Skeptic 🇺🇦🇵🇸 @antifascistcovid19denial@qoto.org

Waiting for the truth: is reluctance in accepting an early origin hypothesis for SARS-CoV-2 delaying our understanding of viral emergence?

"Although the current canonically accepted timeline hypothesises viral emergence in Wuhan, China, in November or December 2019, a growing body of diverse studies provides evidence that the virus may have been spreading worldwide weeks, or even months, prior to that time.

However, the hypothesis of earlier SARS-CoV-2 circulation is often dismissed with prejudicial scepticism and experimental studies pointing to early origins are frequently and speculatively attributed to false-positive tests...

...Several studies performed independently by different groups retrospectively demonstrated the presence of antibodies and viral RNA in clinical samples and showed SARS-CoV-2 community circulation by detecting viral RNA in wastewater at times inconsistent with November 2019 emergence...

...Each study providing evidence for early circulation of SARS-CoV 2 might look inconclusive, but combining all data together reveals an emerging pattern...

...Despite the technical limitations of available early origin studies, even a remote possibility that positive tests indicate an early SARS-CoV-2 circulation should be considered sufficient to warrant the scaling up of research to more samples from more regions and through a wider timespan.

Time is running out: valuable samples that may contain the key to the understanding of SARS CoV-2 origin might already have been destroyed as their regulatory storage time requirements lapse."

Canuti M, Bianchi S, Kolbl O, et alWaiting for the truth: is reluctance in accepting an early origin hypothesis for SARS-CoV-2 delaying our understanding of viral emergence?BMJ Global Health 2022;7:e008386.

https://gh.bmj.com/content/7/3/e008386

TABLE 1 - Causes of False Positive SARS-CoV-2 RT-PCR Results

 Contamination during
  Sampling (eg, an infected worker or surfaces; aerosolization of virus during collection)
  Extraction (eg, aerosolization in containment hood)
  PCR amplification
  Production of Lab Reagents (eg, manufacturers of the positive control may have contaminated other reagents produced in the same facility; contamination of other consumables)
 Contamination of the equipment by high viral titer specimens (eg, sample carryover)
 Cross-reaction with other viruses (eg, other coronaviruses)
 Sample mix-ups
 Software problems
 Data entry or transmission errors
 Miscommunicating results
 Variations in parameters around the LOD and definition of an indeterminate result
 Assuming that an indeterminate result is a positive
 Non-specific reactions

Braunstein, Glenn D. MD; Schwartz, Lori MD, FACOEM; Hymel, Pamela MD, MPH, FACOEM; Fielding, Jonathan MD, MPH, MBA. False Positive Results With SARS-CoV-2 RT-PCR Tests and How to Evaluate a RT-PCR-Positive Test for the Possibility of a False Positive Result. Journal of Occupational and Environmental Medicine 63(3):p e159-e162, March 2021. | DOI: 10.1097/JOM.0000000000002138

https://journals.lww.com/joem/fulltext/2021/03000/false_positive_results_with_sars_cov_2_rt_pcr.23.aspx

"The most widely utilized Nucleic Acid Amplification Test (NAAT) to detect SARS-CoV-2 RNA is the reverse transcriptase-polymerase chain reaction (RT-PCR) test, manufactured by many companies targeting one or more genomic regions of the virus...

...The FDA has published recommendations concerning the data and information that test manufacturers should supply in their application for Emergency Use Authorization (EUA)...

...Acceptable clinical performance is defined as a minimum 95% positive and negative percent agreement (PPA and NPA).

For a screening indication, the PPA recommendation remains at more than or equal to 95% and the NPA is raised to more than or equal to 98% to reduce false positive test results.

In actual use, the clinical sensitivity and specificity of many of these tests is lower in part because of issues surrounding sample collection, handling, and analysis."

Braunstein, Glenn D. MD; Schwartz, Lori MD, FACOEM; Hymel, Pamela MD, MPH, FACOEM; Fielding, Jonathan MD, MPH, MBA. False Positive Results With SARS-CoV-2 RT-PCR Tests and How to Evaluate a RT-PCR-Positive Test for the Possibility of a False Positive Result. Journal of Occupational and Environmental Medicine 63(3):p e159-e162, March 2021. | DOI: 10.1097/JOM.0000000000002138

https://journals.lww.com/joem/fulltext/2021/03000/false_positive_results_with_sars_cov_2_rt_pcr.23.aspx

Evidence for Limited Early Spread of COVID-19 Within the United States, January–February 2020

"retrospective SARS-CoV-2 testing of approximately 11,000 respiratory specimens from several U.S. locations beginning January 1 identified no positive results before February 20...

...The findings in this report are subject to at least three limitations. First, the data presented here are retrospective."

In this thread I will show that the lack of false positives makes these findings highly implausible, and I will show that other studies have had contradictory results.

Jorden MA, Rudman SL, et al. Evidence for Limited Early Spread of COVID-19 Within the United States, January–February 2020. MMWR Morb Mortal Wkly Rep 2020;69:680–684. DOI: http://dx.doi.org/10.15585/mmwr.mm6922e1

#COVID #COVID19 #epidemiology #bioinformatics

@MrHedmad

Have you ever used a piece of software called Obsidian?

It uses a branch of mathematics called graph theory to organize your notes.

It doesn't require any coding and is pretty intuitive to use.

I found it super useful when I doing a research project that involved tracking research citations to visualize the connections on my research topic.

To put this all together:

All cause mortality in Wuhan was well above normal by the time the lockdown was implemented.

Given that deaths lag infections, and given that only a small fraction of infections lead to death, the outbreak would have already been totally out of control by then.

The lockdown was implemented on the peak travel day of the worlds largest annual migration, and there was no travel slow down leading up to it.

An estimated 7 million people left the city in the weeks leading up to the lockdown, including 300,000 people on the eve of the lockdown.

Given this data, it is simply implausible that the lockdown meaningfully prevented overall mortality from increasing in Hubei province outside Wuhan or the rest of China.

"At least 300,000 people escaped on the eve of the lockdown"

https://web.archive.org/web/20240518170223/https://news.ltn.com.tw/news/world/breakingnews/3048974

The 7 million travelers estimated by the New York Times is comparable to the 5 million estimated by the mayor of Wuhan.

https://www.pbs.org/newshour/health/where-did-they-go-millions-left-city-before-quarantine

The following visualizations were produced from cell phone data and published in the New York Times.

All of these travelers were from Wuhan.

"About 7 million people left in January, before travel was restricted."

Worth noting: more travelers went to Rome than Milan, and more travelers went to Los Angeles and San Francisco than to New York City.

https://www.nytimes.com/interactive/2020/03/22/world/coronavirus-spread.html

Data from flightradar24 shows normal flight patterns until the lockdown.

Wuhan Tianhe International Airport can be seen in orange at the bottom.

https://www.flightradar24.com/blog/air-traffic-at-chinas-busiest-airports-down-80-since-the-beginning-of-the-year/

The Wuhan lockdown occurred on January 23rd 2020, which happened to be the peak travel day for "the worlds largest annual migration" - the Lunar New Year.

Data from Baidu shows that the peak travel day is 2 days before the lunar new year.

There's a lot to unpack in these images, but the dates on the x axis of the selected graph are for the year 2024, and the years 2023 and 2019 are lined up by the lunar calendar rather than by date.

The peak travel day is the same all three years.

In 2024 the Lunar New Year fell on February 10th and the peak travel day was February 8th.

In 2020 the Lunar New Year fell on January 25th, and the expected peak travel day would have been on January 23rd.

https://www.nationalgeographic.com/history/article/lunar-new-year

https://qianxi.baidu.com/

Here I've created a composite of the previous image with a WHO image produced from the same data set.

I used GIMP to add daily/weekly tics to the x axis and vertical red lines showing the false and true dates of the lockdown.

The left dotted vertical line is claimed to fall on January 23rd, but actually falls on January 17th.

The vertical red line on the right shows the correct lockdown date of January 23rd.

With the correct placement of the vertical line it's possible to see that excess mortality had already risen substantially before the lockdown was implemented.

Both publications use January 1st 2020 as day 1 of week 1, which I only note because the convention in both China and the US is for day 1 of week 1 to always fall on the Sunday of the week containing January 1st, which usually means day 1 falls during the last week of December of the previous year.

The discrepancy in the Y axis is likely due to this:

"we used the 2019 population in each DSP area to calculate weekly or quarterly mortality rates in 2020 (see supplementary table 3), which were then multiplied by 52 or 4, respectively, to yield annual mortality rates to facilitate comparisons. "

WHO image is Fig. 12. A from the "WHO-convened global study of origins of SARS-CoV-2: China Part"

https://www.who.int/publications/i/item/who-convened-global-study-of-origins-of-sars-cov-2-china-part

Fig 1

Trends in weekly observed (dashed orange lines) versus predicted (blue solid lines) mortality rates for selected major diseases between 1 January and 31 March 2020 in China across different Disease Surveillance Point areas.

First vertical dotted line indicates the time when lockdown was implemented in Wuhan.

Cursor is pointing to the part of this image I'll be examining more closely.

"Outside of Wuhan, no evidence was found of any significant increase in overall mortality, suggesting the success of the rapid control of the spread of SARS-CoV-2 in addition to appropriate maintenance of healthcare services during the nationwide lockdown."

In this thread I will use travel data to show that the lockdown was too late for this to have been possible.

I will further show that this study uses distorted graphs making the lockdown look like it occurred earlier than it really did.

Liu J, Zhang L, Yan Y, Zhou Y, Yin P, Qi J et al.
Excess mortality in Wuhan city and other parts of China during the three months of the covid-19 outbreak: findings from nationwide mortality registries

BMJ 2021; 372 :n415
doi:10.1136/bmj.n415

https://doi.org/10.1136/bmj.n415

#COVID #COVID19

First, the "steep increase" in figure 19 does not appear to be significant.

Second, look at the Y axis on figures 17 and 19: They're off by a factor of 10.

WHO: steepening the curve with Y-axis manipulation.

Fig. 17. Comparison of trends of the pneumonia mortality rate in 2019-2020 versus the average rate of 2016-2018, Wuhan, for the >65-year-old population.