Summary? I'm not signing up
...how the devastation brought by the pandemic in 25 cities and regions compares with historical events. ---Demographer's these events mortality shocks--spikes in the total number of people dying not seen in the weeks before an event...and not lasting once it is over --- e.g., war, famine, bad flu season , natural disasters--
For example : A bad flu season in NYC: Jan. 2011-- 1.05x over normal mortality
Other examples given to
crudely demonstrate the enormity of scale: --- The physical scrolling in the article communicated just as effectively as the written words.
You are looking at ALL "excess deaths", which I think is an accurate view of reality that avoids political counting shenanigans.
1.15x HIV/AIDS crisis in New York City, Sept. 1995 (worst month)
1.31x Chicago heat wave, July 1995
1.61x September 11th in New York City, Sept. 2001 (9/11 was one of the largest mortality shocks in recent American history--meaning 60% more people died that September than normal
1.99x 1957 flu in Santiago, Chile, Aug. 1957
2.00x Paris heat wave, Aug. 2003
2.42x Hurricane Katrina in New Orleans, Aug. 2005
3.61x Spanish flu in Boston, Oct. 1918
3.97x Spanish flu in New York City, Oct. 1918
5x----Few places ever see excess deaths outside of famine/war
Guayas, Ecuador 5.50x-- COVID-19
New York City 5.83x --COVID-19
Bergamo, Italy 6.67x --COVID -19
7.27x Spanish flu in Philadelphia, Oct. 1918
Anticipating comments:
Bottom line: Mortality from all causes is stated relative to historical baselines. In New York in September 2001, mortality was 1.61 times the average monthly rate. The reason is for this is unambiguous-
--The mortality in New York in April was 5.83 times the historical average. What pray tell would one attribute this?
---At certain points coronavirus was outpacing heart disease and cancer deaths (the top 2 killers in the US). ---Moreover,
It's very hard to contract heart disease from a visit to the supermarket or a ride in a bus. It takes a lifetime of poor health choices. . The analysis is comparing increases in deaths from covid-19 to other, individual historical disasters. The idea isn't to "zoom in" to small geographical areas, it's just that individual disasters tend to have limited geographic scope.
The data does not have to be perfect and in fact, data from such a wide range of sources and locations never is. However, the trends and the point is clear, this is a serious situation and if you're concerned about your health, you should take it seriously especially in large cities NYC Metro has a unique perspective-IT WAS VERY REAL HERE--
My questions to the writer's:
--When dealing with an event like 9/11, where substantially all deaths took place in a single day, the shorter the frame the worse the event looks, because the impact on that day's mortality was huge. It you looked at a full year, it was minor, from a statistical point of view.
--Data is political in how your present it and what data you choose. By choosing the "city" level, the mortality appears much worse than if they had chosen the state-level.
This information lacks context. We know +30% of all U.S. deaths occurred in NY. If you had MI, NJ, MA, it is over 50% with a fraction of the total U.S. population. So these deaths are highly targeted. Outside of 10 states (?) states, this virus was a blip on the radar. What generated the out-sized response? I hear if this went unchecked the deaths would have soared to unacceptable levels. Is that true. Some of our worst responding states, FL, TX, etc., had very small excess mortality increases over a typical year.
'The costs are too high': the scientist who wants lockdown lifted faster
--Only some of these figures are labelled with the time span. This makes a huge difference. Are we comparing, say, Jan-May or just the week with the highest death total? That makes a huge difference.
--The point is by reducing the scale to where the problem is concentrated, by mathematical law you end up with it looking "worse". If we only use the confirmed cases by PCR of Covid-19 it has a mortality rate of around 5%. If you use serum studies that show around 10 cases for each one not found by PCR, that gives you a mortality rate of around 0.5%. If you look at ONLY those under 50, you end up with a mortality rate of 0.05% or even less. If you look at ONLY those under 19, you end up with a mortality rate of effectively zero.
--Counterargument is that in 2018 we had no deaths from Covid.
Bottom bottom line: We should have targeted the elderly and at-risk for protection. And masked up but continued to work with precautions. But we have no leadership in all levels of government AND --This virus generates profits for our media bigger than Bush's shock and awe. It sells and sells. Deaths from income inequality? Nobody cares --Medicare for all would save 68,000 lives per year and save 450 bill. But we can't have nice things. Divide and conquer--
Study: 'Medicare for All' would save 68,000 lives, $458B annually. "Medicare for All" would save the U.S. more than $450 billion annually, and the increased access to healthcare would save more than 68,000 lives, compared to the current system, according to an analysis published by The Lancet.
Medicare For All Would Save More Than 68,000 Lives And $450 Billion Every Year, According To New Study
this is some CCP level bull shite. No constitutional right to refuse the vaccine...