Wuhan's House of Cards: the outbreak of COVID-19, in context
In order to see the big picture, we need more than a microscope - we need a telescope.
*Note — My current focus is researching COVID-19’s origins, as part of the D.R.A.S.T.I.C. team of scientists, journalists & researchers. Recent news: D.R.A.S.T.I.C.’s research forms a large portion of the basis for investigations begun by the US Senate, House & National Institutes of Health. Recent appearances and/or discussion on 60 Minutes, The Joe Rogan Exp., Fox News, JRE [again], Bill Maher, & CNN. I am thankful for the efforts of @TheSeeker, @gilles@Harvard2H, @DaoYu15, among others, for placing the breadcrumbs that encouraged me to begin digging deeper into this set of anomalies.
my original Twitter thread [less dense, except for sarcasm]
The larger crimes are apt to be the simpler - for the bigger the crime the more obvious, as a rule, is the motive.
-Sherlock Holmes
‘Seems Legit’
The juxtaposition of a man riding a bicycle as a dead body sits on the sidewalk is a perfect analogy for the 15-17 months we’ve spent trying to maintain a sense of normalcy in the midst of historic disruption.
In honor of today [May 22nd], which happens to be the anniversary of my first commentary on the question of COVID’s origins, I wanted to shed light on discrepancies that have been lost amidst the noise of ‘sexier’ smoking guns, like gain-of-function research.
This article forms the basis of a future submission for peer review, which shows that the data provided by China to the WHO showing early case information is incompatible with most of the other data published on the subject - almost all of which comes from censor-approved studies in Wuhan or elsewhere in China.
Actions speak louder than words, especially when China isn’t saying much to begin with. Even the publication of the full gene sequence in early January was unplanned; Shi’s team had completed the task more than a week before the milestone was announced, but an unauthorized release from another research group forced the hand of the WIV. China also took deliberate actions to obfuscate the background information concerning the geographical distribution of the first cases, which would've most likely pointed to the research labs in the center of Wuhan, not to a remote part of Yunnan Province 1,000 miles away. This article goes a step further, by laying out the evidence/data relating to
1) Seroprevalence,
2) Demographic & Geospatial distributions,
3) Haplotypes
…and how the difference between it and China’s WHO report data is significant enough that only one of the two sets can be true.
These articles and hypotheses deserve greater attention, so why haven’t more media outlets investigated the most plausible analysis of the pandemic’s genesis? China’s intransigence is unusual, because many possible outcomes could help exonerate the country from suspicions regarding the origin of the pandemic. The alternative is that China’s silence is a natural result of being stuck in a corner, unable to offer any evidence that could clear their name because none exists. Conversely, there would be little sense in refusing to release non-personal treatment information if it clearly showed a favorable pattern centered somewhere else.
In short, the numbers reported to the WHO [after a year] were given mere summaries of China’s own investigation, with no raw data in support; the WHO was reduced to simply drawing conclusions from unverifiable data. This is equivalent to allowing the defendant in a court case providing the prosecution with the evidence that criminal guilt must be extracted from.
Many scientists are focusing on identifying the erroneous elements of the SARS-CoV-2 genome; my gut tells me that invalidating the data provided to the WHO would be most effective in the short term. Why?
Because, if the epicenter of the early outbreak was not in Jianghan District [i.e. near the Huanan Market], but in Wuchang District [on the opposite side of the Yangtze River], it would prove that the limited data China released to the WHO was fabricated - in which case there would suddenly be a much larger number of scientists willing to aid in the investigation. More importantly, however, the incredible effort necessary to fabricate a narrative centered on the opposite side of a mile-wide river would inevitably force the world to confront the real question of this pandemic - what's in Wuchang that's worth the effort.
Seroprevalence Anomalies
Wuhan University sits along the eastern edge of Wuchang District, just like the Wuhan Institute of Virology [WIV], a few minutes’ walk away. Both institutions had front-row seats to the first chapter of what has become a global pandemic, so it’s fair to say that the academic research they’ve published wasn’t intended to disprove state-produced analyses. I think, perhaps, that the Chinese CDC should’ve reviewed the year’s worth of publications before clicking ‘send’ to the WHO. Especially for the studies that measured antibodies in the population of Wuhan.
[Note: Immunoglobins M & G are the immune system’s primary defense mechanisms - proteins produced after the detection of a foreign substance or organism somewhere inside the body.]
When I saw the IGG/IGM survey that @TheSeeker268 re-posted from last year, I immediately knew that it could clarify the importance of Wuchang district, relative to the WIV/Huanan Market/etc. However, when I began concatenating the data from various sources, I discovered far more inconsistencies than I expected - inconsistencies which ran counter to the Chinese narrative focused on Huanan Market as the epicenter of the early outbreak.
The data from Wuhan's 10M sero survey [below] had some curious features-such as the positivity proportion when broken down by gender: 56% Female-44% Male, out of a population sample of 10 million in which the There were also more asymp. cases in Wuchang-but, being May, that didn't help, since it's expected that embers of later fires were the ones still burning.
...but in a wildfire the initial location tends to cool long before the rest of the flames go out. When I ran the numbers and re-sorted the districts [below], it was clear that Wuchang and the east side districts had seen a sizable portion of the action, but there was no way to pinpoint WHEN.
….Especially since I’d never seen the other survey results before. But, the IGG/IGM #’s point directly towards Wuhan as being the elder hotspot;
What makes Wuchang seem like the ‘elder hotspot?’ The map on the left shows the percentage of each district’s total population infected, and the right shows the estimated total number of asymptomatic people. When you put this together with other surveys also discussed in this article, the final results in June look a lot like the crucial period from mid-December to mid-January, distribution-wise:
and the data from the emergency ‘assistance?’ line matched up almost perfectly with the IGG #’s:
The image above comes from a study that used the local emergency call line that had been set up as an on-call support network to help sick individuals or their families get transportation assistance to a hospital with availability, alert authorities of an emergency, etc. The service ran through Weibo [a Chinese social media app akin to FaceBook or Twitter]; the researchers who performed the study took all of the usage data for the special service and statistically compared it with population density and other demographic variables to map out the expansion and evolution of the outbreak. The figure below, from a separate study that compiled all official case and death statistics, shows that the Weibo data [though derived from a smaller sample size] tracked the infection trends effectively.
The Chinese researchers had access to better data [i.e. the actual official government health statistics, unlike researchers outside of China], and thus were able to correlate the patient age profiles with the individual neighborhoods [sub-districts known as ‘streets’]; both data sets also reinforced the M<F discrepancy.
By contrast, the WHO report [prepared by Chinese researchers] showed a vastly different geographic distribution of the early cases:
It also reflected a 56.3%-43.7% M>F gender ratio, very different from the other surveys, amongst the first set of patients - the 174 December cases that emerged at the very beginning of the outbreak.
Because the December cases are the most important and the most controversial in the origins investigation, they will figure prominently throughout my analysis; conversely, because China has taken great pains to prevent information about those patients being released, international suspicions have intensified.
China’s reluctance to release that information is especially unusual given how much criticism they received for their lack of transparency during the original SARS outbreak in 2002-2003; the WHO actually passed stronger reporting measures specifically to prevent that behavior from being repeated. Despite being far more capable of providing that information, China has actually worked harder to suppress it than 17 years ago. As you’ll see, other evidence may help fill such gaps, and the clearer our picture becomes, the more powerful the West’s ability to push back on China’s action will be. With any luck, it may help to build the case to the level of ‘beyond a reasonable doubt.’
The reported gender/sex ratio is consistent with the rest of the data China has provided, but not with the rest of the districts in Wuhan or almost every other statistical analysis done by scientists in China or the rest of the world.
[This next bit is in progress, but analyzes the Chinese data within the WHO report in detail, as the 2nd picture provides a preview of]:
Age & Sex Statistical Anomalies
[very much still in progress]
The F>M disparity in Wuchang makes more sense - especially if nurses tend to be female in 🇨🇳, as here in the US. Caixin had reported c. 1/15 Z. Nanshan's anecdote of 1 pt. infecting 14 med. workers - sealing the H2H debate.
[remainder in progress]
Geospatial & Demographic Data
Hmm... but the WHO report certainly doesn't paint this picture like the 2nd one, does it? Guess which pic has data to support it...from Chinese researchers... imagine if the WHO had looked at these side-by-side. But how do we know #2 is legit?
WHO Report:
Well, that's a powerfully strong correlation right there [below]. What it shows is that the Weibo data is perhaps the best external predictor of confirmed case trends.
Plus, it's from China, so the WHO shouldn't question it. Oh, and it happens to mesh nicely with these overall case number statistics from June.
and this distribution
and this age profile
Whoa! and this note on the data:
If there was any doubt, the authors then explicitly tells us that this was EARLY data [pre-lockdown]:
Then it shows the district where Huanan Market was getting hit afterwards [#3]
and this shows the progression.
It's hard to tell exactly where the spark was lit, but all we need to know is which side of the river it fell on. My guess is the one with the WIV, the BSL-4, several other labs and all of the early death. Just a guess.
You see, one constant across the globe was initially high CFR's that decreased over time, which makes sense as drs gain their sea legs. And guess which districts fared worse in that regard [#1, my own creation]. Even better, the final #'s looked very similar [#2]
well, I got 120 from the first map... they should be the same, even if one is depicting something different than the others in terms of the color of the point. With 54 pts missing, their map shows a 82.5% - 17.5% ratio for the west/east sides of the river. Just slightly off.
Haplotype Analysis
Perhaps the best part is that 🇨🇳's haplotype chart was cherry-picked, & was organized by 'sample date' [i.e. whatever they chose], to minimize the connection between the two lineages. Guess which pic is from the WHO report? The more descriptive chart, or the lesser?
The answer is #2; you might have noticed that it looks like a shrub compared to the quantum snowflake above it. The artwork, however, isn’t the most concerning aspect of the haplotype analysis in the WHO report; the part I circled in red is the note explaining how they built the chart. First, they allude to “66 high-quality/non-redundant sequences,”
Clusters?
In the 1st 174 cases [WHO report], there were only 7 clusters [5 spouse pairs, 1 child, 2 pairs in Huanan Market] Not only were the locations bunched on the 'west' side - COVID didn't seem to want to spread indoors, in cramped housing, in districts with very high population density. This is especially interesting because the latest studies have clearly demonstrated that the length of time exposed to an infected person indoors is the variable with the strongest positive correlation for becoming infected yourself.
The World Health Report
[in progress - here are my working notes, to preview]
World Health Organization Origins Report – Demographic Abnormalities:
a) Missing Wuchang Data in all categories
b) Only 120 of 164 cases placed on map
c) Geo distribution according to Weibo data and official reports is dichotomous
d) As an example, the first 44 reported cases were listed as: 27 linked to the Huanan Market and 17 that could not be linked. In the WHO report published 13 months later,
e) 3) Cases numbers in several studies have shown that Wuchang ultimately suffered the largest numbers of cases and deaths during the outbreak, a fact that was obscured by the continuous used of per capita measurements; this reinforced the perception that Jianghan was the center of the outbreak, even though patient and infected health-care-worker numbers rose faster and earlier across the river in Wuchang
f) 3a) The centrality of Jianghan [in the context of being the accelerant in spreading the disease at the beginning] has remained the accepted model for the dispersion of infections throughout the city. This has conditioned researchers to question data that undermines that model, rather than considering the model itself.
g) 3b) This information bias was also driven by the over-reliance on the first research articles that described transmission dynamics in Wuhan. China waited a year before announcing [via the WHO report] that the true number of diagnosed COVID-19 cases was 174, after dozens of studies had relied upon the earlier-reported figure of 44. This had profound consequences when attempting to calculate the estimated TMRCA.
h) Gender imbalance between the data on the two sides of the river
i) IGM/IGG Data supports Wuchang emergence
j) Cases follow Line 2 much closer than proximity to market, early on
k) Dr. Quay’s sequence data
l) Haplotype is ridiculous, spare and infers incorrect view of phylogeny
m) Lack of sequences from Wuchang
n) Although it took a year to investigate and publish, virtually all extant data [stretching back to last summer] is of higher quality, and contradicts the WIV. The GIS department of Wuhan University is right across the street from the WIV
Telescopes
I could probably keep going for a while, but it should be fairly obvious that the WHO report is the outlier against China's own published journal articles [that Chinese censors pre-approved]. The exact path COVID-19 took to get going is unclear. But even if it came from an alien spaceship from the Andromeda galaxy, there shouldn't be any confusion about where the spaceship landed. After all, before Galileo described the heliocentric model of the solar system, he had to invent the telescope first.
From my primary ResearchGate project description:
It’s impossible to overstate the importance of verifying the early Wuhan outbreak data - extracting every drop of evidence from the viral sequences is vital, but the basic epidemiological information I’ve reviewed here is foundational for the origin investigation. I’ll restate my conclusion from the introduction:
“If the epicenter of the early outbreak was not in Jianghan District [i.e. near the Huanan Market], but in Wuchang District [on the opposite side of the Yangtze River], it would prove that the limited data China released to the WHO was fabricated - in which case there would suddenly be a much larger number of scientists willing to aid in the investigation. More importantly, however, the incredible effort necessary to fabricate a narrative centered on the opposite side of a mile-wide river would inevitably force the world to confront the real question of this pandemic - what's in Wuchang that's worth the effort?”
Given the historical economic & cultural impact of the COVID-19 pandemic, and the number of deaths it continues to produce, the leaders of our nations and international institutions should be less concerned with weighing the diplomatic cost of injuring China’s reputation. I can think of 3.4 million individuals whose feelings should be considered first, especially given that they are unable to advocate for themselves.
~C. H. Rixey
#whatsinwuchang
~[My ongoing origins research references project is published on ResearchGate, finally available as a downloadable spreadsheet. Currently it includes 434 linked sources]
Selected references for external graphics and data:
Post-lockdown SARS-CoV-2 nucleic acid screening in nearly ten million residents of Wuhan, China- 20201120 - Wuhan Municipal Health Commission & Huazhong University of S&T
Global Study on the Origin of COVID-19 - 20210330 - World Health Organization
WHO-convened Global Study of the Origins of SARS-CoV-2 [Annexes] - 20210331 - World Health Organization
Using the COVID-19/Influenza Ratio to Estimate Early Pandemic Spread in Wuhan & Seattle - 20200812 - University of Texas
Epidemiological characteristics and the entire evolution of coronavirus disease 2019 in Wuhan, China - 20201008 - Hubei CDC & Huazhong University of S&T
Epidemiological Analysis of new coronavirus pneumonia in Wuchang District, Wuhan - 20201001 - Central Hospital Hubei & Wuchang District Health Bureau
Wuhan's experience in curbing the spread of coronavirus disease (COVID-19)
Exploring Urban Spatial Features of COVID-19 Transmission in Wuhan Based on Social Media Data - 20200619 - School of Urban Design, Wuhan University
Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China - 20200410 - Tongji Hospital & Huazhong University of S&T
Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia - 20200326 - New England Journal of Medicine
Epidemiology of and Risk Factors for COVID-19 Infection among Health Care Workers: A Multi-Centre Comparative Study- 20200928 - Key State Laboratory of Pathogen & Biosecurity, Beijing
Rushed data collection of suspected early Covid-19 cases in Wuhan - 20201015 - Gilles Demaneuf, Medium
Where Did the 2019 Coronavirus Pandemic Begin and How Did it Spread?..... Line 2 of the Wuhan Metro System - 20201029 - Dr. Steven Quay
Investigate the origins of COVID-19 - 20210510 - Science - Bloom, Baric, Chan, Relman et al.
Positive rate of RT-PCR detection of SARS-CoV-2 infection in 4880 cases from one hospital in Wuhan, China, from Jan to Feb 2020 - 20200307 - Renmin Hospital of Wuhan University
- Are Officials In China Downplaying Infection Numbers?
Selected additional references:
China's response to a novel coronavirus stands in stark contrast to the 2002 SARS outbreak response - Outbreak of a novel coronavirus - China coronavirus: mild but infectious cases may make it hard to control outbreak, report warns - The Novel Coronavirus Originating in Wuhan, China: Challenges for Global Health Governance - Potential of large "first generation" human-to-human transmission of 2019-nCoV - Genomic characterization and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding - The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health - The latest outbreak in Wuhan, China - A pneumonia outbreak associated with a new coronavirus of probable bat origin - Origin and evolution of the 2019 novel coronavirus - Accelerated viral dynamics in bat cell lines, with implications for zoonotic emergence - Updated understanding of the outbreak of 2019 novel coronavirus (2019-nCoV) in Wuhan, China - China coronavirus: cases surge as official admits human to human transmission
(c) C. H. Rixey, 2021