COVID-19 - Facts and Information Only Topic

[Mr Info]

Pfizer/BioNTech vaccine positive results (antibodies produced; no serious side effects) from Phase I/II will lead to larger Phase III study (30k) starting end of July. It is an mRNA vaccine  like Moderna’s. Pfizer ramping up for 100 M vaccines by end of 2020.

https://apple.news/ABqlYBoVHTjGejJd88dpTQQ

Posted 19 hours ago (edited)

On 7/3/2020 at 3:21 PM, spartacus said:

with that schedule, how can they ensure that the vaccine lasts longer than a few months

Very briefly...double-blind studies and test participants regularly for C19 antibody production and C19 presence. Correlate data to determine whether those given vaccine did not produce C19 infections.

Actually, if C19 flare-ups continue that may help with determining efficacy of vaccine. There needs to be virus activity for evaluating a vaccine.

 

More info: https://www.google.com/amp/s/www.technologyreview.com/2020/05/26/1002191/how-show-a-coronavirus-vaccine-prevents-covid-19/amp/

Edited 18 hours ago by Mr Info

[What you say is correct, @Mr Info, but I think @spartacus point is that if the vaccine is studied for short-term effectiveness in a PhIII trial of a few months starting now before being approved for use in January, there is no way to determine whether the duration of the vaccine protection is more 5 months.  Valid point.  A number of experts have pointed out that we may wind up with an initial short-term effective vaccine that will hopefully help extinguish outbreaks in congregate living facilities, and an eventual different vaccine with long term effects.  And don't neglect the importance of inducing a T cell response, it's hard to measure but may be key -Hapless]
 

 

 

[RocCityRoller]

From Travel Medicine and Infectious Disease, pulled from Elseveir.

https://www.sciencedirect.com/science/article/pii/S1477893920302179

 

Volume 35, May–June 2020, 101738
Hydroxychloroquine and azithromycin: A retrospective analysis of 1061 cases in Marseille, France

MatthieuMillion^ab1Jean-ChristopheLagier^ab1PhilippeGautret^ac1PhilippeColson^abPierre-EdouardFournier^acSophieAmrane^abMarieHocquart^aMorganeMailhe^aVeraEsteves-Vieira^aBarbaraDoudier^aCamilleAubry^aFlorianCorreard^deAudreyGiraud-Gatineau^acfgYanisRoussel^abCyrilBerenger^acNadimCassir^abPisethSeng^abChristineZandotti^a…DidierRaoult^ab

 

Methods

We retrospectively report on 1061 SARS-CoV-2 positive tested patients treated for at least three days with the following regimen: HCQ (200 mg three times daily for ten days) + AZ (500 mg on day 1 followed by 250 mg daily for the next four days). Outcomes were death, clinical worsening (transfer to ICU, and >10 day hospitalization) and viral shedding persistence (>10 days).

Results

A total of 1061 patients were included in this analysis (46.4% male, mean age 43.6 years – range 14–95 years). Good clinical outcome and virological cure were obtained in 973 patients within 10 days (91.7%). Prolonged viral carriage was observed in 47 patients (4.4%) and was associated to a higher viral load at diagnosis (p < .001) but viral culture was negative at day 10. All but one, were PCR-cleared at day 15. A poor clinical outcome (PClinO) was observed for 46 patients (4.3%) and 8 died (0.75%) (74–95 years old). All deaths resulted from respiratory failure and not from cardiac toxicity. Five patients are still hospitalized (98.7% of patients cured so far). PClinO was associated with older age (OR 1.11), severity of illness at admission (OR 10.05) and low HCQ serum concentration. PClinO was independently associated with the use of selective beta-blocking agents and angiotensin II receptor blockers (p < .05). A total of 2.3% of patients reported mild adverse events (gastrointestinal or skin symptoms, headache, insomnia and transient blurred vision).

Conclusion

Administration of the HCQ+AZ combination before COVID-19 complications occur is safe and associated with a very low fatality rate in patients.

Edited July 4, 2020 by Hapless Bills Fan
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[ExiledInIllinois]

Anybody post this? The relationship  between  air conditioning  and The 'Rona:

 

https://wwwnc.cdc.gov/eid/article/26/7/20-0764_article

 

 

On 7/2/2020 at 8:01 AM, plenzmd1 said:

Think the theory was heat meant people outside more, and outside better than inside The states with huge spikes getting hit hard now are past heat, and into scorching territory, forcing people back inside. Not all people are crazy like you and like to eat outside when its 88 and 80% humidity!

 

BTW, they tracking "cooling" days now...

Read the A/C study.

 

We are a first world  country.  Lots of air conditioning. 

[Mr Info]

10 hours ago, ExiledInIllinois said:

Anybody post this? The relationship  between  air conditioning  and The 'Rona:

 

https://wwwnc.cdc.gov/eid/article/26/7/20-0764_article

 

 

Read the A/C study.

 

We are a first world  country.  Lots of air conditioning. 

This has been the only published article, thus far, correlating the spread of C19 and air conditioners. It would lend more credence if another peer-reviewed paper were published corroborating this.

There is this article questioning its conclusion. 
https://www.healthline.com/health-news/can-air-conditioning-spread-covid-19-probably-not

This article uses expert opinion to dismiss but no evidence. Would like to see more data to support this type of transmission than the one paper.

[Hapless Bills Fan]

18 hours ago, RocCityRoller said:

From Travel Medicine and Infectious Disease, pulled from Elseveir.

https://www.sciencedirect.com/science/article/pii/S1477893920302179

 

Volume 35, May–June 2020, 101738
Hydroxychloroquine and azithromycin: A retrospective analysis of 1061 cases in Marseille, France

MatthieuMillion^ab1Jean-ChristopheLagier^ab1PhilippeGautret^ac1PhilippeColson^abPierre-EdouardFournier^acSophieAmrane^abMarieHocquart^aMorganeMailhe^aVeraEsteves-Vieira^aBarbaraDoudier^aCamilleAubry^aFlorianCorreard^deAudreyGiraud-Gatineau^acfgYanisRoussel^abCyrilBerenger^acNadimCassir^abPisethSeng^abChristineZandotti^a…DidierRaoult^ab

 

Methods

We retrospectively report on 1061 SARS-CoV-2 positive tested patients treated for at least three days with the following regimen: HCQ (200 mg three times daily for ten days) + AZ (500 mg on day 1 followed by 250 mg daily for the next four days). Outcomes were death, clinical worsening (transfer to ICU, and >10 day hospitalization) and viral shedding persistence (>10 days).

Results

A total of 1061 patients were included in this analysis (46.4% male, mean age 43.6 years – range 14–95 years). Good clinical outcome and virological cure were obtained in 973 patients within 10 days (91.7%). Prolonged viral carriage was observed in 47 patients (4.4%) and was associated to a higher viral load at diagnosis (p < .001) but viral culture was negative at day 10. All but one, were PCR-cleared at day 15. A poor clinical outcome (PClinO) was observed for 46 patients (4.3%) and 8 died (0.75%) (74–95 years old). All deaths resulted from respiratory failure and not from cardiac toxicity. Five patients are still hospitalized (98.7% of patients cured so far). PClinO was associated with older age (OR 1.11), severity of illness at admission (OR 10.05) and low HCQ serum concentration. PClinO was independently associated with the use of selective beta-blocking agents and angiotensin II receptor blockers (p < .05). A total of 2.3% of patients reported mild adverse events (gastrointestinal or skin symptoms, headache, insomnia and transient blurred vision).

Conclusion

Administration of the HCQ+AZ combination before COVID-19 complications occur is safe and associated with a very low fatality rate in patients.

 

A couple of comments here.  First, the last name (that's the "running the show" author) is Didier Raoult, who was right off the bat with claiming "100% cure" for hydroxychloroquine/azythromycin.  This is a better study than some of his earlier ones - better endpoints (death, transfer to ICU), more patients. 

 

This is still not a controlled study.   Nor was it performed on very sick patients.  From the paper:

"Data was collected on patients included from March 3rd to March 31st. Individuals with PCR-documented SARS-CoV-2 RNA from a nasopharyngeal sample [19], were prescribed HCQ+AZ early treatment, as standard care, whether or not they had symptoms, with treatment initiation at our day-care hospital (inpatients) or at our infectious disease units (inpatients) when required."
 

So - If you take 1061 patients who were not very ill or necessarily symptomatic and DON"T give them hydroxychloroquine and azythromycin, how many of them would have good clinical outcomes in 10 days?  How many of them would have cleared viral titer in 10 days?  That is the question, and it needs to be asked because 2.3% adverse events is not insignificant if the answer is "roughly the same number".

360 patients were excluded from the study, including 33 for cardiac abnormalities and 66 for "unspecified reasons"  It's important to note that their screening protocol for inclusion included an EKG, and patients with abnormalities were excluded - in other words,  don't go get some hydroxychloroquine and start taking it without medical supervision based on this study.

OK, now let's look at a couple studies that actually attempted to answer the question above. 

 

https://pubmed.ncbi.nlm.nih.gov/32519281/

J Neuroimmune Pharmacol. 2020 Jun 9;1-9.
Does Adding of Hydroxychloroquine to the Standard Care Provide Any Benefit in Reducing the Mortality Among COVID-19 Patients?: A Systematic Review

Tejas K Patel  ¹ , Manish Barvaliya  ² , Bhavesh D Kevadiya  ³ , Parvati B Patel  ⁴ , Hira Lal Bhalla  ⁵

Abstract:

Hydroxychloroquine has been promoted for its use in treatment of COVID-19 patients based on in-vitro evidences. We searched the databases to include randomized and observational studies evaluating the effect of Hydroxychloroquine on mortality in COVID-19 patients. The outcome was summarized as odds ratios (OR) with a 95% confidence interval (CI).We used the inverse-variance method with a random effect model and assessed the heterogeneity using I² test. We used ROBINS-I tool to assess methodological quality of the included studies. We performed the meta-analysis using 'Review manager software version 5.3'. We identified 6 observationalstudies satisfying the selection criteria. In all studies, Hydroxychloroquine was given as add on to the standard care and effect was compared with the standard care alone. A pooled analysis observed 251 deaths in 1331 participants of the Hydroxychloroquine arm and 363 deaths in 1577 participants of the control arm. There was no difference in odds of mortality events amongst Hydroxychloroquine and supportive care arm [1.25 (95% CI: 0.65, 2.38); I² = 80%]. A similar trend was observed with moderate risk of bias studies [0.95 (95% CI: 0.44, 2.06); I² = 85%]. The odds of mortality were significantly higher in patients treated with Hydroxychloroquine + Azithromycin than supportive care alone [2.34 (95% CI: 1.63, 3.34); I² = 0%]. A pooled analysis of recently published studies suggests no additional benefit for reducing mortality in COVID-19 patients when Hydroxychloroquine is given as add-on to the standard care.

-----
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7255448/

Clin Drug Investig. 2020 May 28 : 1–11.

An Updated Systematic Review of the Therapeutic Role of Hydroxychloroquine in Coronavirus Disease-19 (COVID-19)

Saibal Das,¹Subhrojyoti Bhowmick,²Sayali Tiwari,³ and Sukanta Sen⁴

Results
A total of 663 articles were screened and 12 clinical studies (seven peer-reviewed and published studies and five non-peer-reviewed studies from pre-print servers) with a total sample size of 3543 patients were included. Some of the clinical studies demonstrated good virological and clinical outcomes with HCQ alone or in combination with azithromycin in COVID-19 patients, although the studies had major methodological limitations. Some of the other studies showed negative results with HCQ therapy along with the risk of adverse reactions.

Conclusion
The results of efficacy and safety of HCQ in COVID-19, as obtained from the clinical studies, are not satisfactory, although many of these studies had major methodological limitations. Stronger evidence from well-designed robust randomized clinical trials is required before conclusively determining the role of HCQ in the treatment of COVID-19. Clinical prudence is required in advocating HCQ as a therapeutic armamentarium in COVID-19.

 

One final note: it's important to consider that both of these groups publishing literature reviews are from Indian universities.  India is a democracy so no authoritarian government to screen and surpress results.  Their higher education is first- rate - Indian educated scientists are the backbone of a lot of US-based pharma R&D.  India has a lot of people getting sick from covid-19, and Indian physicians and scientists have every motivation to seek out and utilize inexpensive effective pharmaceutical interventions.

 

So, if their verdict is "overall, evidence of multiple studies does not support this treatment at this time", it's probably a good idea to LISTEN UP!

[HappyDays]

 

The hospitalization increase in Nevada is more concerning than the case increase in Florida.

 

Meanwhile in New York:

 

 

This is why the national data doesn't mean as much to me as individual state data. State data makes it easier to track which policies correlate with worse outcomes.

[Hapless Bills Fan]

On 7/4/2020 at 6:47 AM, Mr Info said:

This has been the only published article, thus far, correlating the spread of C19 and air conditioners. It would lend more credence if another peer-reviewed paper were published corroborating this.

There is this article questioning its conclusion. 
https://www.healthline.com/health-news/can-air-conditioning-spread-covid-19-probably-not

This article uses expert opinion to dismiss but no evidence. Would like to see more data to support this type of transmission than the one paper.

 

I think as far as it goes, that study is valid (it was referenced previously upthread, btw).  Two notes: 1) the AC unit in question is a window/wall mounted unit that blows air directly on customers vs. a ducted AC unit that directs air down from the ceiling or up from the floor.  Wall/window units typically also have no or poor filters.  Ducted systems can be (but aren't necessarily outside a hospital) equipped with a MERV-13 filter that can remove droplets and small particles. 2) In [the original article linked by @ExiledInIllinois, the authors did not consider aerosol transmission, only droplet transmission, which led to theorizing about the role of the AC in spreading droplets further than expected.  But the spread was not further than aerosols would be expected to transmit.

 

The fact that widespread covid-19 disease has been documented in meat packing plants vs. other manufacturing environments should probably also be taken into account.  Meat packing plants in particular feature powerful A/C blasting cold air along with humidity.  Yes, the crowded working conditions and long hours play a role as well, but there's probably a reason why meat packing plants and outbreaks seem to be associated (vs other plants with crowded long working conditions, some of which have remained open), and heavy air conditioning may well be a factor.

 

This is a pretty good discussion of that study and the issue of droplet vs aerosol  in general.  It has a number of linked references and features an interview with Johns Hopkins Medicine and Mech E professor Rajat Mittal:

https://www.snopes.com/news/2020/07/02/ac-covid-spread/

Key points:

-increasing evidence shows that aerosols containing SARS-Cov2 spread >6 ft and suggest "“aerosol transmission of SARS-CoV-2 may be a more important exposure transmission pathway than previously considered.”

-if that's the case, then the function of typical A/C systems in public places must be considered. 

-Many commercial air handling units have been configured to save energy by recycling indoor air, or are designed to move air from one room to another before returning it to the unit

 

If we want to reopen as many businesses as safely as possible, it seems logical that A/C systems should be considered as a potential source of recirculating aerosolized SARS-CoV2.  It would seem prudent to recommend that A/C systems be configured to exchange outdoor air to the highest extent possible, and to use the most efficient filter for which they are sized. 

And avoid environments that feature blasting cold air at tightly-packed people who stay in the same relative location for hours (like *cough* bars)
 

EDIT: digging a bit deeper into @Mr Info's link led me to this preprint:

https://www.medrxiv.org/content/10.1101/2020.04.16.20067728v1.full.pdf
"Evidence for probable aerosol transmission of SARS-CoV-2 in a poorly ventilated restaurant"

The link in @ExiledInIllinois post, was to a CDC "Emerging Infectious Diseases"  report from Guangzhou CDC scientists, originally published in late April and discussed upthread, including the seating diagram.   At the time, it was believed that droplet transmission of SARS-Cov2 was a primary means of disease spread and that aerosol transmission was not occurring.  This is relevant because droplets are larger and heavier and fall to the ground quickly.  So normal droplet spread could not explain the disease transmission pattern that was seen, and it was theorized that the A/C unit was responsible.

The above is from a different group, including engineering, architecture, and refrigeration faculty as well as epidemiology and Guangzhou CDC scientists.  They analyzed restaurant video from the relevant time period, but most important they used tracer gas measurements of the restaurant made during similar climactic conditions two months later and with either experimentalist or heated mannequins seated at the same tables.   Then they performed computational fluid dynamics using a standard modeling software package.

Bottom line: careful done study with good modeling.  they conclude aerosol transmission could be responsible for the outbreak, with overall poor ventilation in the restaurant and especially poor ventilation (0.75 L/s) in the area where the outbreak occurred being responsible.  So rather than pointing the finger at A/C, this study probably points the finger at ventilation dead zones, whether or not a space is air conditioned.

That said, in @Mr Info's healthline link, William P. Bahnfleth, PhD, PE, professor of engineering at the Pennsylvania State University and chair of the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) Epidemic Task Force, pointed out:  “A well-functioning air conditioning system in the restaurant that actively provided the appropriate amount of ventilation and had good filters for particulate matter would have greatly lowered the concentration of SARS-CoV-2 in the air, perhaps to the point that fewer diners would have contracted COVID-19.”

Bahnfleth says ASHRAE is advising its members to:

• consider bringing in more outside air or opening windows
• upgrade filters in air conditioning systems
• control airflow directions in a building to move from clean to less clean
• follow the recommendations of the CDC and others regarding physical distancing and hygiene

 

Which loops us back to the Snopes article and my point:

-the function of typical A/C systems in public places must be considered. 

-Many commercial air handling units have been configured to save energy by recycling indoor air, or are designed to move air from one room to another before returning it to the unit (this saves money) rather than to bring in appropriate outside ventilation

-Many commercial air handling units are NOT equipped with good filters that remove particulate matter - these are more expensive.
So I think these things should be considered.

[Hapless Bills Fan]

38 minutes ago, HappyDays said:

 

The hospitalization increase in Nevada is more concerning than the case increase in Florida.

 

Meanwhile in New York:

 

 

This is why the national data doesn't mean as much to me as individual state data. State data makes it easier to track which policies correlate with worse outcomes.

 

couple things here.

1) Whatever one thinks of Cuomo (and Wait, Wait, Don't tell me... here) the NY Forward dashboards are top notch.

# daily tests, # positive tests, % positive tests, # hospitalizations, # ICU beds, % hospital and ICU capacity - it's all right there.

I have NOT found another state that is being as transparent.

2) The Johns Hopkins University website has state-by-state case data in their "Critical Trends"  section
https://coronavirus.jhu.edu/data/new-cases-50-states/arizona
https://coronavirus.jhu.edu/data/new-cases-50-states/california

https://coronavirus.jhu.edu/data/new-cases-50-states/florida

https://coronavirus.jhu.edu/data/new-cases-50-states/nevada
https://coronavirus.jhu.edu/data/new-cases-50-states/texas
3) Worldometer has state by state data in tabular form, and with data sources

https://www.worldometers.info/coronavirus/country/us/

Clicking on most states will bring you to a page that gives # tests, # positives, total deaths, and active cases as well as graphical presentations of positive tests and deaths per day https://www.worldometers.info/coronavirus/usa/florida/

4) All state data is not necessarily up-to-date or high quality.  For example, here in MO, there's a self-proclaimed "data geek" on Facebook who collates and graphs data from the individual county health departments and compares them to the State DHSS.  His finding is that the state data is often lagging behind, sometimes by thousands of cases.  In addition, in some parts of the state, clinical laboratories are overwhelmed and running 5-10 days behind on testing.  Even more worrisome, data on the state dashboard is sometimes edited for unclear reasons.  So we have the Governor making pronouncements on what is going on with covid-19 in the state based upon dramatically out-of-date or incomplete data.

 

Example: as of today (7/4), for 6/30, the state Covid Dashboard reported 184 positive test results. 

Worldometer, as of today, reports 566 cases for 6/30

As of July 1, for 6/30, amateur data geek on Facebook reported 457 new cases.  It's kind of sad (and alarming) when a dude with a baby and a job and a random website, can do a better job of aggregating Public Health data for your state than its own DHHS - basically just by aggregating data from local health departments.
http://mophep.maps.arcgis.com/apps/MapSeries/index.html?appid=8e01a5d8d8bd4b4f85add006f9e14a9d
https://www.facebook.com/photo.php?fbid=10101930435114972&set=pcb.10101930189083022&type=3&theater

https://www.worldometers.info/coronavirus/usa/missouri/

 

Oh, and by the way - we don't know what's going on with active, current Florida hospitalizations.  They haven't been reporting it.  But they promise to start Real Soon Now (tm)

 

There's really no reason why every state as well as the CDC couldn't be publicizing data analogous to NYS - unless they are trying to avoid an accurate and up to date picture

 

 

 

 

 

 

 

[Hapless Bills Fan]

WHOOP WHOOOP WHOOP ALERT ALERT ALERT

 

Actual vaccine study data

Not a press release, preprint

 

Data on BioNTech/Pfizer's vaccine candidate

 

-45 participants injected, 3 dosage arms
-neutralizing antibodies tested for and observed at levels greater than convalescent serum:

"Neutralization titers were measurable after a single vaccination at Day 21 for all dose levels. At Day 28 (7 days after Dose 2), substantial SARS-CoV-2 neutralization titers were observed. The virus neutralizing GMTs after the 10 μg and 30 μg Dose 2 were, respectively, 1.8-fold and 2.8-fold the GMT of the convalescent serum panel. Assuming that neutralization titers induced by natural infection provide protection from COVID-19 disease, comparing vaccine-induced SARS-CoV-2 neutralization titers to those from sera of convalescent humans quantifies the magnitude of the vaccine-elicited response and the vaccine’s potential to provide protection. "

-pain at injection site most common side effect but there were plenty of side effects, mostly mild and resolving (this is actually a sign of an effective vaccine, provided it's within tolerable bounds)

-highest dose cohort only 1 injection due to side effects

On to Phase III!  "While our population of healthy adults 55 years of age and younger is appropriate for a Phase 1/2 study, it does not accurately reflect the population at highest risk for COVID-19. Adults 65 years of age and over have already been enrolled in this study and results will be reported as they become available. Later phases of this study will prioritize enrollment of more diverse populations, including those with chronic underlying health conditions and from racial/ethnic groups adversely affected by COVID-19"

Phase 1/2 Study to Describe the Safety and Immunogenicity of a COVID-19 RNA Vaccine Candidate (BNT162b1) in Adults 18 to 55 Years of Age: Interim Report

Mark J. Mulligan, Kirsten E. Lyke, Nicholas Kitchin, View ORCID ProfileJudith Absalon, Alejandra Gurtman, Stephen P. Lockhart, View ORCID ProfileKathleen Neuzil, View ORCID ProfileVanessa Raabe, Ruth Bailey, Kena A. Swanson, Ping Li, Kenneth Koury, Warren Kalina, David Cooper, Camila Fonter-Garfias, Pei-Yong Shi, Ozlem Tuereci, Kristin R. Tompkins, Edward E. Walsh, View ORCID ProfileRobert Frenck, View ORCID ProfileAnn R. Falsey, View ORCID ProfilePhilip R. Dormitzer, William C. Gruber, Ugur Sahin, Kathrin U. Jansen

 

We report the available safety, tolerability, and immunogenicity data from an ongoing placebo-controlled, observer-blinded dose escalation study among healthy adults, 18-55 years of age, randomized to receive 2 doses, separated by 21 days, of 10 μg, 30 μg, or 100 μg of BNT162b1, a lipid nanoparticle-formulated, nucleoside-modified, mRNA vaccine that encodes trimerized SARS-CoV-2 spike glycoprotein RBD. Local reactions and systemic events were dose-dependent, generally mild to moderate, and transient. RBD-binding IgG concentrations and SARS-CoV-2 neutralizing titers in sera increased with dose level and after a second dose. Geometric mean neutralizing titers reached 1.8- to 2.8-fold that of a panel of COVID-19 convalescent human sera. These results support further evaluation of this mRNA vaccine candidate.

......

These clinical findings for the BNT162b1 RNA-based vaccine candidate are encouraging and strongly support accelerated clinical development and at-risk manufacturing to maximize the opportunity for the rapid production of a SARS-CoV-2 vaccine to prevent COVID-19 disease.

-------------

Pfizer has a track record of developing and getting vaccines approved, including on a short time line upon request of the FDA.  Their vaccine development and manufacturing group is battle-tested and know what it takes - though this is gonna be big.
 

[Hapless Bills Fan]

Hydroxychloroquine study from Henry Ford Hospital in Detroit finds benefit to hydroxychloroquine (but not hydroxychloroquine + azythromycin) treatment

Study: https://www.ijidonline.com/article/S1201-9712(20)30534-8/fulltext

They call it a "retrospective observational study", which seems like a strange use of "observational" but let it pass - point is, it's not a double-blind clinical trial

 

Treatment arms were hydroxychloroquine, hydroxychloroquine + azithromycin, azithromycin alone, nothing

End point was mortality (overall 18%)

Overall crude mortality rates were

13.5% in the hydroxychloroquine alone group (162/1202)
20.1% among those receiving hydroxychloroquine + azithromycin (157/783)

22.4% among the azithromycin alone group (33/147)

26.4% for neither drug (108/409)

 

Median age 64 years which means...half the patients were younger

 

First pass comments:

-It's never a Good Thing, statistically, to have 3x as many patients in your treatment as in your control group

-The mean age of the patients given neither drug is 5 years older than the mean age of the hydroxychloroquine patients, 68 vs 63.  The median age was 71 vs 53 (!!!!) That seems potentially significant in a disease where outcomes worsen sharply as age increases; in a non-double-blind study, does it signal some bias in treatment decisions?

-They tried to overcome these discrepencies by matching 190 patients +/- hydroxychloroquine and still saw a 50% reduction in death, so that's good (but of course a small number)

 

They do a nice job summarizing the evidence for and against and attribute their different result to early administration (usually within 24 hrs of admission):
 

Recent observational retrospective studies and randomized trials of hydroxychloroquine have reported variable results. (Gautret et al., 2020a, Gao et al., 2020,  Gautret et al., 2020b, Jun et al., 2020, Tang et al., 2020, Chen et al., 2020, Yu et al., 2020, Geleris et al., 2020, Rosenberg et al., 2020, Magagnoli et al., 2020, Million et al., 2020) In a randomized controlled study of 62 patients from China with COVID-19, hydroxychloroquine was associated with a shortened duration of fever and time to cough and pneumonia resolution (Chen et al., 2020). In contrast, a study of 1376 consecutive hospitalized COVID-19 patients in New York that used respiratory failure as the primary endpoint found no significant reduction in the likelihood of death or intubation among those receiving hydroxychloroquine compared to those who did not. (Geleris et al., 2020) In a separate multicenter cohort study of 1438 patients from 25 hospitals in New York, no reduction in hospitalized patient mortality was observed with hydroxychloroquine treatment (Rosenberg et al., 2020). Among a number of limitations, this study included patients who were initiated on hydroxychloroquine therapy at any time during their hospitalization****. In contrast, in our patient population, 82% received hydroxychloroquine within the first 24 hours of admission, and 91% within 48 hours of admission. [**** in fact the NY study patients received hydroxychloroquine on average within 24 hrs]

 

In the same journal, other physicians had some valid points about possibly important factors the study failed to sort:

https://www.ijidonline.com/article/S1201-9712(20)30530-0/fulltext#

"potentially important markers of disease severity (e.g. ferritin, C-reactive protein (Zeng et al., 2020), troponins (Vrsalovic and Vrsalovic Presecki, 2020), and D-dimer (Zhang et al., 2020), and co-administration of potentially beneficial therapies (e.g. anticoagulants (Paranjpe et al., 2020) that were not included in the analysis." and "concomitant steroid use in patients receiving hydroxychloroquine was more than double the non-treated group. This is relevant considering the recent RECOVERY trial that showed a mortality benefit with dexamethasone (Horby et al., 2020)"

 

They also point out that "confounding by severity or indication (Kyriacou and Lewis, 2016) is likely. While there was a hospital treatment protocol in place, unmeasured clinical factors likely influenced the decision not to treat 16.1% of patients, in a center where 78% received treatment. These factors are often difficult to capture in an observational study. Were the decision to withhold treatment related to poor prognosis (e.g. palliative intent), it stands to reason that patients receiving neither hydroxychloroquine nor azithromycin would have the highest mortality."

 

And that to me is the biggest question.  The data are the data.  Given the data, they clearly saw an effect.  But it bothers me that the non-treatment group is so much smaller (1/3 the size) and so much older (mean age 5 years, median age 18 years).  I think it may be a valid question, what was the basis to not treat, the non-treatment group?  The fact that twice as many patients in the treatment group received dexamethasone, which has been shown to be of benefit, does point to that possibility as well - the (older) non-treatment cohort may have been earmarked for palliative care and received less treatment overall.

 

One really wants a controlled study.   AND HEY!  WE HAVE ONE!  UK "Recovery" trial, 11,000 patients:

https://www.recoverytrial.net/news/statement-from-the-chief-investigators-of-the-randomised-evaluation-of-covid-19-therapy-recovery-trial-on-hydroxychloroquine-5-june-2020-no-clinical-benefit-from-use-of-hydroxychloroquine-in-hospitalised-patients-with-covid-19

"‘A total of 1542 patients were randomised to hydroxychloroquine and compared with 3132 patients randomised to usual care alone. There was no significant difference in the primary endpoint of 28-day mortality (25.7% hydroxychloroquine vs. 23.5% usual care; hazard ratio 1.11 [95% confidence interval 0.98-1.26]; p=0.10). There was also no evidence of beneficial effects on hospital stay duration or other outcomes. "

 

 

 

 

 

[Hapless Bills Fan]

Atlantic article.  Matches what I know about some places in Missouri, where LabCorp and Quest are now taking 3-10 days to return results in the face of flare-ups

https://www.theatlantic.com/science/archive/2020/06/us-coronavirus-testing-could-fail-again/613675/

 

There is an answer to this.  It's called "pooled testing".  Nebraska has been doing this for months, with kind of tenuous approval from the FDA.

The FDA is ambiguous and lukewarm in its guidance on this: they told Nebraska "we will not object to a pool of 5 samples" or something like that, back in March.

Israel, I believe, has also been doing this in a more complex form

 

Batch testing is not a novel idea: the US Army pioneered it to screen millions of soldiers for VD.  It's also been used to extend testing capacity for malaria etc in poor countries.

What is batch testing?  To save on test reagents and increase throughput on testing equipment, several samples are combined and a "pool" is tested (to compensate for dilution and achieve the same sensitivity, the number of PCR cycles may need to be adjusted upwards to account for the lower concentration). 

 

In its simplest form (as Nebraska has been doing) you combine 5 samples and test the pool. 

-If they're negative, All Good.  Done.

-If you get a positive sample, then you individually test all the samples in the pool.  So if you have a suspected outbreak where 1/3 or 1/2 the samples may be positive, it may not be a good idea.  But in an area where the % positive tests is running 2% or less, it's a huge savings of time and equipment.  Let's say you have 100 samples.  You combine them into 20 pools of 5 samples, a 5x savings in throughput and reagents.  1 or two of those pools may be positive, so you retest  (say) 10 samples.  It's still a 3.3x savings in reagents and equipment use.  Overall, you can easily achieve an increase of 4x (again, assuming the % positives are normally low, as in a congregate living facility and its workers without an active outbreak, or a college - OR A SPORTS TEAM, HINT HINT)
Germany has done some work to specify and validate the technique

https://eurekalert.org/pub_releases/2020-03/guf-pto033020.php

In its more complex form, those 100 samples would be combined into various pools using a mathematical algorithm so that each sample appears in more than one pool.  The positive pools will be found in a specific pattern that can reveal which samples are positive.  There's a group in Israel that has published on this.  They claim an 8x increase in throughput (384 samples into 48 pools).  The drawback is it requires a robotic liquid handler to pipette all the pools, and just the pipetting does take time - about 5 hrs.  The benefit is no need to retest, as long as the incidence of positive samples remains low enough for the algorithm to decode.

 

Opinion:

This is an instance where good national leadership would be invaluable. As more and more industries  (such as universities, and FOOTBALL HINT HINT) want to implement repeated rapid testing to identify asymptomatic and presymptomatic infections, they're all drawing from the same pool of available reagants and equipment.  WE CAN DO THIS, IF we have leadership that says "not only is it OK to do this, but WE WANT YOU TO DO THIS". 

 

I want football, but not if it means Aunt Gerda from Glad Days Care Home and her nurses aides, or people with known contacts with a covid-19 patient, can't get a test.

 

Instead we have lukewarm pussyfooting (see FDA link above).  If the technique needs to be validated, CDC and FDA, get some hands at the lab bench and Get 'Er Done.

This would NOT be a bad time to call your local Department of Health and ask what is their position and guidance on pooled testing for covid-19 disease?

[SlimShady'sSpaceForce]

Coronavirus updates: 8th state surpasses 100K cases. https://www.yahoo.com/gma/cor...95--abc-news-topstories.html

[Hapless Bills Fan]

EDIT: update with links to a recent article in Nature that does a good job breaking this down and explaining the flaws in some of the estimates. 

See end for some excerpts

I'll take a whack at a question that's challenging to answer right now, that came up in the Shoutbox,  I assume on the heels of our President's pronouncement that 99% of Covid-19 cases aren't "serious" and the lack of walk-back from our CDC Director Stephen Hahn.  The question is: what is the true death rate, or more formally "infection fatality rate" from covid-19?  @SDS, this is for you.  I welcome discussion, but I do ask discussion to move to the discussion thread.
 

Infection fatality rate requires that we know two things with fair accuracy:

1) the numerator - how many people have actually died from covid-19?

2) the denominator - how many people have actually been infected covid-19 disease?

 

People have written all kinds of articles about this.  To make a long story short, I think many of them wreck of poor science.  I'll try to get at it independently, showing my work and giving references. 

 

I'd also like to respectfully suggest that it's the wrong question for most people.  What I think most people ought to want to know is not "how likely am I to die if I get covid-19?" but "how likely am I to become seriously ill - to require hospitalization, and possibly suffer complications including brain damage, lung damage, blood clots?  While it's quite true most of the people who die from covid-19 are elderly, all the physicians I know treating covid-19 patients in hospital tell me a lot of their very sick patients are young and overall, healthy.  The CDC's data for June say 30-40% of those hospitalized are age 18-49 and 27-29% are age 50-64 (sorry, those are the age ranges they track).  What percentage of total cases in those age ranges do those represent?  That's I think the question most of us would really like to have answered.

 

The numbers that are published on sites like Johns Hopkins, Worldometer, etc (and by the way, many published for influenza) are "Case Fatality Rates" (CFR) - the number of people who have died from covid-19/ the number of diagnosed people who have tested positive for covid-19.  This is the number that's knowable.

Ideally, testing would be such that almost all infected people would be identified, and almost all the covid-19 fatalites would be identified and the CFR and IFR would converge.  One way to estimate our true infection fatality rate would be to look at a democracy (so we aren't worried about data suppression), which had excellent testing capacity from the start, which never overloaded its medical system so everyone who needed care, got high quality care, and which has controlled its epidemic within a time period where we have data on deaths.  Two examples would be S. Korea, and Iceland.  South Korea reports 284 deaths/13,137 cases, for a case fatality rate of 2%.  How about Iceland?  In some areas, they literally tested everyone.  10 deaths/1866 cases, for a case fatality rate of 0.5%.  Both Iceland and S. Korea may represent populations that may be less susceptible or more susceptible.  Those two countries probably give us bounds (0.5-2%) on a reasonably probable true infection fatality rate. (data from Worldometer, link above).

Let's cross check with a different approach.

Most experts believe that the number of covid-19 deaths are being UNDER counted.  They look at "excess seasonal mortality".  You take the average number of people who die in different months of the year, and compare this year's deaths.  (In the US overall, this data is incomplete because takes weeks to process it.)

Here's a good article about this in The Economist from mid-April.  Here's a key figure:

The dashed line is the expected deaths; anything above the line is excess mortality, the orange stuff is mortality with a positive covid-19 test.  So we see that in most countries, there's a substantial excess mortality (brown area above dashed line) that is not accounted for by known covid-19 cases.

 

We can get at a good number for our Infection Fatality Rate numerator by looking at the excess mortality numbers.  This is likely an overestimate as some people did not obtain treatment and died from other medical problems.  But it's probably the best data we have right now for a numerator in our "infection fatality rate".  From same source:

 

Now we need a denominator, total number of people infected.  One way to approach this is to look at seroprevalence - the number of people who have anti-covid-19 antibodies.  A number of studies have been done that either were deliberately un-representative (such as Boston looking at people on the streets of Chelsea) or that were probably un-representative (several sampling studies in various US cities).  Here's a link to a Lancet editorial that has a good list of seroprevalence studies.  The Spanish study was particularly well done.  It was a randomly chosen sample, involved 60,000 people, and used two different antibody tests.  They found that countrywide, a lower bound of 3.7% (positive by both tests) and an upper bound of 6.2% (positive by at least one test) were infected.  Spain's population is 46,755,000 people.  The lower bound would mean there were 1,729,935 cases and the upper bound would mean there were 2,898,810 cases (the official count is 297,625 cases)  Sanity cross-check: epidemiologists (prior to the serology studies) have been estimating that the official case count is 5-10x higher than actual positive tests.  Those seroprevalence numbers fall within that bound.

43,668 excess deaths/2,898,810 deaths = 1.5% infection fatality rate.  43,668 excess deaths/1,729,935 cases = 2.5% infection fatality rate.  If we guess that maybe 20% of the excess deaths are for other medial causes (for which treatment was unsought or unavailable), that would be 1.2-2%.  I consider that a "best estimate" based on the highest quality data I can find for the numerator and the denominator as of today.  It also cross-checks reasonably with data from two countries, Iceland and S. Korea, where we believe the IFR and CFR may converge and the CFR is 0.5%-2%.

 

I think that's as reasonable a number as we're going to get, based on data we currently have.  Any estimate which adjusts the case numbers by seroprevalence, but that doesn't adjust the covid-19 fatality numbers by excess mortality, should be given the squinch-eye and looked at Veeeeerrry Suspiciously.

 

Now going back What I think most people ought to want to know is not "how likely am I to die if I get covid-19?" but "how likely am I to become seriously ill - to require hospitalization, maybe suffer long-term complications including brain damage, lung damage, damage from blood clots?  (Let me tell you, I spent a single night in a neuro unit with a subdural bleed and two years later I can still tell effects.  They're minor, but there.  I am NOT volunteering for a disease with no pharmaceutical treatment that could require me to need prolonged hospitalization and cause micro-clots and brain damage (see other article on how covid-19 kills), not if I can help it.)  So how likely is that?  It's SWAG time.

 

Initial data from the WHO-China joint report were that 20% of covid-19 cases were serious and 5% were critical illness requiring hospitalization.   That's certainly an overestimate, based on initial testing limited to symptomatic patients and without awareness of the number of asymptomatic/mild cases..  So how can we correct? (I don't think it's helpful to say "just divide by 5 or 10" because we have no idea what China's excess mortality may have been...)

 

How about this: We know that many of the serious, hospitalized cases in the US recover.  Several studies of different prospective covid-19 treatments have given median death rates in hospitalized patients of about 20%.  If the true case fatality rate is 1.2-2.0% and we assume most die in hospital, that would mean that the likely rate of a serious case (requiring hospital treatment) would be 6-10% of the covid-19 total cases in the population [That's (1.2-2.0)/0.2, and it's total cases, not positive tests]

 

Hopefully, as treatment protocols improve and (wishing for this!) we get better at protecting nursing home facilities, the case fatality rate will drop and be closer to 0.5% and the incidence of serious disease requiring hospitalization will also shift, as right now >65% demographic represented 28-38% of the hospitalizations.  But if we go with the CDC June data 30-40% of those hospitalized are age 18-49 and 27-29% are age 50-64, multiply your appropriate age range by 6-10% and you should get your chance of becoming seriously ill, should you contract covid-19.

Either way I slice it, I come out with the number of serious cases of covid-19 are >1%, unless you're under (or maybe close to) age 18.

-------------------------------------------------

EDIT: I found a good article in Nature that does a reasonable job explaining various IFR estimates.
"...early seroprevalence studies did not properly account for the lack of sensitivity and specificity in the antibody test kits that were used, or for discrepancies between the sampled and underlying populations, says Verity.  These issues could have inflated estimates of the total number of infected people and so made the virus seem less deadly, he says.

Equally, if COVID-19 deaths go undetected — a problem in many countries that aren’t testing all deceased people for the virus — that, too, can bias the fatality rate, says Gideon Meyerowitz-Katz, an epidemiologist and PhD candidate at the University of Wollongong, Australia."

Overall, this article points out that current estimates with more carefully done seroprevalence studies are converging at 0.5-1% (where good hospital care remains available, with variable approaches to excess mortality). They point out that population IFR may be misleading, as there is a strong age variance.  If you're trying to answer the question "how likely am I to die from this disease?" age matters....a lot. 

They also point out that the general health of the population matters: how many people have underlying conditions?

 

Here is an article from a Swiss group that estimated IFR (in Switzerland) by age.  Switzerland (being Switzerland) did not have a significant excess mortality not accounted for by diagnosis of covid-19....overall the population IFR was 0.64% broken down as follows:

   age <50: IFR <0.02% (taking the higher bound - but increases with age from negligable <20 to this value at some point)
   50-64:  0.14%

   >65: 5.6%

Switzerland has compulsory private health insurance at an affordable cost.  Switzerland also has lower incidence of many identified risk factors for covid-19: they make the list of "top 10 countries with thinnest/fittest population" (mean BMI: 25.3) "top 10 countries with lowest rate of death from heart disease", estimates of hypertension in adult Swiss ~25% vs 50% in USA, estimates of diabetes 5% vs 10% in USA (and to make matters worse, they pick up their dog poop and stop for pedestrians at crosswalks.  In fact they honk at you and get cross if you don't exercise your right of way.  Those Swiss!).  The article also notes that even in urban centers with the highest number of covid-19 infections, hospital capacity remained adequate to provide a high standard of care to all patients.  Thus the infection fatality rate in Switzerland may represent a "best case" for prompt diagnosis and treatment of a fundamentally healthy population where neglected or undiagnosed co-morbid health conditions are relatively rare.

If we predict IFR may be 3x higher in US with our spotty health care and much higher comorbid conditions (closer to the 1-2% I believe seen in Spain), that would translate to

   age <50: IFR <0.06% (again, increases from negligable <20 to this value at some point)
   50-64:  0.42%

   >65: 16.8%

 

Again: remember these are figures for MORTALITY, but a significantly larger number of people at each age become ill and require hospitalization; the estimate reached above is that 6-10% of all those infected may require hospitalization.  Per CDC June data 30-40% of those hospitalized are age 18-49 and 27-29% are age 50-64.  MORBIDITY (serious illness) may be the more appropriate metric for Joe Everyman to assess risk.

 

 

[Hapless Bills Fan]

OK, I thought I posted this here but I can't find it.  If someone else sees this posted,  let me know and I'll merge or delete.  Thanks.

 

https://www.washingtonpost.com/health/2020/07/01/coronavirus-autopsies-findings/

 

Emerging data from autopsies of covid-19 patients that sheds light on what's actually going on and may improve treatment

Key findings and implications:
-Finding: not finding signs of classic myocarditis, which was believed to be a cause of sudden death in 20-30% of hospitalized patients.  Instead finding megakaryocytes and blood clots (also in lungs)

-Implication: investigate treatment with anti-platelet medication in addition to blood thinners (clinical trials)

-Finding: abnormal clotting in heart, kidney and liver, as well as the lungs,  may be responsible for multiple organ failure observed in seriously ill covid-19 patients

-Implication: initiate early treatment with anticoagulants in covid-19 patients

-Finding: not finding virus or inflammation in the brain, as was expected given prevalence of neurological symptoms such as extreme fatigue, slow awakening when weaned from ventilator, need for cognitive and physical rehabilitation even in patients not that seriously ill.  Instead finding swaths of dead cells, as from hypoxia and/or blood clots, whether patient died suddenly or spent weeks in ICU

-Implication: early monitoring of oxygen levels/clots and oxygen therapy/treatment of clotting very important to avoid lasting impact on brain

 

It's not just people who die.  Another article about neurological deficits observed in recovering covid patients

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7188454/

 

 

 

 

 

 

[SlimShady'sSpaceForce]

Gov. Andrew Cuomo on Tuesday added three more states to New York's travel advisory.

Those traveling to New York from Delaware, Kansas and Oklahoma now must quarantine for two weeks.

 

https://www.yahoo.com/gma/coronavirus-updates-us-reports-45-000-cases-death-085800230--abc-news-topstories.html

 

[Edit:  raises the appropriate question, how can he enforce this?  Because otherwise, it is all for show]

 

 

 

 

[Hapless Bills Fan]

Aerosol transmission

https://www.nytimes.com/2020/07/04/health/239-experts-with-one-big-claim-the-coronavirus-is-airborne.html

 

Scientists are frustrated by WHO's failure to recognize that covid-19 transmission is airborne.

Started back in April:

Dr. Morawska and others pointed to several incidents that indicate airborne transmission of the virus, particularly in poorly ventilated and crowded indoor spaces. They said the W.H.O. was making an artificial distinction between tiny aerosols and larger droplets, even though infected people produce both.

“We’ve known since 1946 that coughing and talking generate aerosols,” said Linsey Marr, an expert in airborne transmission of viruses at Virginia Tech.
(....)
"But the discussion was dominated by a few experts who are staunch supporters of handwashing and felt it must be emphasized over aerosols, according to some participants, and the committee’s advice remained unchanged."
(...)
"Dr. Marr and others said the coronavirus seemed to be most infectious when people were in prolonged contact at close range, especially indoors, and even more so in superspreader events — exactly what scientists would expect from aerosol transmission.
(...)
“There is no incontrovertible proof that SARS-CoV-2 travels or is transmitted significantly by aerosols, but there is absolutely no evidence that it’s not,” said Dr. Trish Greenhalgh, a primary care doctor at the University of Oxford in Britain."

“So at the moment we have to make a decision in the face of uncertainty, and my goodness, it’s going to be a disastrous decision if we get it wrong,” she said. “So why not just mask up for a few weeks, just in case?”
(...)
The W.H.O. tends to describe “an absence of evidence as evidence of absence,” Dr. Aldis added. In April, for example, the W.H.O. said, “There is currently no evidence that people who have recovered from Covid-19 and have antibodies are protected from a second infection.”

The statement was intended to indicate uncertainty, but the phrasing stoked unease among the public and earned rebukes from several experts and journalists. The W.H.O. later walked back its comments.

Scientific American article from back in May:
https://www.scientificamerican.com/article/how-coronavirus-spreads-through-the-air-what-we-know-so-far1/?utm_medium=social&utm_content=organic&utm_source=twitter&utm_campaign=SciAm_&sf235754426=1

 

[Hapless Bills Fan]

School reopening: many places have done it, data on outcomes are scarce:

https://www.sciencemag.org/news/2020/07/school-openings-across-globe-suggest-ways-keep-coronavirus-bay-despite-outbreaks

 

It was time, a growing chorus said, to bring children back to school.

By early June, more than 20 countries had done just that. (Some others, including Taiwan, Nicaragua, and Sweden, never closed their schools.) It was a vast, uncontrolled experiment.

Some schools imposed strict limits on contact between children, while others let them play freely. Some required masks, while others made them optional. Some closed temporarily if just one student was diagnosed with COVID-19; others stayed open even when multiple children or staff were affected, sending only ill people and direct contacts into quarantine.

Data about the outcomes are scarce. “I just find it so frustrating,” says Kathryn Edwards, a pediatric infectious disease specialist at the Vanderbilt University School of Medicine who is advising the Nashville school system, which serves more than 86,000 students, on how to reopen. Her research assistant spent 30 hours hunting for data—for example on whether younger students are less adept at spreading the virus than older ones, and whether outbreaks followed reopenings—and found little that addressed the risk of contagion in schools.

 

That seems to be the bottom line. 

 

We know that symptomatic covid-19 disease and serious complications are very very rare in children - until they started contact tracing, China thought children weren't getting sick at all. 

 

We know that school closures and lockdowns have isolated children and that they are more vulnerable to undetected abuse and lack the food that schools provided.

 

We know that many places have reopened schools and several never closed them. 

 

But data on specific outcomes indeed seems very scarce to find.

 

This is an example of the sort of thing that has me face-palming and banging my head:

https://www.sciencemag.org/news/2020/05/how-sweden-wasted-rare-opportunity-study-coronavirus-schools

 

 

The one country that could have definitively answered that question has apparently failed to collect any data. Bucking a global trend, Sweden has kept day care centers and schools through ninth grade open since COVID-19 emerged, without any major adjustments to class size, lunch policies, or recess rules. That made the country a perfect natural experiment about schools’ role in viral spread that many others could have learned from as they reopen schools or ponder when to do so. Yet Swedish officials have not tracked infections among school children—even when large outbreaks led to the closure of individual schools or staff members died of the disease.

 

“It’s really frustrating that we haven’t been able to answer some relatively basic questions on transmission and the role of different interventions,” says Carina King, an infectious disease epidemiologist at the Karolinska Institute (KI), Sweden’s flagship medical research center. King says she and several colleagues have developed a protocol to study school outbreaks, “but the lack of funding, time, and previous experience of conducting this sort of research in Sweden has hampered our progress.”

 

 

[SlimShady'sSpaceForce]

Areas of New York have recorded a nearly 70 per cent rate of immunity to Covid-19, in what scientists have described as “stunning” findings that suggest they could be protected from any second wave.

https://www.yahoo.com/news/scientists-hail-stunning-results-show-180918348.html

 

[Edit: I would prefer to re-direct from the Yahoo article, to the less-sensationalistic and more factual NY Times article to which it refers:

https://www.nytimes.com/2020/07/09/nyregion/nyc-coronavirus-antibodies.html

-The antibody tests were performed at a storefront clinic, "CityMD", between late April and late June

-They probably do NOT reflect a random sample of the population in those neighborhoods, since people who believe they had symptoms/were exposed are most likely to seek antibody testing

-Huge variation seen neighborhood to neighborhood from 68% to 56% to 17% in wealthier Cobble Hill, Brooklyn

 

Key quotes:
"Dr. Ted Long, the executive director of the city’s contact-tracing program, said that while much remained unknown about the strength and duration of the protection that antibodies offer, he was hopeful that hard-hit communities like Corona would have some degree of protection because of their high rate of positive tests. “We hope that that will confer greater herd immunity,” he said."

 

That's not quite "scientists hail STUNNING results".  It's very hopeful for those people in poor neighborhoods who had to work in order to eat, maybe they'll be spared in a 2nd wave.  But even there....because the results were from people who sought antibody testing, they may not reflect the overall population even in those neighborhoods:

 

"“For sure, the persons who are seeking antibody testing probably have a higher likelihood of being positive than the general population,” said Professor Nash. “If you went out in Corona (the Queens neighborhood) and tested a representative sample, it wouldn’t be 68 percent.”

My guess would be more like Chelsea, MA, around 30%.  I could be wrong of course.

 

Overall the antibody positive rate was 26%, which agrees with the NYS Wadsworth survey.  -Hap]

[shoshin]

 

Not rocket science but there are still unbelievers.

[Hapless Bills Fan]

A nice piece explaining immune response from one of my favorite bloggers, Pharma R&D chemist Derek Lowe

TL;DR: it’s important to remember that neutralizing antibodies against COVID-19 are only one measure of immune response.  Cellular immunity is important in fighting viral infections, and much harder to measure.