Skeptic 🇺🇦🇵🇸 @antifascistcovid19denial@qoto.org

Impact of the COVID-19 Pandemic on Emergency Department Visits — United States, January 1, 2019–May 30, 2020

"The number of visits for conditions including nonspecific chest pain and acute myocardial infarction decreased, suggesting that some persons could be delaying care for conditions that might result in additional mortality if left untreated...

...The striking decline in ED visits nationwide, with the highest declines in regions where the pandemic was most severe in April 2020, suggests that the pandemic has altered the use of the ED by the public.

Hartnett KP, Kite-Powell A, DeVies J, et al. Impact of the COVID-19 Pandemic on Emergency Department Visits — United States, January1, 2019–May 30, 2020. MMWR Morb Mortal Wkly Rep 2020;69:699–704. DOI: http://dx.doi.org/10.15585/mmwr.mm6923e1

Lab leak vs natural spill over is a distraction from the lack of evidence that COVID-19 is a viral pandemic originating in China.

In my previous threads I showed that the lockdown in Wuhan was too late.

I showed that all cause mortality was already well above normal and 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.

I showed that the vast majority of international travelers went to other Asian countries.

I showed that studies, including the Seattle Flu Study, finding a lack of early spread of the virus lack plausibility due to the absence of false positives, and I showed that there is a larger body of contradictory evidence.

In this thread, I will show that the excess mortality during the spring 2020 wave was associated with a decline in emergency department utilization, not just for low acuity visits but for high acuity visits as well.

If this is confusing due to media reporting on overwhelmed hospitals, the confusion is coming from the fact that the emergency department and intensive care unit are separate.

I will present data showing that ED utilization went down while ICU utilization went up, suggesting that patients delayed care until it was too late.

https://ourworldindata.org/grapher/excess-deaths-daily-per-100k-economist

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

#COVID #COVID19 #epidemiology #bioinformatics #healthcareisahumanright

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.

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.

Perhaps they were referring to the pneumonia mortality in the 65+ age group:

Fig. 19. Comparison of trends of the pneumonia mortality rate in 2019-2020 against average rate of 2016-2018, Hubei outside Wuhan, for the >65-year-old population.

Fig. 14. A: Comparison of trends of the all-cause mortality rate in 2019-2020 versus the average
rate of 2016-2018, Hubei Province outside Wuhan, for all age groups;

Fig. 12. A: Comparison of trends of the all-cause mortality rate in 2019-2020 against average rate
for 2016-2018 in Wuhan, for all age groups;