — Swood100 (talk) 15:50, 21 May 2020 (UTC)
@Swood100: I acknowledge that the mortality rate due to COVID-19 was highest among older age groups, however this study is about the number of infected employees. I found a CDC page talking about rate of hospitalization by age group, but it may not indicate how susceptible each age group to catching COVID-19, only that they experienced symptoms requiring hospitalization. In hopes of keeping the section readable, I would suggest adding in a paraphrased version of the sentence "The researchers in the Major League Baseball study noted their participants were not representative of the population as a whole", and in the |quote= tag for the reference, adding in the full sentence:
<ref>{{cite web |title=Fewer than 1% of MLB employees test positive for COVID-19 antibodies |url=https://www.latimes.com/sports/story/2020-05-10/mlb-employees-test-positive-for-coronavirus-antibodies-covid-19 |website=Los Angeles Times |accessdate=20 May 2020 |date=10 May 2020 |url-status=live |archive-url=https://web.archive.org/web/20200519051520/https://www.latimes.com/sports/story/2020-05-10/mlb-employees-test-positive-for-coronavirus-antibodies-covid-19 |archive-date=May 19, 2020 |quote=The researchers in the Major League Baseball study noted their participants were not representative of the population as a whole: 95% under the age of 65, 80% white, 60% male and 100% employed.}}</ref>
—  LetterOpener (talk) 22:40, 21 May 2020 (UTC)

Wikipedia is not a Promotional Site

Wikipedia is not a site to promote a specific company or company's product(s). See WP:PROMOTION. - LetterOpener (talk) 04:14, 20 May 2020 (UTC)

@LetterOpener: By removing the phrase “such as the tests from Abbott Labs” in the Antigen section you have turned the sentence into an assertion that all Isothermal nucleic acid amplification tests can process only one sample at a time per machine. Do you have a reference to support that? I understand your aversion to mentioning companies by name unnecessarily but this product has already received a great deal of notice in the press due to the fact that it (a) produces results so quickly, (b) has been mentioned in presidential press conferences, and (c) is used in the White house, so I believe that its name recognition warrants a reference to it by name. It is not an attempt to promote the product of a specific company.
@Swood100: Actually, the sentence "Isothermal nucleic acid amplification tests, such as the test from Abbot Labs, can process only one sample at a time per machine." already read that way, saying all isothermal nucleic acid amplification tests can process only one sample at a time per machine, and the test from Abbott Labs was an example of one such test. I should have removed the comma as well. Looking at the Abbott Labs website, they offer four testing products (two "molecular" tests and two antibody tests) rather than one. I do not see specific mention of their machines processing only one sample at a time per machine, though the toaster-sized box likely has less processing ability than the laboratory-sized machines. The spelling of Abbot Labs also has two t's in it. The burden of proof for keeping that sentence remains with whomever added it, and a [citation needed] tag should be added to that sentence until it can be proved that all such tests can only process one sample at a time per machine.
There are already two other mentions of specific test products on this page from Abbott Labs: "Abbott's m2000 system" and "ID NOW COVID-19", and a photograph of President Trump next to an Abbott Laboratories testing kit. The current page also has this blatant advertising section in it which I feel should be removed: "The test kit uses the company's "toaster-size" ID NOW device which costs $12,000-$15,000.[171] The device can be used in laboratories or in patient care settings, and provides results in 13 minutes or less.[170] There are currently about 18,000 ID NOW devices in the U.S. and Abbott expects to ramp up manufacturing to deliver 50,000 ID NOW COVID-19 test kits per day.[172]". — LetterOpener (talk) 06:13, 21 May 2020 (UTC)
@LetterOpener: This particular machine is one that has received much publicity and that people have heard about. To simply refer to Isothermal nucleic acid amplification tests would leave many readers in the dark as to what exactly we're talking about whereas referring specifically to a machine they've heard of would connect with them. I don't see it as advertising. These machines are so expensive that only a dedicated clinic would be in the market for one. Furthermore, negative information about this machine is also reported on this page. Would you remove that as well? Isn't that the sort of information that people who come to this page find useful? It seems to me that the information value greatly exceeds any promotional value. — Swood100 (talk) 16:46, 21 May 2020 (UTC)
@Swood100: I did not remove the Abbott Labs section further below on the page, simply the first mention of it as an example of an isothermal nucleic acid amplification test. I do not intend to remove the low 85.2% accuracy of the Abbott Labs ID NOW COVID-19 test, which I feel is an important metric for the test. I do want to put a [citation needed] tag for the Cleveland Clinic study, and I bet someone else would want to put the director of the study as well. —  LetterOpener (talk) 23:27, 21 May 2020 (UTC)
Are you in favor of removing all company and product names from this page in that they constitute Advertising, marketing or public relations? — Swood100 (talk) 20:42, 21 May 2020 (UTC)
@Swood100: Not at this time, since the specific products' attributes and testing results are relevant. However, there are currently 190 unauthorized products, 76 authorized Test Kit Manufacturers and Commercial Laboratories, and 29 High Complexity Molecular-Based Laboratory Developed Tests (same link). I believe including just authorized products would be prudent, but by doing so the page will eventually become a large list of hundreds of companies and products. — LetterOpener (talk) 14:58, 22 May 2020 (UTC)
Also, the quoted text by the main reference in the paragraph is to the effect that antigen tests are the only practical way to scale up testing to the levels necessary. Why did you remove that idea from the opening sentence? It said that the test is “seen by many” this way. Is that not true? Instead we now suggest that there are other candidates for such a test. Where is the source mentioning other candidates, and what are they?
@Swood100: The sentence in question "Antigen tests are seen by many as the only way it will be possible to scale up testing to the numbers that will really be needed to detect acute infection on the scale required.", has several weasel words in it. See Wikipedia:Manual_of_Style/Words_to_watch#Unsupported_attributions. The sentence I changed it to is "Antigen tests are seen as one way to scale up testing to levels necessary to detect acute infection on the scale required." The phrases "seen by many", "the only way it will be possible", and "really be needed" are the portions I removed unless additional citations can be added for each. I believe the burden of proof to justify keeping those phrases in the sentence falls on whomever added them. If we put the "seen by many" phrase back in, it will need to have multiple citations of high quality (e.g. medical journals rather than news articles) or it will get a [who?] tag. — LetterOpener (talk) 06:13, 21 May 2020 (UTC)
@LetterOpener: How about the following (with appropriate references):
According to Deborah Birx, head of the White House Coronavirus Task Force, antigen tests are the only way it will be possible to scale up testing to levels necessary to detect acute infection on the scale required. "There will never be the ability on a [PCR] test to do 300 million tests a day or to test everybody before they go to work or to school," she said on April 17. "But there might be with the antigen test." RT-PCR tests are accurate but it takes too much time, energy and trained personnel to run the tests, and the isothermal nucleic acid amplification test from Abbott Labs can process only one sample at a time per machine. — Swood100 (talk) 16:47, 21 May 2020 (UTC)
@Swood100: A reputable source for an applicable quote, that part sounds good to me. I believe the "too much" should be "significantly more", because that implies a limit that should not be exceeded. Otherwise, that sentence is fine up until "... to run the tests". The Abbott Labs test sentence should go further down on the page under their existing "Isothermal nucleic amplification" heading, which should really be ""Isothermal nucleic acid amplification". The CNN reference also says that PCR testing is suffering from supply chain shortages, which should be mentioned in the PCR testing section. —  LetterOpener (talk) 23:27, 21 May 2020 (UTC)
Furthermore you changed the sentence “The problem is that in the case of respiratory viruses often there is not enough of the antigen material present in the nasal swab to be detectable” to “In respiratory viruses often there is not enough of the antigen material present in the nasal swab to be detectable.” This is the principal drawback of the antigen test and this paragraph is intended to make that point clearly. If you don’t like “The problem is that” then let’s use a different phrase but one that makes it clear that this is not just a continuation of the preceding descriptive paragraphs but is announcing a major failing. How about “The principal weakness of the antigen test is that in the case…”? — Swood100 (talk) 20:17, 20 May 2020 (UTC)
@Swood100: The change of the first eight words in that sentence does not appear to undercut the fact that nasal swabs contain limited antigen material. The remainder of that paragraph and the reference to https://www.sciencemag.org/news/2020/04/nih-launches-competition-speed-covid-19-diagnostics# supports the initial sentence as well. I disagree with adding "the principal weakness" or "The problem" unless it can be cited that nasal swab collection is truly a larger problem than all other testing factors such as accuracy, availability, cost, and processing time. I am good with "A problem with antigen testing is that in the case of respiratory viruses..." — LetterOpener (talk) 06:13, 21 May 2020 (UTC)
@LetterOpener: The problem is not that nasal swab collection is a larger problem than all other testing factors. The problem is that the antigen material from the nasal swab is not amplified, as is the genetic material from the nasal swab in the PCR and the Isothermal nucleic acid amplification tests, and consequently there is too little of it to be detected by the test. That this is the principal drawback of the antigen test is well-documented by the existing references. Why you would resist this is mystifying. It is the major failing of the antigen test. — Swood100 (talk) 16:46, 21 May 2020 (UTC)
@Swood100: After reading the other references #36 and #39 which were in different areas of the article, I agree that the major drawback in antigen testing is its lower accuracy compared to PCR testing, which outweighs other drawbacks of the test. What about this possible rephrasing to emphasize antigen testing accuracy by explicitly placing it at the front of the paragraph? I also want to remove the "Many scientists" weasel word unless more reputable sources can be added.
"The principle drawback to antigen tests is the lower accuracy compared to RT-PCR tests. According to the World Health Organization (WHO) the sensitivity of similar antigen tests for respiratory diseases like the flu ranges between 34% and 80%.[39] "Based on this information, half or more of COVID-19 infected patients might be missed by such tests, depending on the group of patients tested," the WHO said. CNN Medical Analyst Dr. Kent Sepkowitz, an infectious disease specialist, expressed doubt whether an antigen test can be made reliable enough in time to be useful against COVID-19.[39] According to the FDA, positive results from antigen tests are highly accurate, but there is a higher chance of false negatives, so negative results do not rule out infection. Therefore, negative results from an antigen test may need to be confirmed with a PCR test.[40] In respiratory viruses often there is not enough of the antigen material present in the nasal swab to be detectable.[37] This would especially be true with people who are asymptomatic and who have very little if any nasal discharge.[citation needed] Unlike the RT-PCR test, which amplifies very small amounts of genetic material so there is enough to detect, there is no amplification of viral proteins in an antigen test.[36][39] "
Here is the reference for the WHO accuracy statement of 34-80%, which actually references this study: Bruning AHL, Leeflang MMG, Vos JMBW, Spijker R, de Jong MD, Wolthers KC, et al. Rapid Tests for Influenza, Respiratory Syncytial Virus, and Other Respiratory Viruses: A Systematic Review and Meta-analysis. Clin Infect Dis [Internet]. 2017 Sep 15 [cited 2020 Apr 1];65(6):1026–32. Available from: http://academic.oup.com/cid/article/65/6/1026/3829590/Rapid-Tests-for-Influenza-Respiratory-Syncytial —  LetterOpener (talk) 01:00, 22 May 2020 (UTC)

@LetterOpener: Why did you remove the section about NEOKIT-COVID-19 in your 22:40 21 May edit on this page? — Swood100 (talk) 13:33, 22 May 2020 (UTC)

@Swood100: It was an accidental removal, and I've restored it below. I believe the time it took to type out a lengthy reply coincided with the time someone else was saving this page. I would prefer to avoid editing this talk page when the main article requires a lot more work. — LetterOpener (talk) 14:58, 22 May 2020 (UTC)

Antibody tests

I fixed the wording a little. The sources tell "a half", so let it be, but this is just uncertain. Here is the idea. For example, the test produces 15% positive results for the population of NY [1]. However, what is the rate of false-positive results by these tests (it is the false-positives rather than false-negatives are significant for such tests due to the Cross-reactivity#In_immunology)? If it is 15%, then it well can be that all positive results determined by this test for NY can be false (some of these people will of course be truly positive, merely by chance). My very best wishes (talk) 17:31, 29 May 2020 (UTC)

But surprisingly, they claim less than 12% false-negatives and 1% false positives [2], contrary to claims by other sources currently on the page. There is definitely an inconsistency here. My very best wishes (talk) 02:49, 30 May 2020 (UTC)

My test has been diverted by chugtai lab,

My test has been said positive from chugtai lab and from shukat khannum lebortry lahore it came negative. Waleesilyas114 (talk) 01:52, 2 June 2020 (UTC)

@Waleesilyas114: You should ask a doctor about that, not Wikipedia. --Mdaniels5757 (talk) 01:53, 2 June 2020 (UTC)

No mention of lab professionals performing the tests

It's odd the article doesn't make any mention of lab professionals performing the tests (medical technologist/medical laboratory scientist/etc).GobsPint (talk) 17:09, 2 June 2020 (UTC)

Semi-protected edit request on 3 June 2020

Dear sir or madam I am a volunteer working for a scientific web site. We have created a database presenting different risks and outcomes of COVID-19. Our team works hard and updates the database with new data every day. I would like to add the link to the database in the "External links" section of this article(http://corona.epidy.com/). We work diligently to provide up to date and useful results. As I could not make the edit to this article, I would like to request you to do this, adding the link of the site "http://corona.epidy.com/" in the external resources section. Yours faithfully Zori Mark Zoryan Zorimark (talk) 12:15, 3 June 2020 (UTC)

 Not done: Wikipedia is not for promotion. I am not competent in the matter to judge whether this information is reliable or not, but I could not find independent assessment of the publisher through a quick glance at google. In any case, this needs ideally to be reported in reliable sources before being included. RandomCanadian (talk / contribs) 21:54, 3 June 2020 (UTC)

Semi-protected edit request on 8 June 2020

In the "Polymerase chain reaction" section, the following sentence can be found:

Polymerase chain reaction (PCR) is a process that amplifies (replicates) a small, well-defined segment of DNA (or RNA many hundreds of thousands of times, creating enough of it for analysis.

Please close the parentheses - I suspect the place to do it is after the word RNA. 147.161.12.161 (talk) 11:57, 8 June 2020 (UTC)

 Done Pupsterlove02 talk • contribs 12:38, 8 June 2020 (UTC)

Detection dogs?

I've seen a couple of articles (in RS media) recently about detection dogs being trained to test for COVID (at least in one project, from urine samples), which is apparently giving very promising results, being both quick and accurate. Should this be mentioned here? -- DoubleGrazing (talk) 07:39, 2 June 2020 (UTC)

Are there any articles with actual results? — Swood100 (talk) 17:55, 8 June 2020 (UTC)

Covid-19 Testing in Brazil

The Covid-19 Testing page mentions Brazil has tested 10,697,205 samples, while worldmeters mentions 999,836. Can anyone confirm these numbers? I could not confirm from the source mention on Wikipedia as I don't know the language. me_arunkt (talk) 12:33, 9 June 2020 (UTC)

NUmbers change every day. Now 1.5m. https://www.worldometers.info/coronavirus/ Lfstevens (talk) 00:40, 14 June 2020 (UTC)

So, no false positives ?

Anyone ? Searching for "false" seems to indicate that there are no such occurrences (but searching for "positive" makes for an interesting read). The president of Tanzania claims he got a bunch of false positives (see COVID-19 pandemic in Tanzania) —Jerome Potts (talk) 12:49, 14 June 2020 (UTC)

We talk about the problem of false positives when discussing the low positive predictive value of antibody tests. As for the PCR-based and isothermal nucleic amplification tests there is a great variety of such tests and it seems that they each have their unique shortcomings. For example, the problem with the ID Now is false negatives. Maybe the test in use in Tanzania has a false positive problem. Are you aware of any source talking about a general false positive problem among tests? — Swood100 (talk) 14:35, 15 June 2020 (UTC)

Recent changes made by Lfstevens

@Lfstevens:

  • You added the following sentence: "Polymerase chain reaction (PCR) is a process that amplifies (replicates) a small, well-defined segment of DNA (or RNA many hundreds of thousands of times, creating enough of it for analysis." You added "or RNA." What is the authority for the proposition that PCR can amplify RNA? And if this is true, then what is the reason for using reverse transcription to convert the RNA into DNA for amplification, and why should it be pointed out that this kind of virus only contains RNA? The original stated a fact, that PCR amplifies DNA. Then it disclosed a problem, that this virus has no DNA, thereby setting up the two-part solution: first RT, then PCR.
  • You also added: "Reverse transcription polymerase chain reaction (RT-PCR) is a technique that first uses reverse transcription to convert the extracted RNA into DNA for amplification." But RT-PCR doesn’t just convert RNA into DNA for amplification. It is a two-step process. First, the RT part of the process converts RNA into DNA for amplification. Then, the PCR part amplifies the DNA. You cut out the second step. The original that you replaced made a point of explaining this to the reader as a two-step process. The original said “and then uses PCR to amplify a piece of the resulting DNA, creating enough to be examined in order to determine if it matches the genetic code of SARS-CoV-2” and you replaced this quoted text with “for amplification.” How does this help the user understand what is going on? And why is it necessary to convert the RNA into DNA anyway, given the opening statement?
  • What is the problem with emphasizing the two-step process? Real-time PCR was explained as providing advantages “during the PCR portion of this process.” You replaced this with advantages “for PCR.”
  • After disclosing the (MIQE) proposed terminology (RT-qPCR) the original said “but not all authors adhere to this.” You removed that part, apparently wishing the reader to assume that the hodgepodge of different terminology for the same thing all preceded the MIQE proposal, and that since then everybody has been using the same terminology, but this is not the case at all. Those guidelines were issued in 2009 and were ignored. In fact, the cited references for both qRT-PCR and rRT-PCR both were published after that. So what’s the point of removing the “but not all authors adhere to this”?
  • In the phrase “and will enable quarantined people to collect their own samples more efficiently” you removed “more efficiently,” implying that unless saliva is being tested people can’t collect their own samples. But people can collect their own samples using nasopharyngeal swabs. The problem is that they tend not to insert the swab deeply enough (since it is uncomfortable) and so do not collect samples from locations that are most likely to contain evidence of viral presence.
  • In the text “saliva yielded greater detection sensitivity and consistency throughout the course of infection when compared with samples taken with nasopharyngeal swabs” you replaced "nasopharyngeal swabs" with “swab samples.” But the source was not comparing to just any “swab” sample. Besides nasopharyngeal swabs there are oropharyngeal swabs, mid-turbinate swabs, anterior nares swabs. Why not just report what the source said?
  • Why did you remove the text explaining to the user that antibody tests enable the determination of an accurate mortality rate of the disease, as well as how close a population is to herd immunity?

--- @Swood100:

  • RNA/DNA - fixed.
  • PCR portion - the extra context is not necessary
  • not all authors - ok
  • efficiency - where does it say that auto-collection with nasopharyngeal swabs is effective or practiced?
  • swab types - ok the section did not talk about other swab types so no risk of confusion.
  • antibody tests - wrong section
  • EUA - belongs in the yet-to-be-written history section.

Lfstevens (talk) 19:49, 12 June 2020 (UTC)

@Lfstevens:
  • efficiency - where does it say that auto-collection with nasopharyngeal swabs is effective or practiced?
What would make you think that auto-collection has not been practiced using nasal swabs? It’s the standard way of doing it. See this, this and this.
  • *swab types - ok the section did not talk about other swab types so no risk of confusion.
But why introduce even the possibility of confusion simply to remove a word?
  • *PCR portion - the extra context is not necessary
But was the extra context detrimental? Does the removal of that phrase make the explanation clearer? Why do you feel the need to substitute your judgment for somebody else’s in cases where there is no error and where reasonable people can differ about the usefulness of additional explanation?
  • Test samples are treated with certain chemicals that allow RNA to be extracted.
Again your insistence that your wording must be used, even though the wording you replaced was eminently reasonable. The original, prior to talking about the extraction of RNA, explained why we were mentioning RNA at all when it’s the DNA that we need. Is it a clear benefit to understanding to move that to the end of the following paragraph?
  • *EUA - belongs in the yet-to-be-written history section.
So in the interim why is it better for this EUA not to be mentioned at all? What harm would come from leaving it where it was? If it would go anywhere else it would be in current section 6.1. What exactly do you intend to put into the yet-to-be-written history section? If this is to be a major structural change to this article I strongly urge you to propose it first on the talk page.
  • *antibody tests - wrong section
What does this even mean? Why did you remove the information that antibody tests enable the determination of an accurate mortality rate of the disease, as well as how close a population is to herd immunity? You did not move them to a different section. I replaced them after waiting for you for four days. And why don’t they belong in the opening section?
Also, you added “Antibody tests instead support attempts to estimate the prevalence of disease within a population.” This is another example of fixing something that wasn’t broken, and breaking it in the process. Look up “prevalence” in the dictionary. It is “the percentage of a population that is affected with a particular disease at a given time.” Your addition was stark misinformation. Antibody tests can’t tell the percentage of people who are infected at any given time, for the simple reason that antibodies don’t appear until some period of time after the infection sets in. The text you replace has received a great deal of review and useful modification before you arrived here. Most of your modifications are not clear improvements, though you may prefer your own wording. It seems to be just a little on the egocentric side for you to be so quick to conclude, without compelling reason, that your formulation must be superior, and to apparently give little heed to the very real possibility of introducing errors such as this one, as well as the error state in which you left footnote 22 (fortunately, fixed by AnomieBOT), and the error state in which you left “or RNA” (the subject of the section above this one).
  • *RNA/DNA - fixed.
But how could you introduce an error as egregious as asserting that PCR can amplify RNA?
  • You added: “Isothermal nucleic acid amplification tests also amplify a the virus's genome,” in which you changed the original “methods” to “tests,” but in Wikipedia and elsewhere these are described as methods, not tests. A method is a technique used to obtain data. A test measures that data. Referring to Isothermal amplification methods as tests is colloquial at best. Why did you make that change? Also, “amplify a the virus’s genome” is not grammatically correct.
  • Why did you remove the CT images from the “Imaging” section? Not useful in your opinion? To hell with the guy who thought they were? Do they detract from the article?
  • You changed "Since antibodies are slow to present they are not the best markers of acute infection" to "Antibodies are too slow to present serve as acute infection markers.” What is the meaning of "Antibodies are too slow to present serve as acute infection markers”? A certain number of subclauses is really required for coherence.
  • You changed “In respiratory viruses often there is not enough of the antigen material present in the nasal swab to be detectable” to “Respiratory viruses often lack enough antigen material to be detectable.” But the problem is not that the viruses lack enough antigen material. The problem is that the nasal swabs lack enough antigen material.
  • You followed the above text with “This would especially be true with people who are asymptomatic and who have very little if any nasal discharge” but are you saying that it is especially true in asymptomatic people that respiratory viruses lack enough antigen material? Do you have a source for that?
  • You changed “Unlike the RT-PCR test, which amplifies very small amounts of genetic material so there is enough to detect, there is no amplification of viral proteins in an antigen test” to “Unlike the RT-PCR test, viral proteins in an antigen test.” What??? Beside the absence of a complete sentence, what harm is there in reminding the reader that there is no amplification of proteins?
  • You changed: “IgG antibodies to SARS-CoV-2 generally become detectable 10-14 days after infection” to “IgG antibodies generally become detectable 10–14 days after infection,” asserting that this applies to all IgG antibodies, not just those to SARS-CoV-2. The source says “IgG antibodies to SARS-CoV-2 generally become detectable 10 – 14 days after infection although may be detected earlier.” You changed the text so it is no longer supported by the source. Do you have a new source?
  • You changed “most, if not all, of the current COVID-19 antibody testing done at large scale is for detection of binding antibodies only and does not measure neutralizing antibodies” to “Most if not all scaled COVID-19 antibody testing is for detection of binding antibodies only and does not measure neutralizing antibodies (NAb).” But “scaled” does not mean “done at large scale.” According to the dictionary it means “to pattern, make, regulate, set, or estimate according to some rate or standard : ADJUST” //a production schedule scaled to actual need. So what is “scaled COVID-19 antibody testing”? Also, you introduced an error in the link, turning the word red. Why did you leave it that way? The original had a working link in the next sentence. There was no problem with that.
  • You moved the discussion of neutralizing antibodies to the “accuracy” section, as if a test designed to find binding antibodies is inaccurate if it doesn’t find neutralizing antibodies. There are two types of antibody tests: for binding antibodies and for neutralizing antibodies. A test for binding antibodies is not an inaccurate version of the test for neutralizing antibodies. See this CDC explanation.
  • You changed “It is presumed that once a person has been infected his or her chance of getting a second infection two to three months later is low” to “It is presumed that a post-infection patient has a low chance of a second infection” but the source did not talk about a “post-infection patient” but rather about "a second infection two to three months later." This source doesn’t say that a person’s antibodies 14 days after infection are at the same level as they are 56 days after infection. Again, your addition is not supported by the source.
  • You removed “One study determined that reinfection at 29 days post-infection could not occur in SARS-CoV-2 infected rhesus macaques.” Why isn’t that relevant?
  • You took the original: “can last much longer and may have the ability to greatly lessen the severity of a reinfection,” and changed “greatly lessen” to “reduce.” The wording of the source was “which can either completely prevent disease or greatly alleviate the severity of clinical manifestation.” “Reduce the severity of” does not capture the magnitude expressed here. What was the point of changing it?
  • You added that ELISAs can be qualitative or quantitative. How many people do you think know what qualitative and quantitative mean in the context of ELISA? Is this important enough for the user to know? If it is, then why not explain it, or at least supply a link to an explanation, such as this or this.
  • You made a reference to Neutralization assays which turned red because this does not link to an actual article in Wikipedia. Are you going so fast that you didn’t even see this, or is the problem something else?
  • You added: “This test can multiple types of antibodies, including IgG, IgM, and IgA.” What does it mean that a test “can multiple types of antibodies”?
  • You changed: “reported that 10 individuals had produced no detectable NAbs at the time of discharge, nor did they develop NAbs thereafter” to “reported that 10 individuals had produced no detectable NAbs at the time of discharge, or thereafter.” Perhaps you are not aware of this, but “had produced” is past perfect, which expresses the idea that something occurred before another action in the past. In this case the lack of production occurred before the discharge. "Had produced" can’t be the verb for “thereafter.” “10 individuals had produced no NAbs thereafter” is incorrect. It should be “10 individuals produced no NAbs thereafter.” So you have to change the tense in the clause containing "thereafter," as in the text you replaced.
  • You changed “How these patients recovered without the help of NAbs and whether they were at risk of re-infection of SARS-CoV-2 was left for further exploration” to “How these patients recovered without the help of NAbs and whether they were at risk of re-infection not established.” In the first place, “not established” is not the same as “not addressed.” “Not established” implies that they tried and failed to establish something, whereas the sense of this study was that this question was not a focus of the study. Also, “whether they were at risk of re-infection not established” is missing a verb.
  • You changed: “An additional source of uncertainty is that even if NAbs are present, several viruses, such as HIV, have evolved mechanisms to evade NAb responses” to “An additional source of uncertainty is that even if NAbs are present, viruses such as HIV can evade NAb responses.” You changed the focus from saying that “several viruses” (of which HIV is just one example) can evade Nab responses to saying that “viruses such as HIV” can evade Nab responses. Has it been established that SARS-CoV-2 is a virus such as HIV? Isn’t it somewhat confusing to be referring to “viruses such as HIV” with no prior explanation as to why such viruses are relevant here? Perhaps you don’t see the problem here.
  • You removed: “While this needs to be examined in the context of COVID-19 infection, past experiences with viral infection, in general, argue that in most recovered patients NAb level is a good indicator of protective immunity,” the purpose of which was to say that the ability of some viruses to evade Nab responses is not considered to be much of a concern, but you changed it so that the reader could be left thinking that it could be a significant concern. Why?
  • You added: “After infection, patients remain infectious for an uncertain interval,” but the source says: “At this time, replication-competent virus has not been successfully cultured more than 9 days after onset of illness. The statistically estimated likelihood of recovering replication-competent virus approaches zero by 10 days.” Your statement is misleading, right?
This is beyond a puzzlement. — Swood100 (talk) 01:19, 15 June 2020 (UTC)

---

  • How could you: seriously?
  • Test vs method: Take your point.
  • CT images: unintentional. In fact I can't even find the deletion. And please don't attribute bad motives to me. I am sincerely doing my best to improve this piece.
  • Present serve: typo. Good catch.
  • Viruses lack: fixed.
  • “This would especially be true with people who are asymptomatic and who have very little if any nasal discharge” I didn't add that.
  • “Unlike the RT-PCR test": fixed.
  • IgG antibodies : fixed
  • immunity passports? Didn't seem appropriate there. Perhaps in another section.
  • scaled : fixed.
  • link: I always move links earlier. Sorry for the error.
  • neutralizing antibodies: fixed
  • Second infection: distinction without a difference? 2-3 months seemed over-specific. (why not 4 months?)
  • 14 v 56 : couldn't find that in the text.
  • "reinfection at 29 days": it was an animal study.
  • Greatly: that word is vague. If included, it should be in a quote.
  • ELISAs: took all that material from the source. I removed considerable detail from that. Don't object to further reductions or additional explanations.
  • Neutralization assays: fixed.
  • This test can multiple types of antibodies: fixed.
  • past perfect: fixed.
  • “Not established”: fixed.
  • several viruses: "such as" implies more than one.
  • Has it been established that SARS-CoV-2 is a virus such as HIV? They're both viruses.
  • NAb immunity: we shouldn't be leading them on.
  • 10 days: added detail.

Appreciate the close reading, if not the gotcha attitude. Cheers. Lfstevens (talk) 03:42, 17 June 2020 (UTC)

Semi-protected edit request on 18 June 2020

The word "conducing" should be "conducting" Tombammann (talk) 22:05, 18 June 2020 (UTC)

Where? Graham Beards (talk) 22:20, 18 June 2020 (UTC)

No mention of how shortages impacted testing?

There's no mention of how lack of qualified personnel, equipment, and reagent shortages delayed or impacted testing. The shortages mean that assays with worse limits of detection and higher false negative rates continue to be used. GobsPint (talk) 01:28, 25 June 2020 (UTC)

Thanks for noticing. Feel free to add material on that subject. Lfstevens (talk) 03:16, 25 June 2020 (UTC)
Would be good to say something like ..."an increase in demand quickly depleted supplies on an international level leading to a world shortage despite increased production." Best not make it seem production stop because of the pandemic when in fact it increased by 10 fold bUT still couldn't keep up with demand.--Moxy 🍁 03:43, 25 June 2020 (UTC)
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