COVID-19 Coronavirus Containment Efforts

[.Scott]

Both your link and the CDC list the level of fully vaccinated in Hillsborough county at 19.2%.
I'm not sure where to find the county level 1st dose data at the either the CDC nor the New Hampshire state websites, so I can't comment about that.

The link I provided (https://covidactnow.org/us/new_hampshire-nh/?s=1797716) shows the 1st-shot NH county numbers. Scroll down about a page to get figures for the 6 most populous counties, then click the light blue "View all counties in New Hampshire" to get all 10.

But as I said, the numbers for the 10 counties don't give you the 60.2% shown for the State.

 

[nsaspook]

Australia is cranking down the screws on the India Coronavirus infection quarantine..

https://thehill.com/policy/internat...to-66k-if-citizens-fly-home-from-india-during

Australia Health Minister Greg Hunt https://www.health.gov.au/ministers/the-hon-greg-hunt-mp/media/travel-arrangements-to-be-strengthened-for-people-who-have-been-in-india on Saturday that the government is issuing a temporary pause on travelers from India if the person has been in India for 14 days.

According to Australian Broadcasting Corporation, those that violate the ban could face up to a $66,000 fine (over $50,000 U.S.), five years in prison or both.

“The Government does not make these decisions lightly,” Hunt said in a statement. “However, it is critical the integrity of the Australian public health and quarantine systems is protected and the number of COVID-19 cases in quarantine facilities is reduced to a manageable level.”

 

[Keith_McClary]

We just crossed over 400k

The media in Canada are all over the situation in India, but they don't seem to realize that the per capita rates in Canada are the same, and almost twice as high here in Alberta (although Calgary mayor Naheed Nenshi has pointed this out).

 

[Jarvis323]

The media in Canada are all over the situation in India, but they don't seem to realize that the per capita rates in Canada are the same, and almost twice as high here in Alberta (although Calgary mayor Naheed Nenshi has pointed this out).

There's a lot of uncertainty in the numbers though.

India is doing about five tests for every confirmed case, according to Our World in Data, an online research site. The U.S. is doing 17 tests per confirmed case. Finland is doing 57 tests per confirmed case.

"There are still lots of people who are not getting tested," said Dr. Prabhat Jha of the University of Toronto. "Entire houses are infected. If one person gets tested in the house and reports they're positive and everyone else in the house starts having symptoms, it's obvious they have COVID, so why get tested?"

Jha estimates, based on modeling from a previous surge in India, that the true infection numbers could be 10 times higher than the official reports.
...
"The biggest gap is what's going on in rural India," Jha said. In the countryside, people often die at home without medical attention, and these deaths are vastly underreported. Families bury or cremate their loved ones themselves without any official record. Seventy percent of the nation's deaths from all causes occur in rural India in any given year.

 

[Wrichik Basu]

There's a lot of uncertainty in the numbers though.

Yes, you are right, especially in the part that many people are not getting tested. The primary reason is fear of getting isolated by the community. Many doctors are also advising against testing. For instance, my Dad's boss in the office started having fever two weeks back, but he kept coming to the office. He took Paracetamol just in time so that when the security would check his temperature, it would be normal. His family physician advised him not to get tested, and directly advised COVID medication instead. Later, when the body temperature was not decreasing even after taking 1g paracetamol, he decided to return to his home city. He took a flight (thereby infecting many others). At home, his health degraded, and he had to be hospitalized, where an RT-PCR test was done, and it came positive. Unfortunately, it was too late, and he passed away yesterday. He was younger than Dad, in his forties probably.

 

[PeroK]

The media in Canada are all over the situation in India, but they don't seem to realize that the per capita rates in Canada are the same, and almost twice as high here in Alberta (although Calgary mayor Naheed Nenshi has pointed this out).

The daily per capita rates in India are now significant, although still low compared to European and North and South American numbers at their peak. And the overall figures are still very low - about 10% of European figures.

That's clearly not the whole story.

 

[.Scott]

Yes, you are right, especially in the part that many people are not getting tested. The primary reason is fear of getting isolated by the community. Many doctors are also advising against testing. For instance, my Dad's boss in the office started having fever two weeks back, but he kept coming to the office. He took Paracetamol just in time so that when the security would check his temperature, it would be normal. His family physician advised him not to get tested, and directly advised COVID medication instead. Later, when the body temperature was not decreasing even after taking 1g paracetamol, he decided to return to his home city. He took a flight (thereby infecting many others). At home, his health degraded, and he had to be hospitalized, where an RT-PCR test was done, and it came positive. Unfortunately, it was too late, and he passed away yesterday. He was younger than Dad, in his forties probably.

This certainly reflects Indian government policies that are back-firing.
They have created an environment where people respond in the worse possible way to a potential COVID infection:
1) Hide/deny it.
2) Avoid testing.
3) Take a fever reducer (which would interfere with the unassisted immune response).
4) Continue contacts - and travel.

Unfortunately fir India, this is not the kind of situation that is commonly quickly recognized and corrected. In indicates that things are probably going to go down hill for at least another month.

 

[Astronuc]

In my county, we have 139,100 (47.4% of the total population) having at least the first dose of vaccine, with 99,830 (34.0%) having both of two doses (Pfizer or Moderna). Currently we have 601 positive cases with 41 hospitalizations, which are down from over 1400 cases and 70 hospitalizations at the beginning of April.

I've heard that cases are rising in Oregon, and authorities in Kansas City, Missouri are reporting an increase in Covid cases in younger age groups.

COVID-19 hospitalizations have soared 135% at Saint Luke’s Health System in Kansas City over two weeks and the hospital is currently treating 40 patients, according to local ABC affiliate KMBC.

Doctors say the patients coming through their doors are unvaccinated 30- to 50-year-olds.

Today, Missouri reports 833 COVID-19 hospitalized patients with 137 in the ICU and remaining ICU bed capacity of 22%. State data shows that ICU patients plummeted at the start of 2021 but slowly ticked up again in early April.

Of new confirmed COVID-19 cases in the state, 18 to 24-year-olds followed by 25 to 29-year-olds were responsible for the brunt of new infections this year.

https://abcnews.go.com/US/kansas-ci...italizations-rise-135-young/story?id=77436780

 

[Wrichik Basu]

This certainly reflects Indian government policies that are back-firing.
They have created an environment where people respond in the worse possible way to a potential COVID infection:
1) Hide/deny it.
2) Avoid testing.
3) Take a fever reducer (which would interfere with the unassisted immune response).
4) Continue contacts - and travel.

Unfortunately fir India, this is not the kind of situation that is commonly quickly recognized and corrected. In indicates that things are probably going to go down hill for at least another month.

...or maybe uphill.

The problem is that many of us do realize the situation, but we are not the ones framing the policies.

In some houses around our flat, people are wearing masks inside their house. This simply implies that someone has contracted the virus. During the first wave, when somebody was affected, the local governing body made arrangements for sanitization of the buildings and roads. Now, all this has stopped.

As I wrote earlier, the vaccination program has almost come to a halt. As per the new policies, out of the total number of doses of vaccines manufactured, manufacturers have to reserve 50% for the central Govt (aka Govt. of India). Out of the remaining 50%, all states and private hospitals must order their vaccines. I am not sure where the central Govt. is supplying those vaccines, but it is probably not for the common people. There has been an acute shortage of vaccines in almost all states and private hospitals.

Also, the places where vaccines are being administered are ill-planned. People queuing up for vaccines and people waiting for COVID RT-PCR test are standing in two queues which are just next to each other. Any healthy person might contract the virus from the people standing next to him. This is what Dad experienced when he went to take his first shot. Mom and I haven't taken our shots yet (because we couldn't book a slot yet).

One of our relatives, including his family, has fallen seriously ill. Though they were having fever since some days before the shot, they didn't get themselves tested, but took the vaccines instead. Later, when symptoms aggravated, they all tested positive. The two senior citizens in their house have been admitted to the hospital; one of them is critically ill. The others are at home, but cannot even get up from the bed. The doctor said that probably they were positive even before they took the vaccine, and that is why the illness became worse after they took the vaccine.

Dad's another colleague, who worked in the same floor as his Boss, has been having fever since some weeks. Today, after their Boss passed away, he has been requesting everyone to arrange a bed for him in any hospital, as his SpO2 has started deteriorating. Unfortunately, till evening, no arrangement could have been made; we don't know what will happen tomorrow.

 

[.Scott]

People queuing up for vaccines and people waiting for COVID RT-PCR test are standing in two queues which are just next to each other. Any healthy person might contract the virus from the people standing next to him.

Were these queues indoors out outdoors? Were people social distancing? If indoors, how voluminous and well-ventilated was the room?

If people could get infected from one line to the next, it would be even worse to be uninfected in the testing line.

From what you are describing, hunker down for about 6 weeks. Your neighborhood seems to be quickly heading for herd immunity the hard way.

 

[Wrichik Basu]

Were these queues indoors out outdoors?

Indoors.

Were people social distancing?

What's that? As far as I know, the two queues were just next to each other. Maybe less than one arm distance between them.

If indoors, how voluminous and well-ventilated was the room?

It was ventilated in the sense that there was no air-conditioner, and the windows were open. I don't know how large the room was, or how many windows it had.

 

[russ_watters]

The New Hampshire website has the opposite. Fully vaccinated has leveled off over the last two weeks while first vaccinations are steadily adding up. Since I haven't been following New Hampshire closely, I can't say for sure, but Oregon takes nearly a month to get all the numbers collected, so I wouldn't worry about the latest 2 weeks of data.

That's odd as both sites agree on the current value. It's the past that is different.

Because of reporting delays, a graph constructed using the "current value" looks different from one constructed using the date of vaccination. The only value that they share in common is today's "current value". So a graph of "date of vaccination" will change over time. The past few days will show a plateau (a sharp drop in vaccination rate) and then if you look at it a week later it will show much higher numbers and rate. The only oddity I see is the nh.gov site shows a plateau in the fully vaccinated but not in the 1st dose. It sort of looks like the 1st dose is "today's value" whereas the "fully vaccinated" is date of vaccination. Unless the reporting delay is longer for fully vaccinated.

Incidentally, I've been graphing "current value" from the CDC, which is a pain because each data point only exists "today" and then it's gone. So you have to compile it manually from Wayback Machine if that's what you want.

 

[OmCheeto]

Using a set of countries that varied in quality of their reporting data and in their access to medical care, there's probably too much noise to see any signal that might exist. A better data set to analyze might be to look at the US by county (available here), though there there are also a lot of confounding factors (e.g. politics and culture also differ significantly with population density in the US).

It would appear that your suggestion was gnawing at my brain, so I did some legwork this morning, and, um, came to the same conclusion.

I see little correlation. pop density ref:
https://github.com/camillol/cs424p3/blob/master/data/Population-Density By County.csv

infection/death data
ref: Johns Hopkins:
https://raw.githubusercontent.com/C...ta/csse_covid_19_daily_reports/04-25-2021.csv

 

[Ygggdrasil]

It would appear that your suggestion was gnawing at my brain, so I did some legwork this morning, and, um, came to the same conclusion.

View attachment 282381

I see little correlation.pop density ref:
https://github.com/camillol/cs424p3/blob/master/data/Population-Density By County.csv

infection/death data
ref: Johns Hopkins:
https://raw.githubusercontent.com/C...ta/csse_covid_19_daily_reports/04-25-2021.csv

Just looking at the graph, it looks to me like there is a negative correlation overall (have you calculated the correlation coefficient for the data?).

Regarding PhD-level analyses of the topic (probably as expected), you can find people with PhDs who argue both sides of the issue:

Spreading of COVID-19: Density matters
Wong & Li. PLOS ONE. 15: e0242398 (2020)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0242398

Physical distancing has been argued as one of the effective means to combat the spread of COVID-19 before a vaccine or therapeutic drug becomes available. How far people can be spatially separated is partly behavioral but partly constrained by population density. Most models developed to predict the spread of COVID-19 in the U.S. do not include population density explicitly. This study shows that population density is an effective predictor of cumulative infection cases in the U.S. at the county level. Daily cumulative cases by counties are converted into 7-day moving averages. Treating the weekly averages as the dependent variable and the county population density levels as the explanatory variable, both in logarithmic scale, this study assesses how population density has shaped the distributions of infection cases across the U.S. from early March to late May, 2020. Additional variables reflecting the percentages of African Americans, Hispanic-Latina, and older adults in logarithmic scale are also included. Spatial regression models with a spatial error specification are also used to account for the spatial spillover effect. Population density alone accounts for 57% of the variation (R-squared) in the aspatial models and up to 76% in the spatial models. Adding the three population subgroup percentage variables raised the R-squared of the aspatial models to 72% and the spatial model to 84%. The influences of the three population subgroups were substantial, but changed over time, while the contributions of population density have been quite stable after the first several weeks, ascertaining the importance of population density in shaping the spread of infection in individual counties, and in their neighboring counties. Thus, population density and sizes of vulnerable population subgroups should be explicitly included in transmission models that predict the impacts of COVID-19, particularly at the sub-county level.

Does Density Aggravate the COVID-19 Pandemic?
Hamidi, Sabouri & Ewing. Journal of the American Planning Association 86: 495 (2020)
https://www.tandfonline.com/doi/full/10.1080/01944363.2020.1777891

Problem, research strategy, and findings: The impact of density on emerging highly contagious infectious diseases has rarely been studied. In theory, dense areas lead to more face-to-face interaction among residents, which makes them potential hotspots for the rapid spread of pandemics. On the other hand, dense areas may have better access to health care facilities and greater implementation of social distancing policies and practices. The current COVID-19 pandemic is a perfect case study to investigate these relationships. Our study uses structural equation modeling to account for both direct and indirect impacts of density on the COVID-19 infection and mortality rates for 913 U.S. metropolitan counties, controlling for key confounding factors. We find metropolitan population to be one of the most significant predictors of infection rates; larger metropolitan areas have higher infection and higher mortality rates. We also find that after controlling for metropolitan population, county density is not significantly related to the infection rate, possibly due to more adherence to social distancing guidelines. However, counties with higher densities have significantly lower virus-related mortality rates than do counties with lower densities, possibly due to superior health care systems.

Takeaway for practice: These findings suggest that connectivity matters more than density in the spread of the COVID-19 pandemic. Large metropolitan areas with a higher number of counties tightly linked together through economic, social, and commuting relationships are the most vulnerable to the pandemic outbreaks. They are more likely to exchange tourists and businesspeople within themselves and with other parts, thus increasing the risk of cross-border infections. Our study concludes with a key recommendation that planners continue to advocate dense development for a host of reasons, including lower death rates due to infectious diseases like COVID-19.

 

[Vanadium 50]

it looks to me like there is a negative correlation overall (have you calculated the correlation coefficient for the data?).

I think the better thing to do is to sum this into deciles: rank counties by population density and aggregate the first 31 million people, the next 31 million and so on. By plotting every county your eye is drawn to a lot of small counties that make little aggregate effect on the statistics. The median county only has 25,000 people.

The first decile in population is only 7 counties: Los Angeles County, California, Cook County, Illinois, Harris County, Texas, Maricopa County, Arizona, San Diego County, California, Orange County, California and Kings County, New York. Note that what I am suggesting is to rank by density and sum by population to get deciles: the 7 counties are there just to suggest how different in sizes the various counties are.

 

[Jarvis323]

It would appear that your suggestion was gnawing at my brain, so I did some legwork this morning, and, um, came to the same conclusion.

View attachment 282381

I see little correlation.pop density ref:
https://github.com/camillol/cs424p3/blob/master/data/Population-Density By County.csv

infection/death data
ref: Johns Hopkins:
https://raw.githubusercontent.com/C...ta/csse_covid_19_daily_reports/04-25-2021.csv

I was trying to see if I could reproduce the results, but it doesn't seem like the data you linked matches up. the first link gives density by county in the US, and the second link gives Covid stats for cities around the world, but doesn't have US counties listed.

 

[OmCheeto]

I was trying to see if I could reproduce the results, but it doesn't seem like the data you linked matches up. the first link gives density by county in the US, and the second link gives Covid stats for cities around the world, but doesn't have US counties listed.

The 2nd link lists US counties. You have to filter out the rest of the world.
Are you from America? If so, just look for your state and try and find a city. There are instances where there are counties that match the city: New York county is part of New York city, and San Francisco county is part of the city of San Francisco, etc, etc.

The 1st link was what I had trouble with, and ended up tossing about 100 counties out of the 3000+. Mostly Alaska, Virginia, and Utah. I didn't think 3% would make a big difference, so I didn't bother hand entering them.

 

[Jarvis323]

The 2nd link lists US counties. You have to filter out the rest of the world.
Are you from America? If so, just look for your state and try and find a city. There are instances where there are counties that match the city: New York county is part of New York city, and San Francisco county is part of the city of San Francisco, etc, etc.

The 1st link was what I had trouble with, and ended up tossing about 100 counties out of the 3000+. Mostly Alaska, Virginia, and Utah. I didn't think 3% would make a big difference, so I didn't bother hand entering them.

I see. I was just seeing what I would get, I ended up finding some different sources and I got similar results as you (log(density), deaths per-capita) .

But I'm not sure about how we should actually interpret the density. It is density per-square mile for each county. But counties are often very sparse, with many thousands of acres completely uninhabited. So in this case, you're sometimes incorporating, say 100's of miles of desert, or forrest, into the calculation, yet the population centers might actually be densely packed.

Here is Clark County for example:

I think what this plot is showing is primarily emphasizing information about the ratio of empty land to inhabited land. The reason it only looks like a reasonable plot is with log scale for density is related with that I think. Here it is without a log scale.

It might work to try filtering out counties which have uninhabited areas if there are many of them.

I think county-wise analysis is problematic though.

I found an article discussing this issue.

Calculating population density this way is straightforward, but can be misleading, because nonresidential land covers such as forests, parks, and wetlands, and nonresidential land uses including agricultural and commercial areas are included in the calculation. Since these types of areas are mostly uninhabited, including them when calculating population density understates the true density of the areas where people live. Consequently, a more accurate way of measuring population density would be to exclude the land area taken up by nonresidential land covers and land uses. To do so, we extracted data for the smallest geographic area for which census data are available, the census block. In Census 2010, there were 484,481 census blocks in Florida; of these, 183,972 census blocks (38%) had no people living in them. We recalculated population density by excluding the land area of all census blocks with zero population in each county. That is, only the land area of census blocks with at least one person enumerated in Census 2010 is included in our second measure of population density. While this still includes some types of nonresidential areas, it more accurately reflects the density of the areas where people live. Statewide, just under two thirds of the total land area is made up of census blocks with nonzero population. This varies widely by county, ranging from under 30% in Franklin, Gulf, Monroe, Palm Beach, and Broward counties to over 90% in Jackson, Holmes, and Suwannee counties. The smaller the ratio, the more population density increases under this measure.

https://www.bebr.ufl.edu/node/7619/revisions/10326/compare

They suggest to eliminate the area from empty census blocks. In Clark County, they look like this,

Maybe a more extreme example is Inyo County.

The tiny patch in the upper left actually looks like this.

 

[OmCheeto]

I think county-wise analysis is problematic though.

Using a set of countries that varied in quality of their reporting data and in their access to medical care, there's probably too much noise to see any signal that might exist. A better data set to analyze might be to look at the US by county...

Damned if I do, and damned if I do.

This actually all started with some jesting about why New Zealand and England had such different outcomes.
One factor was population density. Hence, where we are now.

I'm still of the opinion that "hubris" is probably the biggest factor.
Though, the exact word for what is causing this may not exist.

Covid + Hubris = Chubris

Chubris
The attitude that there is something wrong with people in other locations that does not exist in ones own location and therefore what is happening to them cannot possibly happen where you live.

No matter where you look, once people let their guard down, Covid comes to town.

 

[.Scott]

Incidentally, I've been graphing "current value" from the CDC, which is a pain because each data point only exists "today" and then it's gone. So you have to compile it manually from Wayback Machine if that's what you want.

I have been doing something similar.
I use the Ubuntu OS (a variant of Linux). I wrote a bash script that waits for new data each day using the "wget" command. It then formats the data and appends it to a log file.

 

[Astronuc]

Children make up 26% of new COVID-19 cases in Colorado
More than 800 children ages 0 to 19 have been hospitalized with the virus.
https://abcnews.go.com/Health/children-make-26-covid-19-cases-colorado/story?id=77503946

In Colorado, children between 0 to 19 account for 26.4% of all cases reported the week of April 25, according to state data. Overall, children make up 16.57% of all infections in the state since the start of the pandemic.

So far, 847 people between the ages of 0 to 19 in Colorado have been hospitalized and 13 have died since the start of the pandemic through April 29, according to a report by the American Academy of Pediatrics and the Children's Hospital Association.

 

[Wrichik Basu]

Not COVID-19, but definitely related to it:

https://www.hindustantimes.com/citi...-among-covid-19-patients-101620320873994.html

 

[Vanadium 50]

Children make up 26% of new COVID-19 cases in Colorado

1. If you vaccinate everybody 16 and up, you shouldn't be surprised that the fraction of cases 15 and under goes up. Indeed, if this number did not go up for children it would indicate a problem.
2. 13 deaths 0-19 out of 6478 is 0.2%. 99.8% are 20 and up.
3. Zero-19 is an odd choice, since most states use 0-17. Not sure how they got this number or why they wanted to use it. The CDC doesn't have the number of Colorado deaths in the 0-17 group from Covid alone, but it does have 21 deaths from Covid,Influenza or Pneumonia. Nationally, the fraction of 0-17 year olds in the Covid category is 25.3%, so the best estimate of the number of 0-17 year olds Covid fatalities would be 5.3. Scaling national numbers to Colorado one gets an expected value of 3.2 deaths.
   I don't think expecting 3.2 and seeing 5.2 is surprising -- especially given fifty shots at it.

While these "man bites dog" stories bring in the clicks, I don't think they are good for constructing public health policy around.

 

[Astronuc]

https://www.newsweek.com/perfectly-healthy-girl-dies-covid-two-days-after-test-1589493
A fifteen-year-old girl from Illinois has died from COVID-19 just two days after testing positive for the disease. Her family said their daughter, who excelled in school and athletics, had no known pre-existing conditions and had been perfectly healthy until recently, although she had complained of a headache on Saturday

On Sunday, she woke up feeling dizzy and weak, and coughing. The fifteen-year-old took a rapid COVID test, which her mother had bought, and the result turned out to be positive. By Monday, the teen's condition had deteriorated so much that she had to be hospitalized. Dykota Morgan passed away early Tuesday morning.

What is troubling is that she apparently had complained of headaches for two weeks. I wonder if they bothered to check for a fever. She had to have it for at least 3-5 days before onset of severe symptoms.
https://wgntv.com/news/coronavirus/...rom-covid-19-two-days-after-testing-positive/Read more here: https://www.miamiherald.com/news/coronavirus/article251210879.html

The Miami Herald is reporting that 'younger patients are causing Florida to have among the highest Covid hospitalization rates in the country.' That is based on a per capita basis. Then again, Florida is third in population (21,477,737) behind California (39,512,223) and Texas (28,995,881) and ahead of New York (19,453,561). July 2019 Estimates

Overall, the number of people being treated for COVID in Florida hospitals has ticked down over the last two weeks after a slight rise in the beginning of April. About 3,000 Floridians were https://bi.ahca.myflorida.com/t/ABICC/views/Public/COVIDHospitalizationsCounty?%3AshowAppBanner=false&%3Adisplay_count=n&%3AshowVizHome=n&%3Aorigin=viz_share_link&%3AisGuestRedirectFromVizportal=y&%3Aembed=y on Thursday, down about 10% from 3,345 patients on April 23.

More than a quarter of confirmed COVID hospital admissions in Florida for the week predating May 1 were among people between 30 and 50 years old, compared to 13% in the week predating Jan. 15.

Covidtracking.com kept some good statistics/numbers, but they stopped reporting cumulative hospitalizations, since too many states did not report those numbers.

Only about two-thirds of states and territories report data for Cumulative hospitalized/Ever hospitalized, and even fewer states report data for Cumulative in ICU/Ever in ICU and Cumulative on ventilator/Ever hospitalized. Therefore, adding these state and territory figures together to get a national count (as we do for other COVID-19 metrics with complete reporting such as cases and tests) drastically undercounts the true cumulative national number of COVID-19 patients who have ever been hospitalized, admitted to the the ICU, or placed on a ventilator.

According to the Carlson School of Management, U of Minnesota, 37 states have reported cumulative hospitalizations, currently at 1,108,960 hospitalizations. States not reporting include, California, Nevada, Texas, Louisiana, Missouri, Illinois, Michigan, North Carolina, West Virginia, Pennsylvania, Delaware and Massachusetts. The numbers hospitalized likely exceed 1.5 million based on California and Texas leading the nation in positive cases and deaths, and the number of those hospitalized could be approaching 2 million. Why is this important/significant? Because about one-third (possibly 500+ k) of those hospitalized have long term adverse effects to lungs or neurological damage. The full scale of physiological injury to those who 'recovered' has yet to be measured.

https://www.sciencedaily.com/releases/2021/05/210506105342.htm (small study with 1/3 of patients having lung damage)
https://www.biospace.com/article/la...er-neurological-damage-in-covid-19-patients-/ (large-scale study with 1/3 patients have some neurological issues).
https://www.forbes.com/sites/robert...months-later-new-study-finds/?sh=61833a944eb2

NY Times reports cumulative positive cases of 32,632,099 and 579,634 deaths due to Covid-19 in the US along, and we are far from over.

  State      Positives   Deaths
California   3,753,425   62,165
Texas        2,909,093   50,690
Florida      2,258,425   35,548
New York     2,062,707   52,038 (state confirms 42211 deaths)
Illiois      1,352,140   24,483
Pennsylvania 1,171,863   26,497
Georgia      1,082,584   19,661
Ohio         1,080,121   19,344
New Jersey   1,005,938   25,740
N. Carolina    985,775   12,761

 

[Astronuc]

Zero-19 is an odd choice, since most states use 0-17. Not sure how they got this number or why they wanted to use it.

Each state does it slightly differently, which is annoying.

In Washington state, they report the age groups for deaths (5553):

Age Group	Percent of Cases	Percent of Hospitalizations	Percent of Deaths
0-19	17%	2%	0%
20-34	31%	9%	1%
35-49	24%	16%	4%
50-64	18%	26%	13%
65-79	8%	29%	34%
80+	3%	18%	49%
Unknown	0%	0%	0%

New York States reports age groups by decades: 0-9, 10-19, 20-29, . . . .

Age group   Pct    Deaths
  0-9       0.0%      15  
10-19      0.0%      12
20-29      0.3%     144
30-39      1.1%     477
40-49      2.9%    1220
50-59      8.2%    3477
60-69     18.0%    7587
70-79     26.0%   10964
80-89     27.4%   11523
  90+      16.1%    6783

Total death 42211, and there may be another 10k deaths according to estimates by NY Times and others.

 

[PeroK]

https://www.newsweek.com/perfectly-healthy-girl-dies-covid-two-days-after-test-1589493
A fifteen-year-old girl from Illinois has died from COVID-19 just two days after testing positive for the disease. Her family said their daughter, who excelled in school and athletics, had no known pre-existing conditions and had been perfectly healthy until recently, although she had complained of a headache on Saturday

In this case, it doesn't appear that this girl died directly from COVID. The news item isn't specific on the cause of death, but a severe headache is not a typical COVID symptom.

Moreover: if the virus is now widespread in younger people in the US, then many young people who are hospitalised for any reason will test positive on admission to hospital. You need to be careful to distinguish between young people admitted to hospital because of COVID and those who have COVID in addition to whatever else requires hospitalisation.

Such news items, in my experience, are full of data analysis fallacies.

 

[morrobay]

In this case, it doesn't appear that this girl died directly from COVID. The news item isn't specific on the cause of death, but a severe headache is not a typical COVID symptom.

Unfortunately headaches can be symptoms. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273035/

 

[Rive]

In this case, it doesn't appear that this girl died directly from COVID. The news item isn't specific on the cause of death, but a severe headache is not a typical COVID symptom.

There are/were reported cases among young about having negligible symptoms with already developing pneumonia

Also, there seems to be a percentage of victims having the first 'real' symptom as sudden death.

This Covid thing is just far too tricky to discuss individual cases without knowing the exact details.

 

[AlexCaledin]

- It might be simply probability of inhaling a droplet with many viruses deep into one's lungs - in such case, the unprepared immune system can hardly help much...

 

[Vanadium 50]

She had to have it for at least 3-5 days before onset of severe symptoms.

According to KTLA, the symptoms started "little more than a week after she turned 15". According to her mother's gofundme page (because when you lose a child, of course the first thing you need to do is set up a gofundme page) she turned 15 two weeks ago. So this is consistent with that. Her parents didn't think it was Covid then, and so didn't have her tested until it was too late.

I will be called cruel and heartless, but think it is a bad idea to formulate public policy based on anecdotes that tug at the heartstrings. (And Google tells me a similar story happened half a year ago with a girl named Sarah Simental)

282 children have died from Covid in the US. In that time, the number of "excess murders" in the same age bracket caused by the lockdown is above 500 and may be as high as 1000. So the "Just think about the children!" argument doesn't actually point in the direction of "Lockdowns forever!".

 

[PeroK]

Also, there seems to be a percentage of victims having the first 'real' symptom as sudden death.

If you have medical evidence that COVID may produce sudden, asymptomatic death, then let's see it.

 

[Rive]

If you have medical evidence that COVID may produce sudden, asymptomatic death, then let's see it.

Thought it's common knowledge by now.
random link (with good references included) by looking for 'covid sudden death'.

 

[PeroK]

Thought it's common knowledge by now.
random link (with good references included) by looking for 'covid sudden death'.

Far from compelling, I would say. The cases seem to be older people who suddenly have a cardiac arrest.

This isn't my area of expertise, so I can't contribute more than say I'm sceptical of the News Week story, which seems to contain no medical evidence that the cause of death was COVID.

And, the data from the UK seems clear enough: most deaths from COVID in the older age groups; most excess deaths in the older age groups. We've no evidence of significant excess deaths in children during the pandemic.

 

[Wrichik Basu]

This editorial published in The Lancet explains why the current Govt. is to be blamed for the second wave of the pandemic in India.

In the last 24 hours, we have had >401k new COVID patients, and >4k deaths in the country.

 

[Rive]

We've no evidence of significant excess deaths in children during the pandemic.

I don't really get where that come from.

If you have medical evidence that COVID may produce sudden, asymptomatic death, then let's see it.