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Requests for a Reset Section

Hello all, I recently moved "requests for a reset" to the "Responses" section. My edit was reverted by another user so I would like to discuss here. I believe that the "requests for a reset" section fits better thematically with the "responses" section. While it is true that it is a real-time reaction to the rise in infections, I think the timeline section should be reserved for more significant milestones. Including every response by every group of public health experts would make the timeline section too unwieldy. However, if there are other reasons to include it in the timeline section, that would be good to discuss. Michelangelo1992 (talk) 17:45, 11 August 2020 (UTC)

@Michelangelo1992:
  • 1) Moving the paragraph to Responses seems better than keeping it in Timeline section, as per above.
  • 2) Dropping the paragraph altogether and keeping only the sentence about "[...] U.S. PIRG and 150 health professionals sent a letter asking [...]" would do Wikipedia a service. As it stands, the paragraph gives WP a very partisan and biased look, by overemphasis of pro-lockdown experts who propose an action on federal level and conspicuous silence about e.g. nobel laureate Michael Levitt, a biophysicist, and Stanford's Dr John Ioannidis, Professor of Medicine, of Health Research and Policy (at least he is mentioned in references for IFR), etc. One should also realize that state governors have their own public health experts and advice from them; I do not see what makes Peter Hotez and Michael Osterholm more competent than those experts. In fact, Michael Osterholm's predicted 800,000 total deaths in the U.S. from the covid seem very unlikely to me, but we will see.
  • 3) At least removing the images of the experts would be an improvement: we do not learn much from these images.
--Dan Polansky (talk) 13:58, 14 August 2020 (UTC)
Since "reset" is a coined word and a metaphor for another lockdown, I'd suggest using another word. In any case, the section should treat the topic as an issue, including opposing opinions, ie. "COST-BENEFIT" citations.--Light show (talk) 17:38, 14 August 2020 (UTC)
@Dan Polansky: Why don't you add what you find to be conspicuously missing? Michael Levitt (who thinks someday we'll all say COVID was no big deal) never rose very far in visibility on this topic. Why do we cite John Ioannidis in a preprint? Have you asked for help at WP:MED? I cited Ioannidis elsewhere when his STAT piece came out in March. It's published so maybe that would better represent his views? -SusanLesch (talk) 17:58, 15 August 2020 (UTC)
I am a seasoned Wiktionary editor and I am very inexperienced with Wikipedia. I am doing above all charts since they appear to be rather objectively given, not perfectly objectively, but still. I am not certain that statements of which expert says what belong to an encyclopedia; experts are notoriously unrealiable in general. Therefore, I am not comfortable adding material of what experts say; I might be comfortable adding peer-review science, which finds that lockdowns do not reduce death[1]. My point about bias stays, and I have no idea why you added the images of the two obviously misguided experts.
From what I understand, nobel laureate Michael Levitt, biophysicist, does not say the covid is no big deal; he says that multiple epidemiological estimates and projections are hugely overblown and the responses are disproportionate; if you have a direct quote from him pointing otherwise, I'll stand corrected. I have a direct quote from a YouTube video[2]: "The World Health Organization and I think the epidemiologists in general [...] they overestimated bird flu by a factor of a 100 or 10 000 [...] Ebola was overestimated by a factor of 100 [...]" --Dan Polansky (talk) 07:22, 16 August 2020 (UTC)
Chaudhry et al. (2020) looks promising so pardon me while I take time out to read the whole thing. Thank you for the link! I like your idea of not adding material of what experts might say. I have no problem if the entire section is removed or maybe better reworded into a sentence. I'll try adding such a sentence to the timeline in July. Just to back up my very out of context paraphrase, Dr. Levitt said a couple of weeks ago in an interview with the Stanford Daily that, "I think that when we come to look back, we’re going to say that wasn’t such a terrible disease." Regarding Ioannidis, I don't think a preprint is a great source, and the paragraph where we use it probably is overcited. -SusanLesch (talk) 15:47, 16 August 2020 (UTC)
As for "wasn’t such a terrible disease", we already know it wasn't for some value of "such a terrible disease"; for many even relatively badly hit countries, it seems no more than twice as bad as a bad flu of recent years in terms of excess death, but I would have to double check to have the "twice" right. And if "such a terrible disease" means "as terrible as indicated by Neil Ferguson" or "as terrible as a disease with lethality (IFR) of 2%", it really wasn't by any stretch. That said, it is bad enough to be taken seriously, and there are spread mitigation measures that are proportional to the threat.
A preprint surely is not of the peer-review grade, and I do not know how Wikipedia handles preprints. Still, a preprint is better than "expert said". I mentioned John Ioannidis as an example of an expert that does not support a lockdown, and I have currently no stance of whether preprints are appropriate as sources.
(Thank you for the link to the Stanford Daily interview.) --Dan Polansky (talk) 18:15, 16 August 2020 (UTC)
We got four answers already to the question of preprints. -SusanLesch (talk) 20:56, 16 August 2020 (UTC)
Regarding "peer-review science, which finds that lockdowns do not reduce death". Careful. True, they did find that government actions such as lockdowns were not associated with a statistically significant reduction in mortality. But the authors say their work found "more restrictive public health practices may...be associated with less transmission and better outcomes."
Also Chaudhry et al. acknowledge limitations including that lockdowns may only be effective in countries where they can be implemented--and they cite the United States as an example of another sort of country. And because their data only runs through May 1, 2020, I would hesitate to draw a hard line like your conclusion. So this leaves me in agreement with your idea to omit expert opinion and that includes no peer-reviewed works, unless somebody at WP:MED like Michelangelo1992 is willing to check it all over? -SusanLesch (talk) 03:19, 17 August 2020 (UTC)
Thank you. Let me note that I am making no firm conclusion about whether lockdowns work. My intuition was that early lockdowns would be able to shift the infection to the future; that would be hinted at by California (early lockdown) and New York City (late lockdown). And shifting the infection from dry months to humid months (winter and spring to summer) at least makes sense in principle, but not the other way around. But my intuition does not matter, there can be all sorts of confounding factors, and Chaudhry et al. is the best peer-reviewed science that I know of now. (Peer-reviewed does not mean infallible.) The pro-lockdown experts should produce peer-reviewed science or at least a preprint. Experts waving their credentials is no science. --Dan Polansky (talk) 06:54, 17 August 2020 (UTC)
The reason originally given for lockdowns was to "flatten the curve", that is, to slow the transmission of the infection. Such measures were intended to ensure that health services were not overwhelmed, which would have resulted in deaths that would have been avoidable. That tends to spread fatalities over a longer time without necessarily reducing their number. Because deaths are a lagging indicator, by May 1, outbreaks were still claiming lives despite measures taken, and it is not surprising that a survey didn't find a statistically significant correlation between total fatalities and measures taken. In any case, Chaudhry et al is a single study and needs to be put into context by a reliable review before its results are usable here. Although peer-review is a necessary condition for an article to meet WP:MEDRS, it is not a sufficient condition, and does not make a primary source into a secondary one. --RexxS (talk) 12:36, 17 August 2020 (UTC)
That's looks like a plausibly reasonable rigor for Chaudhry et al, even if very stringent. Should similar rigor apply to "Expert X says Y" or are such statements allowed to stay since they are true? --Dan Polansky (talk) 13:01, 17 August 2020 (UTC)
As for effect by May 1, many lockdowns were imposed in mid March, so they had 5-6 weeks to take effect, until May 1st.
And now is Aug 17; what are the peer-reviewed solid studies produced by pro-lockdown experts, now that the effect would need to be already noticeable? --Dan Polansky (talk) 13:05, 17 August 2020 (UTC)
We need rigour for biomedical claims, and even more so for any non-obvious or surprising claim. The rigour required for "Expert X says Y" depends on what "Y" is (depends on MEDRS and REDFLAG) and on how we know that "X" is an expert on that topic (depends on WP:SPS, which says "Exercise caution when using such sources").
Our article on COVID-19 pandemic lockdowns uses reliable sources and shows when lockdowns started by country. You'll see that the bulk of the lockdowns began in late March. Given that it takes quite a few days for such measures to affect transmission rates, that confirmed cases lag several days behind infections, that fatalities can lag confirmed infection by a few weeks, and that reporting of deaths often lag the event by a few days, you might presume that a May 1 cutoff date doesn't give most countries a lot of leeway to show the effect of lockdowns on mortality. However, like any other Wikipedia editor, I'm not qualified to analyse primary studies, so you'll have to take the preceding with a pinch of salt.
It is indeed 17 August. I don't see any later studies produced by anti-lockdown, pro-lockdown, or neutral experts, which would be needed to inform a review. Perhaps the challenges of producing a robust study are too great at present? Who knows? --RexxS (talk) 17:58, 17 August 2020 (UTC)
As for "fatalities can lag confirmed infection by a few weeks", charts in sources such as Worldometers or covidtracking.com do not suggest that the mean lag is a few weeks; it looks more like a week. So I still do not see May 1st as unusably early, and the peer-reviewed Chaudhry et al does not either, it seems. On a marginal note, it seems that while for Wikipedia, peer-reviewed primary sources are frowned upon for pharmaceutical interventions, for some people, non-peer-reviewed verbal "expert" opinion on efficacy and safety of non-pharmaceutical interventions such as hard lockdowns is somehow good enough to justify their use. And I do not see what makes non-pharmaceutical interventions, especially hard lockdown, so much less dangerous than pharmaceutical interventions. --Dan Polansky (talk) 06:37, 18 August 2020 (UTC)
Careful. Chaudhry et al. says, "In the context of COVID-19, it is thought that public health interventions typically require from 2 to 3 weeks to affect outcomes, hence the impact of widespread border restrictions may not have yet been detected in our dataset." That sentence cites two sources which you are free to track down. -SusanLesch (talk) 15:59, 18 August 2020 (UTC)
Fair enough as per the quotation. In any case, the pro-lockdown experts have not produced any peer-reviewed science, as far as I know, not even a preprint; I'll stand corrected since I cannot know this positively. Anecdotally, Peru had a hard lockdown since March 16 but the resulting Peru death rate per million is bad; maybe they had a poor implementation. The number of poor-outcome hard-lockdowners is suspiciously high. Solid analysis is required and the pro-lockdown experts should produce solid analysis; signing letters, waving credentials and saying "trust the experts", meaning "trust us but not the other experts", is no replacement for solid analysis. --Dan Polansky (talk) 06:49, 19 August 2020 (UTC)
I don't know what you're talking about. Regarding, "the pro-lockdown experts have not produced any peer-reviewed science...". Try PubMed. A search for "(covid-19) AND (lockdown) AND (mortality)" will yield 100 hits.
Wong et al. finds countries that implemented stay-at-home orders, curfews, and lockdowns curbed the percent increase in daily new cases to <5 within a month. In Spain, mortality declined 18.33 days after lockdown, but in some areas increased, the authors think due to population density and mobility before the lockdown. And Colombia, India, China, and Italy. -SusanLesch (talk) 20:55, 19 August 2020 (UTC)
Okay, that is "Impact of National Containment Measures on Decelerating the Increase in Daily New Cases of COVID-19 in 54 Countries and 4 Epicenters of the Pandemic: Comparative Observational Study" and it does not measure impact on death rate. Do we have a statistical study that measures impact on death rate, one that finds a correlation on a non-trivially large country set? No models, mathematical speculation, just properly controlled empirical correlation? E.g. "Only strict quarantine measures can curb the coronavirus disease (COVID-19) outbreak in Italy, 2020"[3] does not meet that criteria since it says "Our model shows how the number [...]"; no models please and no single-country studies. As for "In Spain, mortality declined 18.33 days after lockdown": they have to show that it would not have declined without a lockdown, and that is much harder to do if you have no control group of countries; the Spanish study is "An ecological study" and yet "The findings presented herein emphasize the importance of early and assertive decision-making to contain the pandemic"; a red flag. And even if we assume effect of the measures, by not comparing to other countries, we fail to determine what parts of the measure package brought about the efffect; for instance, it could be that prohibition of mass gatherings would alone achieve very significant effect.
I do stand corrected at least to some extent: there is peer-reviewed material on PubMed. That said, I don't see that it is science proper, as per my notes above. --Dan Polansky (talk) 09:36, 20 August 2020 (UTC)
Regarding, "I don't see that it is science proper, as per my notes above." I don't know who you think you are. I will leave you with Lockdowns and COVID-19 Deaths in Scandinavia from Google Scholar. Goodbye. -SusanLesch (talk) 22:03, 20 August 2020 (UTC)
Critical work with sources requires critical reasoning and critical assessment of sources, searching for deficiencies. There is a lot of bad science out there; that would explain why Wikipedia seems to require or prefer meta-analyses for medical claims; a meta-analysis would go through published peer-reviewed medical reports and include or exclude studies based on assessment of quality. As for "Lockdowns and COVID-19 Deaths in Scandinavia"[4], I have argued elsewhere that Scandinavia does not present a reasonably large set of countries, and that one would have to show that the Nordic countries really are comparable as for similar demographics, similar nursing home size, similar traffic density in urban centers, similar Spring holiday week, etc. When one assumes that the countries are comparable in all these regards, it is really easy to notice the lower death rates in lockdown countries, but the catch is whether they really are comparable. I cannot access the article without registering in SSRN so I cannot check their methodology (I have no intent to register); their abstract states no confounding factors they controlled for and no limitations. --Dan Polansky (talk) 09:25, 21 August 2020 (UTC)

For anyone else, the button "Download This Paper" is at upper left. -SusanLesch (talk) 16:15, 21 August 2020 (UTC)

I don't know what happened but I was now able to download the pdf using the above link, without registering anywhere. Reading the pdf confirms that the paper does not control for the above factors I said it needs to control for. Instead, it says "We exploit the fact that ex ante Denmark, Norway and Sweden are very similar societies (i.e. a deep enduring Scandinavian tradition and culture) but [...]"; they do not mention a single observational measurable characteristic by which they are "similar". The paper does not control for 1) nursing home size, 2) traffic density in urban centers, 3) week of Spring holiday, 4) demographic differences, e.g. age distribution. One can only conclude that the paper is no solid science. On a perhaps less important note, the pdf I downloaded says "This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3616969". --Dan Polansky (talk) 12:35, 23 August 2020 (UTC)

Not what the 2 sources actually say

"Some states had immediate needs for ventilators; hospitals in New York City, for example, ran out.[275][276]".

The sources don't verify that and no wonder since NY didn't run out of ventilators. They were only short of what they wrongly predicted to be in need of at the time. Maybe an update would be appropriate here?--TMCk (talk) 20:16, 22 August 2020 (UTC)

Thank you; statements dropped in diff. --Dan Polansky (talk) 12:49, 23 August 2020 (UTC)

The article is plotting hospitalizations, which is good, but from a source that has very outdated hospitalization data, which is bad.

https://covidtracking.com/data shows up-to-date daily current hospitalizations, which is good; there is https://covidtracking.com/data/download. We could plot hospitalizations from there, but they have some curious data license here: https://covidtracking.com/about-data/license.

Does anyone know what the legal force of a "data license" is given that data and information (unlike expression of information) is not subject of copyright in the U.S.? Can we use data from covidtracking.com to create a plot in Wikipedia? --Dan Polansky (talk) 17:22, 3 August 2020 (UTC)

The license that I see, on the associated github repo, is the Apache 2.0 license--a common Libre/Free license for software. It permits use for just about anything, but says you can't hold them liable or take their data and wrap it in your own trademark (I think a totally academic proposal). Scotty.tiberius (talk) 11:26, 13 August 2020 (UTC)

@Scotty.tiberius: Thank you; which repo is it (which URL)? --Dan Polansky (talk) 17:46, 15 August 2020 (UTC)
github.com/COVID19Tracking , and the API/Covidtracking.com website all cite that license. — Preceding unsigned comment added by Scotty.tiberius (talk • contribs) 14:47, 21 August 2020 (UTC)
Thank you; I can see .csv data in https://github.com/COVID19Tracking/covid-tracking-data/tree/master/data and the Apache License 2.0 in https://github.com/COVID19Tracking/covid-tracking-data, in LICENSE. --Dan Polansky (talk) 12:59, 23 August 2020 (UTC)

South Dakota Cases typo

The number of cases for South Dakota is listed as 11,1135. On the South Dakota page it says 11,135. I was not allowed to edit the template to correct this typo. Holland jon (talk) 15:49, 23 August 2020 (UTC) 2nd attempt it let me correct this. Not sure what I was doing wrong first time, now fixed. Holland jon (talk) 16:20, 23 August 2020 (UTC)

Some good news on covid in the U.S.

Some good news concerning the development in the U.S. (there are also bad news, but they are out of scope of the following):

  • On U.S. level, new daily cases seem to be plateauing, starting to decline; current hospitalization seem to approach a plateau or a peak[5].
  • In Arizona and Florida, both new daily cases and current hospitalizations are behind a peak and starting to decline[6][7].
  • In Texas, new daily cases are behind a peak and in decline; current hospitalizations slowed down and seem to be approaching a plateau[8].

--Dan Polansky (talk) 16:42, 28 July 2020 (UTC)

More good news on current hospitalizations ("avoid healthcare overload"):
  • Texas current hospitalizations are in decline[9].
  • Alabama, Mississippi and Nevada current hospitalizations seem to approach a peak[10][11][12].
  • Louisiana current hospitalizations reached a peak and start to decline[13].
  • Missiouri current hospitalizations seem to have reached a peak[14].
Covidtracking.com has Regional Current Hospitalizations showing charts per one of four big U.S. regions.
Covidtracking.com has Currently Hospitalized by State, a map in which progression charts per state are available on a mouseover; unfortunately, the map does not relate the hospitalization counts shown as pies to population size or to hospital capacity. --Dan Polansky (talk) 09:30, 1 August 2020 (UTC)
The IFR (Infection Fatality Rate) expected to be 0.1-0.27% (currently, the USA has 157,000 deaths), this is similar to the study from a number of Western European nations having their rates at 1% and Geneva's case at 0.35-0.65%. Scientists predict a third spike in the winter (Nov 2020-Mar 2021) of new infections, as well the SARS-CoV-2 antibody tests finds most of them vanish between 2-6 months after infection. The current second spike is about to end, but the USA has to develop a national pandemic plan and federal government backed strategy to counter a third and possibly final spike of the COVID-19 pandemic just when a potential vaccine is approved for mass distribution to the US population. 2605:E000:100D:C571:EC63:3E23:F16C:B2D1 (talk) 18:21, 3 August 2020 (UTC)
Next spike in the U.S. will probably happen much sooner, with opening of K-12 schools (if they are going to open in-person). This is all well known from flu pandemics [15]. One can not isolate kids in the school from each other and teachers. One can not test them for COVID every other day. "K-12 schools and colleges can reopen, but safety should come first, Fauci says". But the safety can not and will not come first, unless this is going to be on-line.My very best wishes (talk) 01:51, 4 August 2020 (UTC)
How do we know that the rate of spread of the covid in pupils and students in schools is the same as that of flu in that group? What solid sources or compelling analysis support that notion? --Dan Polansky (talk) 09:58, 4 August 2020 (UTC)
I agree, we have relatively few examples and studies about COVID-19 right now, such as 260 employees being infected or exposed already at one of the districts [16], so that systematic comparison with flu pandemics is not possible. There will be a lot more information about spreading the COVID in schools and colleges very soon. My very best wishes (talk) 17:58, 4 August 2020 (UTC)
P.S. "Speaking Thursday during a briefing with the Alliance for Health Policy, Fauci said that if he was in a classroom with children who often don't cover their sneeze or cough, he "might very well" wear goggles or a face shield." (CNN). This is going to be like in a hospital. My very best wishes (talk) 16:51, 6 August 2020 (UTC)
Did Fauci say what happens to the covid if Jupiter aligns with the Mars? --Dan Polansky (talk) 08:20, 7 August 2020 (UTC)
More good news on current hospitalizations ("avoid healthcare overload"):
  • Current hospitalizations are behind the recent peak and in decline in Arizona[17], California[18], Florida[19], Louisiana[20], Texas[21].
  • Current hospitalizations are at a peak or slightly after it in Alabama[22], Georgia[23], Mississippi[24], Missouri[25], Nevada[26], Tennessee[27].
Does anyone know of a single page where one can see hospitalization progression charts for all U.S. states, just by scrolling down and without any mouseovers?
--Dan Polansky (talk) 08:26, 7 August 2020 (UTC)
Typo fixed.--Dan Polansky (talk) 09:20, 8 August 2020 (UTC)
More good news:
  • U.S. current hospitalizations[28] continue to decline ("avoid healthcare overload"); from the recent peak of about 60,000, they declined to about 45,000 current hospitalizations.
  • U.S. daily deaths[29] are no longer growing and are at a plateau of about 1,100 new deaths per day; in April, U.S. daily deaths reached above 2,000 new deaths per day.
--Dan Polansky (talk) 09:44, 16 August 2020 (UTC)

I'm sorry--what exactly are you proposing? Are you suggesting things to be added to the page? Should something be altered? I'm not sure whether a "good news" section would be suitable for an encyclopedia format. 2601:1C0:C802:3A00:159D:C91F:EE48:2147 (talk) 06:24, 18 August 2020 (UTC)

Someone might add to the overview section of the article something like this: "At the end of August, current hospitalizations were in decline for over 30 days." A similar statement could be made for confirmed cases, although they plateaued for a while before resuming the decline. However, I am not experienced with the overview section and its proper scope, and I prefer to do charts and remove bad sentences, especially those traced to bad sources. --Dan Polansky (talk) 08:30, 27 August 2020 (UTC)

Plotting tests per 1000, as a comparison

plotOwid.py: 

import sys, csv, argparse

parser = argparse.ArgumentParser(description="Plots OWID. Plots top countries by the last value of the field.")
addarg = parser.add_argument
addarg("fileName", help="E.g. owid-covid-data.csv")
addarg("fieldName", help="E.g. new_tests_smoothed_per_thousand or total_tests_per_thousand")
addarg("countryCode", help="E.g. USA")
addarg("countryCount", type=int)
args = parser.parse_args()

countryLabel = {"USA": "U.S.", "ARE": "United Arab Emirates", "BHR": "Bahrain",
                "MLT": "Malta", "DNK": "Denmark", "NZL": "New Zealand",
                "RUS": "Russia", "IND": "India", "LUX": "Luxembourg"}
# The above needs expansion as required

# Fill valuePerCountry
valuePerCountry = {}
for line in csv.DictReader(open(args.fileName)):
  valueStr = line[args.fieldName]
  if valueStr != "":
    countryCode = line["iso_code"]
    if not countryCode in valuePerCountry:
      valuePerCountry[countryCode] = []
    valuePerCountry[countryCode].append( (line["date"], float(valueStr)) )

# Find top countries
lastValue = []
for country in valuePerCountry:
  lastValue.append( (country, valuePerCountry[country][-1]) )
lastValue.sort(key=lambda pair: pair[1][1], reverse=True)
selectedCountries = [args.countryCode]
extension = [country for country, rate in lastValue[:args.countryCount]]
if args.countryCode in extension:
  extension.remove(args.countryCode)
selectedCountries.extend(extension)
maxLastValue = max([x[1][1] for x in lastValue])

# Collect dates
dates = set()
for country in selectedCountries:
 dates1 = [date for date, rate in valuePerCountry[country]]
 dates |= set(dates1)
dates = sorted(dates)

# Output
lightColors = ["#DBB", "#BDB", "#BBD", "#DDB", "#DBD", "#BDD"]
sys.stdout.write("|legend=Legend\n")
sys.stdout.write("|colors=#00C,")
for country in selectedCountries[1:]:
  if lightColors:
    sys.stdout.write(lightColors.pop() + ",")
  else:
    sys.stdout.write("#DDD" + ",")
sys.stdout.write("\n")
sys.stdout.write("|x = " + ", ".join(dates) + "\n")

for n, country in enumerate(selectedCountries):
  countryMinDate = valuePerCountry[country][0][0]
  countryMaxDate = valuePerCountry[country][-1][0]
  ratesOut = ""
  for date in dates:
    if date < countryMinDate:
      ratesOut += ", "
  for date, rate in valuePerCountry[country]:
    if maxLastValue >= 1000:
      ratesOut += ", %i" % rate
    else:
      ratesOut += ", %.2g" % rate
  for date in dates:
    if date > countryMaxDate:
      ratesOut += ", "      
  sys.stdout.write("|y%i = %s\n" % (n + 1, ratesOut))
  label = countryLabel[country] if country in countryLabel else country
  sys.stdout.write("|y%iTitle = %s\n" % (n + 1, label))

Usage:

plotOwid.py owid-covid-data.csv new_tests_per_thousand USA 5

--Dan Polansky (talk) 14:10, 19 August 2020 (UTC)

Changed to be more generic, able to plot various fields available in OWID. --Dan Polansky (talk) 10:08, 20 August 2020 (UTC)
Fixed maxLastValue and changed .3g to .2g in figure format. --Dan Polansky (talk) 09:06, 27 August 2020 (UTC)

Dropping semilog-chart with cases and deaths but not tests

Semilog-chart with cases and deaths but not tests.

I am again about to drop a semilog-chart with cases and deaths but not tests. It is misleading in that its straigt-line portions suggest there was exponential growth but since tests are not plotted, it is not obvious that the apparent exponential growth had to do with exponential growth of tests. The chart even suggests exponential growth by adding straight trend lines. We must not mislead. --Dan Polansky (talk) 09:16, 27 August 2020 (UTC)

I'm not sure, but just checking: are you arguing that the increase in cases and deaths is primarily because of the increase in tests? I'm not sure if I'm reading this right.
I think these charts are very insightful for the first period of time. Maybe they should simply be cut off at a certain point. I suggest you create an alternative version that you find more helpful, rather than dropping stuff. Adding number of tests is helpful information if there are rapid changes in the number of tests - but the trends are more comparing one day to the next, and it seems fair to assume that these days see roughly the same number of tests. effeietsanders 01:44, 28 August 2020 (UTC)
I am saying that the initial exponential increase of confirmed cases was due to initial exponential increase of tests; this is confirmed in the test positivity rate chart. The word "exponential" in my statements is important and is absent from "increase in cases and deaths is primarily because of the increase in tests"; there is no doubt that even under constant daily test regime, there will be new daily confirmed cases and new covid-coded deaths for some time to come. Again, the word exponential is key. --Dan Polansky (talk) 11:49, 30 August 2020 (UTC)
Moreover, the discussed chart is largely redundant to the third chart in COVID-19 pandemic in the United States#Progression charts, with the difference that the chart we include does not show any exponential trendlines. Using the argument I made, also the chart currently included is problematic but at least it does not suggest any trendlines; tests can be added to the currently included chart. --Dan Polansky (talk) 14:11, 30 August 2020 (UTC)

Death rate trend since July - calculations

I did some mathematical work on US Covid-19 deaths in mid-July, reported and discussed here but since archived. I simply took the figures from this article for 1-15 July and did a least-squares exponential fit; the result was y = 116.7645323 exp(5.178324329 × 10^-3 x), where x is day number, 1 for 1 July, etc., and y is number of deaths. This is a totally mindless mathematical fit with no modelling or assumptions, no selection of data, using, as I said the data from the article - anyone can repeat this. I extrapolated the figures beyond this period; I posted some extrapolated numbers here (now archived), saying very clearly that this was not a prediction. In fact, as I said, I expected that the real numbers would be lower than the extrapolation as measures to control the epidemic kicked in.

I have not done any further work, I'm still using the extrapolation from 1-15 July. The extrapolated figure for 1 September (day 63 from 1 July) is 161,805. The actual number of deaths as reported in the article under the heading "COVID-19 cases in the United States" is 172,978, which I found a shock. It indicates that growth since the first half of July is significantly greater than the exponential growth in that period.

It is very easy to replicate these calculations using data from the article, and also to use a different base period for the extrapolation - there is zero input from me, zero selection, zero knowledge, zero skill (except the ability to do a least-squares exponential fit). Possibly this information will be useful for those working on the article (I haven't made any significant edits beyond improving wording).

Best wishes, Pol098 (talk) 19:41, 2 September 2020 (UTC)

There is nothing above to be taken seriously. I commented on the above in Talk:COVID-19_pandemic_in_the_United_States/Archive_13#Exponential fit. There was nothing meaningful in the fitting. The exponential business is nonsense. Current U.S. new daily deaths, 7-day average, are slowly declining, excellent news; the recent peak was about 1200 new deaths per day and it has now declined to under 900 new deaths per day[30]. Current hospitalizations have been declining for over 30 days[31], and are down from recent peak of 60,000 to today's 35,600. For the lay reader, there is currently no exponential growth of total deaths since if that were so, there would be exponential growth of daily new deaths, which are declining instead. --Dan Polansky (talk) 09:16, 3 September 2020 (UTC)
If the reader cannot resist the temptation to look at death projections, I can recommend Talk:COVID-19 pandemic in the United States/Archive 14#Simplistic death projection, which includes my very simplistic projections and also projections by nobel laureate Michael Levitt. --Dan Polansky (talk) 09:34, 3 September 2020 (UTC)
I generally agree with Dan Polansky; mine was a purely mathematical exercise, and I expected it to be overly pessimistic. The one comment I disagree with, if taken literally, is "The exponential business is nonsense". While, indeed, it isn't a prediction and shouldn't be taken as such, the exponential fit for the limited period in which I applied it is very good, surprisingly so, it is the appropriate simple function to fit the figures. There is a graph that is sometimes added to the article, deleted when it goes out of date, and re-added when it is updated (currently not included) which shows the figures to be visually very close to a straight line for extended periods if plotted on a logarithmic scale, i.e., the curve is exponential. So, the exponential nature of the growth is not necessarily significant or predictive, but it is a fact of the past progression. Best wishes, Pol098 (talk) 10:49, 3 September 2020 (UTC)
The exponential business really is nonsense; as per #Dropping semilog-chart with cases and deaths but not tests above, the initial exponential increase of confirmed cases was due to initial exponential increase of tests, and a similar consideration holds true for initial growth of covid-coded deaths. The daily new deaths have been in decline since Aug 1, and therefore, the total death curve has not been exponential at least since Aug 1, over 30 days. That is a very obvious consideration. --Dan Polansky (talk) 11:14, 3 September 2020 (UTC)

Let me plot the total deaths on a normal scale:

--Dan Polansky (talk) 11:23, 3 September 2020 (UTC)

Let me plot another chart, one that shows for each date the ratio of its total death value to the value of the previous date, of that 7-day moving average. That is, the chart shows what the base for exponential growth would be if it really were exponential growth:

--Dan Polansky (talk) 11:46, 3 September 2020 (UTC)

And let me show only part of the chart so that the low values are more distinct:

--Dan Polansky (talk) 11:55, 3 September 2020 (UTC)

Just for the hell of it I've done another mindless mathematical exercise, which I do not claim reflects reality at all (just that it's mathematically accurate). Looking at the last of the 3 graphs of Dan Polansky, I eyeball a rate of increase of very roughly 0.5% deaths per day (assuming that the graph approximates to a horizontal straight line for the last few weeks). I have made just one mathematical calculation, with no selection or tuning, I just plugged in a daily increase of 0.5% from the extrapolated figure of 163490 (lower than the actual reported number) for today, 3 Sep 20, and ran it to 17 Nov 20, which is where I ended the exponential fit. I find the exponential fit (extended from the first 15 days of July) extrapolates to 241,079; a 0.5%/day increase from 4 Sep gives 241,033 for the same date, which I find astonishingly close to the exponential, particularly as I just eyeballed the 0.5% figure. The fit is close for every day, 17 Nov is not "privileged" or specially selected. Making a brief foray into reality, the %/day curve does seem to be trending down since the beginning of August (steadily reducing from 0.8% to 0.55%), so hopefully the numbers produced by the mindless mathematics are pessimistic. And obviously any major medical development will change things radically. Pol098 (talk) 13:14, 3 September 2020 (UTC)
And yet the total death curve was growing less than linearly for the whole of August, let alone exponentially. I don't understand the above mindset. This whole talk of "exponential growth" used for modelling this epidemic is a dangerous nonsense, one that I have fallen for myself initially. (I hate to admit as much.) --Dan Polansky (talk) 13:57, 3 September 2020 (UTC)

Too many graphs/charts

I stopped by this article for the first time in quite a while today, and I see it currently exceeds the PEIS limit, and also has a ton of charts and graphs. Those are presumably related, so my advice for any of you trying to figure out how to get it back under the limit would be to drop the unneeded ones. As to which ones should go, I'll leave that to those of you who have been following this page more closely. {{u|Sdkb}} talk 08:05, 26 August 2020 (UTC)

Most of the charts are useful and non-rendundant. To address the PEIS problem, one should investigate the actual largest contributor to the problem. For a start, the transcluded Template:COVID-19 pandemic data/United States medical cases by state shows abundant low-value-added use of templates.
The Template:COVID-19 pandemic data/United States medical cases by state provides a very good quick overview of the state of affairs in various parts of the country in a quick readable format. It's more difficult to read historical data points and keep scrolling to the bottom in tables where cases are listed by dates. The the other tables are more difficult to read in a script for researchers as well. --GoodOldSam (talk) 19:54, 3 September 2020 (UTC)
Should some charts be removed, I would see the three charts in Number of U.S. cases by date section as the foremost candidates: they contain a line for each state (50 lines in total?) and thus are quite large in terms of wikitext (about 39 KB), and yet the value they provide seems rather limited. By contrast, all the charts in Progression charts section have about 57 KB, yet provide much more valuable picture. (For reference: Wikipedia:PEIS.)
To help a little, I went ahead and reduced the data amount in one of the charts I have added: diff. --Dan Polansky (talk) 09:04, 27 August 2020 (UTC)
The all-cause death graphs are the least important; I'm sure various causes of deaths are affected to different degrees (deaths from flu(non-covid-19), car accidents, roller coaster accidents, etc) so pooling across causes despite the interaction with the pandemic isn't very appropriate. Also the deaths by year isn't adjusted by population, or population age, so it's hard to see the interaction, but the graphs above already make the case that deaths have increased this year. Of 19 (talk) 04:56, 29 August 2020 (UTC)
To the contrary, I find the all-cause death graphs to be very important, showing the covid in proportion to baseline deaths and showing that covid deaths are very likely more than just misattributed deaths for other causes. As for "so pooling across causes despite the interaction with the pandemic isn't very appropriate", that makes no sense to me at all. My words seem confirmed by the introductory paragraph of mortality.org[32]: "In response to the COVID-19 pandemic, the HMD team decided to establish a new data resource: Short-term Mortality Fluctuations (STMF) data series. Objective and internationally comparable data are crucial to determine the effectiveness of different strategies used to address epidemics. Weekly death counts provide the most objective and comparable way of assessing the scale of short-term mortality elevations across countries and time." --Dan Polansky (talk) 11:54, 30 August 2020 (UTC)

Recently Removed State Cases Table

First of all, thanks to everyone who contributes to this page, and especially to the person who periodically updated what I believe was titled the State Cases Table. To clarify if I got the name of the table wrong, it contained the following columns (U.S. state or territory, Cases, Deaths, Recov., Hosp.). Over the past five months I used the data from this table to study the slow but steady growth in the number of COVID-19 deaths from the 10 states with the lowest number of deaths. I am sorry to see that support for the table was dropped. Could whoever supported that table possibly point me to the source for that table? Thank you. Bobanello (talk) 20:55, 3 September 2020 (UTC) Bobanello

Fixed in diff. --Dan Polansky (talk) 05:54, 4 September 2020 (UTC)

Demographics pie chart

I am considering to switch the demographics bar chart to pie chart. I have the following:

COVID-19-related deaths by age group:

One thing I don't like is that the x-values are not shown in the chart, only in the legend. Does anyone know how to add the x-value lables directly to the chart?

Also, the values are shown oddly for the small portions; they should ideally not be shown at all for the small portions and only be shown for portions that are large enough to comfortably host the y-value text. --Dan Polansky (talk) 13:20, 4 September 2020 (UTC)

I'm confused. Earlier, you make the argument that it is silly to show absolute numbers for the US without normalizing it per capita - but wouldn't the same argument apply even more strongly here? It is hard to interpret these numbers without providing context of how big these age groups are to begin with. For the US population, most people at least know it's about 300M, and the world population is about 6B. I would have a harder time guessing the percentage of people 15-24 years old.
Aside from that, the buckets seem somewhat artificial and overly granular for young age. effeietsanders 02:32, 5 September 2020 (UTC)
That's a good point: the absolute death counts per age group are not adjusted for age group population size. However, that would mean that the portion of the old-age people would be even larger when adjusted for age group population size. That said, the distortion is not so huge as in intercountry comparisons of death counts. I'll think about it. --Dan Polansky (talk) 06:12, 5 September 2020 (UTC)

"Trumpvirus" listed at Redirects for discussion

A discussion is taking place to address the redirect Trumpvirus. The discussion will occur at Wikipedia:Redirects for discussion/Log/2020 September 5#Trumpvirus until a consensus is reached, and readers of this page are welcome to contribute to the discussion. –Deacon Vorbis (carbon • videos) 13:36, 5 September 2020 (UTC)

News agencies

Dan Polansky: I object to your edit summary, "...sources to Reuterns: we already know the numbers without Reuters and the rest is their biased story telling as part of mainstream media living from producing bad news". What possible good can come from badmouthing Reuters? -SusanLesch (talk) 18:47, 4 September 2020 (UTC)

I see no arguments, evidence, or analysis above, and therefore there is nothing to respond to with substance. --Dan Polansky (talk) 06:36, 5 September 2020 (UTC)
All right. That's one way to answer a question. -SusanLesch (talk) 18:53, 5 September 2020 (UTC)
I thought it was a rhetorical question. Let me articulate the obvious, then. Mainstream media are unreliable and non-neutral; by refusing to uncritically take over problematic sentences from mainstream media, we make the encyclopedia more reliable and neutral. Reuters is part of mainstream media. The Reuters article[33] mentions IHME without at the same time indicating that IHME is unreliable: "The Institute for Health Metrics and Evaluation is anticipating an uptick in COVID-19 cases in the coming months, resulting in around 300,000 total deaths by December, and a nearly 75% increase in hospitalizations." They are doing no serious journalism, just parotting unreliable sources without critical assessment of the sources. If they wanted to quote IHME, they should have included reservations about IHME in the same paragraph; they did not. Fail. --Dan Polansky (talk) 06:40, 6 September 2020 (UTC)
It is unreasonable to expect a global news agency to produce news at the level of detail you seem to require. I suggest you read news agency which says "All four began with and continue to operate on a basic philosophy of providing a single objective news feed to all subscribers; they do not provide separate feeds for conservative or liberal newspapers." Don't you realize we are very lucky to have them? Next time your city has an earthquake or an election what other dependable source do you plan to consult? I take offense because the business model for most of journalism has been threatened by the web and I don't enjoy it when some guy like you decides to denigrate the entire field. The other three fourths of your answer is your assertion that IHME is unreliable which is your opinion and is not a proven fact. -SusanLesch (talk) 16:34, 6 September 2020 (UTC)
It is not unreasonable at all; it is their fulltime job, and it is very easy to do a background check on IHME. --Dan Polansky (talk) 12:07, 7 September 2020 (UTC)
If, on the other hand, it is unreasonable to hold mainstream media to the kind of standard that I mentioned, we obtain the conclusion anyway: mainstream media are unreliable on science since it is unreasonable to require of them the kind of background checking and checking for reliability of their sources that would make them reliable. --Dan Polansky (talk) 15:41, 7 September 2020 (UTC)

Mortality in the United States

The lead ought to say that the total number of deaths in the U.S. is the world's highest. My source is Johns Hopkins Cases and mortality by country. Why doesn't the first paragraph state this very basic fact? -SusanLesch (talk) 17:18, 20 August 2020 (UTC)

The fact should be excluded since it is irrelevant: it above all reflects on how populous a country is. It would be hard for a small country to lead by the number of deaths no matter how bad its covid handling. The discussed statement is true, but irrelevant and arguably misleading. Instead of the absolute number, the article relevantly states the relative number AKA death rate: "As of August 20, its death rate had reached 529 per million people, the eleventh-highest rate globally." --Dan Polansky (talk) 09:32, 21 August 2020 (UTC)

Specific outbreaks, plagues, and epidemics in the United States lists a number of epidemics and most of them carry a fatality number in the first paragraph. List of epidemics offers only the total number who died. Hardly irrelevant. I'm tired of arguing with you. -SusanLesch (talk) 19:47, 21 August 2020 (UTC)

If you're talking blame, then such a number would be weird to mention maybe. However, if you're talking about the impact that the pandemic has had on a country, it seems fair to also point out that the number is highest in absolute sense. For balance sake, you may want to point out as well how that compares to a typical impact on other countries (e.g. mortality). effeietsanders 21:49, 21 August 2020 (UTC)
PS: @Susan: the way I read it, Dan is not really against mentioning the number, but rather whether that is the 'highest' country in the world.
Right. For a comparison between countries, the absolute death count is meaningless. And "the world's highest" is a comparison between countries. As for mentioning the absolute death count, it is in the infobox, and I do not propose to remove it from there. --Dan Polansky (talk) 12:14, 23 August 2020 (UTC)
The impact of a pandemic on a country really does not depend directly on the absolute count; it depends on the relative count, that is, deaths per million pop. Similar for unemployment: the absolute count of unemployed people does not directly reveal the severity of unemployment; it is the percent of people unemployed that indicates the severity. --Dan Polansky (talk) 12:22, 23 August 2020 (UTC)
Per all the examples in Wikipedia's list of epidemics I added a total to the lead paragraph. That number is important when we compare epidemic to epidemic. -SusanLesch (talk) 17:01, 23 August 2020 (UTC)
I removed the sentence in diff: the number is in the infobox and the indicated relation to the world's count is likely to be misleading. The non-misleading death per million is already in the article. Unlike the present article, list of epidemics does not give epidemics per country, and therefore, inter-county comparison does not become a problem in articles it links to. --Dan Polansky (talk) 20:24, 23 August 2020 (UTC)
I would request to revert that - the phrase was quite neutral, and I disagree it is meaningless. We should not rely on infoboxes to confer essential information. The fact that about 20% of the worldwide deaths are in the US, is a meaningful piece of information in an article about the pandemic in the US. I would agree that this is misleading in an article about the pandemic in general - but if you're describing the US, it helps to provide some context of how it relates to the worldwide pandemic. effeietsanders 20:57, 23 August 2020 (UTC)
What I removed is this: "As of August 2020, 170,000 of the world's 800,000 deaths from COVID-19 occurred in the U.S." The comparison to world's absolute death count is not neutral; it artificially makes U.S. look worse than it is. This becomes obvious when one uses the same sentence form for e.g. Belgium: "9,872 of the world's 800,000 deaths from COVID-19 occurred in Belgium." In this sentence, Belgium does not look bad yet it has more deaths per capita than U.S., and that is the true indicator of severity. The sentence removed by me is another attempt to sneak in invalid inter-country comparison of absolute numbers. --Dan Polansky (talk) 08:08, 27 August 2020 (UTC)
I think you're over interpreting language. This is not what I would read into that at all - it states clearly that the US is heavily impacted, but also clearly signals that it is not just the United States. An example of why it can be confusing in a different context: in the article Ebola virus epidemic in Liberia does mention how many people died, but it does not mention anything about the worldwide impact of the virus. This means we lack context that the 4800 deaths was almost half the worldwide death count, showing that this was an epicenter of the disease.
It feels like you're reading some kind of judgement into the sentence, while it is mostly providing context on the worldwide stage. effeietsanders 01:51, 28 August 2020 (UTC)
I explained above the comparison to be misleading, but apparently to deaf ears. In any case, you noticed the comparison is not made in Ebola virus epidemic in Liberia; do you know of a single Wikipedia article making that comparison? Let us notice that the comparison was inserted by someone who said "The lead ought to say that the total number of deaths in the U.S. is the world's highest", proposing to add sophistry to the lead; that same person seems to think that the PIRG letter is more than a low-grade timewaster. We shall be neutral. --Dan Polansky (talk) 12:06, 30 August 2020 (UTC)

This article needs to say to readers that the number of deaths in the U.S. is the highest in the world. That is, the death toll, or absolute number of total deaths, simply, the actual number of people who died here in context. It is true per the best source we have, Johns Hopkins University. It is not sneaky or sophistry, invalid or dubious or irrelevant; those are your words and interpretations. -SusanLesch (talk) 16:41, 30 August 2020 (UTC)

@Dan: I'm not sure if this ad hominem is very helpful. I have heard your argument about neutral, I just don't agree that your removal of this context is actually making the article more neutral; au contraire. My impression is that your attitude towards removing data that feels too painful to mention, may result in downplaying the impact of this pandemic on the United States - which by itself is again not unbiased. effeietsanders 20:55, 31 August 2020 (UTC)
To avoid repetition of what I already said above, I will referain from raising obvious objections to some points above. The reader is well advised to consult e.g. File:COVID-19 Outbreak World Map Total Deaths per Capita.svg to see how the death rate in the U.S. compares to other countries, and get a relevant picture rather than partisan invalid comparison of absolute numbers between countries. It would be also of interest to have a chart or table of excess death per capita for various countries, but I do not know of any source providing such a table.
Outstanding unanswered question: you (Effeietsanders) noticed the comparison is not made in Ebola virus epidemic in Liberia; do you know of a single Wikipedia article making that comparison? That is, do you know of a single Wikipedia article that is on an epidemic in a particular country and compares the absolute deaths in that country with worldwide deaths? Or do you know of a peer-reviewed scientific article making such a comparison? --Dan Polansky (talk) 09:58, 2 September 2020 (UTC)
Why don't you address any of the specific arguments I made above? You just repeated the same assertion without any proof or further articulation. Why don't you for instance address this: "it [the absolute death count] above all reflects on how populous a country is". --Dan Polansky (talk) 14:56, 2 September 2020 (UTC)
Dan Polansky, addressing your point: if your measure is true, "[the absolute death count] above all reflects on how populous a country is", then the US must have 21.5% of the world's population. -SusanLesch (talk) 18:02, 2 September 2020 (UTC)
It's above all, not solely. The death count depends on 1) death rate (the relevant measure), and 2) population. We already report 1) and use it for inter-country comparison; 2) just adds confusion to the measure. The U.S. death rate is on the similar order as many other countries (500-1000 per million pop), and that is the relevant comparison. Put differently, as for death rate, the U.S. is in the same first league as many other countries, and which country has which exact rank in that league is of no scientific significance. Of note is that we have no reliable data from the very populous China; they don't even tell us how many tests they are doing. --Dan Polansky (talk) 09:01, 3 September 2020 (UTC)
Dan Polansky, and others. Your editing of the following RFC is welcome before I post it about 24 hours from now. Two weeks is too long to argue and we don't appear to be getting anywhere. -SusanLesch (talk) 14:12, 3 September 2020 (UTC)

Proposed RFC

Should the lead inform the reader that the United States has more than 20% of the world's mortality from COVID-19?
  • One view prefers deaths per capita as a measure of severity.
  • The other view is that the context of the US fraction is important for understanding.
Yes or No. Previous discussion. ::::-SusanLesch (talk) 14:12, 3 September 2020 (UTC)

Semi-protected edit request on 6 September 2020

Request 1

The introduction says that the US has the eleventh highest death rate worldwide, and there's a little note saying that it's ninth if microstates are skipped. Could you delete the note and put its information into the sentence?

"As of September 2, the U.S. death rate had reached 563 per million people, the eleventh-highest rate globally, and ninth-highest if European microstates are excluded." 2601:5C6:8081:35C0:1C4:1766:5D51:7D23 (talk) 23:47, 6 September 2020 (UTC)

 Done -SusanLesch (talk) 03:13, 7 September 2020 (UTC)

Request 2

"67,000 lives could be saved with 95% universal mask-wearing" appears at the very end. "Universal" means 100%. Could you remove "universal" so the sentence makes sense? 2601:5C6:8081:35C0:1C4:1766:5D51:7D23 (talk) 23:59, 6 September 2020 (UTC)

 Done Thank you for the correction. -SusanLesch (talk) 03:08, 7 September 2020 (UTC)
I think this actually is more confusing. The way I read it, it was '95% of universal' but '95% mask wearing' suggests to me that somehow people wear the mask either 95% of the time, or that the mask type is '95%' (which is coincidentally also an actual mask type). I would suggest to find a different phrasing :) effeietsanders 22:22, 7 September 2020 (UTC)
You are right. Thank you, I hadn't stopped to realize that N95 is a filter. Hope that's better. -SusanLesch (talk) 23:38, 7 September 2020 (UTC)

Mass edits without rationales

An editor has mass-reverted a large number of separate improvements to the article lead, but did so with no rationale. Each of the edits they reverted en masse were made with a rationale, however, and any changes should be made with an explanation and/or discussion. Mass deletions or reversions without an explanation obviously go against guidelines. --Light show (talk) 18:02, 10 September 2020 (UTC)

Greetings, Light show. Hold on a minute, you made more edits today than I did. Also, I gave a rationale, "restoring lead from yesterday, no reason to diminish deaths and amplify a trade agreement." I felt that backing up a whole day was the only way to restore the lead. Apologies if you disagree. I am happy to explain my edit further. My goal is a clear and simple lead that honors the 190,000 people who have died here.
If I counted correctly, you made about 19 edits today, among them 8 edits identified as "top". This left the lead with the number of deaths obscured by 20 words and 4 superscripted notations. You moved up or added 2 short sentences of statistics, one double cited, and the other cited plus a readers note. Then Michelangelo1992 restored information that I had just put into prose per an edit request 4 days ago, with an edit summary, "Re-added JHU source and microstate information that were removed without explanation." So, we wound up with 20 words with 5 superscripted conditions. All of this is very difficult for a reader to parse.
The second part of my edit summary refers to your addition, "That same day, President Trump, during a speech announcing his signing of the United States–Mexico–Canada Agreement....", putting a prominent wikilink in the 7th sentence and 2nd paragraph. I appreciate your adding the context, but with this placement it catches the reader's eye more than the topic of the article.
Are you familiar with the publisher Springer Nature formerly Springer-Verlag? They have an online tutorial about writing in English called "Avoiding common language issues." My rationale "diminish deaths" relates closely to stress position. I hope this helps. Best wishes. -SusanLesch (talk) 19:07, 10 September 2020 (UTC)
Hi, thanks for explaining. I feel that to keep things clearer we should take one edit at a time. It might even help to segment them with a subsection to this section if it gets that involved, although I don't think it should. It's not even a matter of actually disagreeing, since I'm only trying to abide by guidelines, but more of noting apparent errors in your explanations:
First, you're right that I made eight edits to the lead. But the other comments about why you reverted them are unclear. For instance, you wrote that the "number of deaths [were] obscured by 20 words..." In fact, I did nearly the opposite, not by "diminishing deaths," as you wrote in your rationale, but merely taking case and death details from the last paragraph and adding them to the first one, so the subject was not split up.
The other part of your single rationale was that my edits "amplify a trade agreement." The word "amplify" is unusual here. As you know, there has been much ado about Trump "downplaying" the outbreak and early on stating it was "under control." As part of the chronology, I added that "Trump, during a speech announcing his signing of the United States–Mexico–Canada Agreement, stated that the virus outbreak in China was 'under control and a very small problem in this country.'" The obvious purpose of mentioning when and why the statement was made was to not mislead readers by not showing his comment in proper context. If we just had him saying that during a speech, many would assume the purpose of the speech was about the outbreak. Of if we didn't even mention a speech, and left it as "he said...", many might assume he said it during an interview, or press conference, or in some writing. Any of those assumptions by a reader would have been wrong, as the comment was made briefly during a speech about a specific topic unrelated to the outbreak. According the source, it was apparently the first time he made that comment.
In any case, since that "under control" comment has become a news story, as noted in the section before this one, adding context to his statement seemed valuable to many readers. It was not intended to "amplify" or make the noted subject of the speech "prominent" by including a simple link, which you somehow feel "catches the reader's eye more than the topic of the article."
There was no rationale for reverting a logical edit like this one, which simply moved a dated event to chronological order. Or for this one, which was citing the source accurately.
You also mentioned some material which I put in Notes, with a superscript, such as this one. In fact leaving it in the lead at all was unnecessary, since it was merely a news item based on someone's speculations. Nor was it in the article body, or could have been, being a speculation. So I just made it a note in the top paragraph for the time being. In any case, those are just a few of the reasons why a mass reversion of edits were uncalled for and if anything, even with no discussion first, should have been made individually with a clear rationale. My suggestion is to self-revert your edit which was made in good faith, and let's do this right from here on. --Light show (talk) 20:37, 10 September 2020 (UTC)
The final fact of a paragraph, in this case the first paragraph, carries a lot of weight in readers' minds. That weight is right now exactly where it should be. So no, I cannot agree to revert myself. I am in school and can't get to this until tomorrow, but will try to work out a version for both of us in my sandbox. Maybe you missed my point about the stress position. Here is is again in "The Science of Scientific Writing." No way do I think I understand all that. But I do know that the first paragraph is important and that it shouldn't ask the reader to decide between three citations, two footnotes, or skip it altogether. -SusanLesch (talk) 23:18, 10 September 2020 (UTC)
Per your reply about stress positions, note that the current version which you restored has other more serious stress-related defects. Such as 15% of the lead's text, added to the final paragraph, is speculation, and not usable. While the first paragraph which you are focused on, was originally this, to which I added some other relevant material from the article, seen here. I apologize if you feel that the added text somehow "diminished deaths," despite the fact that the added text was also about deaths. As the material came from the body, no citations are actually necessary.--Light show (talk) 01:40, 11 September 2020 (UTC)
I noted that there were several significant changes to the lede yesterday and they appear to be restored. I think that the current (AKA prior to Light Show's edits) version is better both for clarity and flow, but that may be a product of the fact that I am simply used to it. I think that rather than making such major changes as a series of edits, it would be easier to come to consensus if we discuss those edits individually. As it is, there were such significant changes between the versions that I found it hard to compare them to the old version directly. Are there any specific changes that you think we should make to the lede, @Light show:? Michelangelo1992 (talk) 16:22, 11 September 2020 (UTC)
As was noted, I made eight changes to the lead. You can click the diff for any of those, for instance, then compare and comment, since they had a rationale. --Light show (talk) 17:43, 11 September 2020 (UTC)

Proposed rewrite

Light show, sorry it was my firm opinion that breathlessly citing statistics right after the death toll distracts from those deaths. Imagine yourself at a friend's funeral where the mortuary company pipes in a loud radio station of talk show chatterboxes.

As promised I worked out a lead that incorporates your edits, plus some things that emerged in our discussion. Right here. What do you think? Outline of paragraphs:

  1. intro
  2. history (timeline), global and federal responses
  3. state and local responses
  4. impacts: risk by ethnicity and race, social and economic
  5. statistics

Notes

  • Per your note above, I removed the 15% from the last paragraph.
  • Also per your notes, sometimes no citations are necessary. I included them here but hope many can be removed.
  • American Samoa declared an emergency on January 29, but FEMA records approval on April 17. I adopted April 17 so everybody is covered.
  • Still missing is the US on world stage.
  • There may be a better way to present mail-in voting.
  • Also maybe better wording is needed for "Clusters of infections and deaths have occurred in many areas."
  • Much of this comes from your version (the version I started with).

-SusanLesch (talk) 23:17, 11 September 2020 (UTC), link updated -13:31, 12 September 2020 (UTC)

Doesn't seem an improvement, as you surprisingly rewrote the entire lead. The rewrite now hits readers with a timeline factoid jungle, while comprising over 50% of the lead. Note the first large section of the article itself is already a Timeline. So I would opt for greater balance, closer to the lead in COVID-19 pandemic in the United Kingdom. The lead should cover a broader spectrum and summary of the article, with few if any citations even needed.
The new text following the timeline paragraph is heavily politicized, with some material even lacking clear relevance to the surrounding text: "Preparations for fall elections were challenged in April, when President Trump said, 'I think mail in voting is a terrible thing,' although he voted by mail himself." In fact it's the only quote in the rewrite, nor is it part of the article in any case. There is no mention about testing, treatments, vaccines, nursing homes, co-morbidities, etc.
So I would simply leave the lead as is and editors can deal with improvements on a piecemeal basis. If material is "tightened," for instance, and someone objects, they can revert with a clear rationale and/or discuss. Thanks for the effort to improve the lead.--Light show (talk) 01:03, 12 September 2020 (UTC)
Maybe somebody else will step up! Humbled by your great jungle. -SusanLesch (talk) 13:28, 12 September 2020 (UTC)

New article needed: COVID-19 Testing in the United States?

The section "Testing" is substantially longer than any other section in the article. I believe reducing it to approximately two paragraphs, and migrating the bulk of the information into a new article, would be beneficial for readability. There is already an article called COVID-19 testing, but said article appears to be more about testing itself, rather than a USA-specific article. I wanted to get other editor's opinions prior to making a BOLD move into a new article. Michelangelo1992 (talk) 17:50, 9 September 2020 (UTC)

Do you think another section could be separated? This one stands out. Preparations made after previous outbreaks. In place of all that I would rather see information on COVID-19 hospitalization and death by race/ethnicity. -SusanLesch (talk) 14:42, 11 September 2020 (UTC)
I will begin working on a draft for the new testing page today. I think that the "preparations" section would be a very good standalone article as well. I am struggling a little bit on the title, but there is plenty of reliable information about previous pandemic preparation that can be sourced for it. Michelangelo1992 (talk) 16:25, 11 September 2020 (UTC)
Update: The new article COVID-19 testing in the United States has been created and I have migrated a lot of information from this article there. Please feel free to contribute there. I have minimized the "Testing" subsection in this article, but please feel free to expand slightly if other editors feel that more needs to be added. Thank you all! Michelangelo1992 (talk) 18:49, 12 September 2020 (UTC)
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