/media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Pandemics, Kp, sunspot notes.txt www.BillHowell.ca 21May2020 initial 08********08 09Mar2021 covid "virus versus policy" deaths - prompted by Sundowners' executive dcision on allowing coffee etc 210302 FAIR Health study - the Impact of COVID-19 on Pediatric Mental Health.pdf A sst private healthcar claims https://s3.amazonaws.com/media2.fairhealth.org/whitepaper/asset/The%20Impact%20of%20COVID-19%20on%20Pediatric%20Mental%20Health%20-%20A%20Study%20of%20Private%20Healthcare%20Claims%20-%20A%20FAIR%20Health%20White%20Paper.pdf 210302 FAIR Health study - percent change 2019-2020 in emergency room claim lines related to major depressive disorder and generalized anxiety disorder, age group 13-18 years.png 210302 FAIR Health study - percent change 2019-2020 in overdose claim lines and substance use disorder claim lines, age group 13-18 years.png 210302 FAIR Health study - percent change 2019-2020 reasons for emergency room visits (including top five and mental health conditions), age group 19-22 years 210302 FAIR Health study - percent change 2019-2020 in emergency room claim lines related to major depressive disorder and generalized anxiety disorder, age group 13-18 years 210302 FAIR Health study - percent change 2019-2020 in emergency room claim lines for top three mental health conditions, age group 19-22 years Sorry for not shutting up, but Terry Armstrong raised a key point that I completely missed : "... My opinion – the coffee is needed for the mental health of our seniors. ..." Keep in mind : covid kills the dead (yeah - I know I'm a prick for saying that, just to cause trouble) suicide kills the young, especially entering family-formation years, especially women Don't look now, but we may already have blood on our hands? There is a [suspicious, ?dishonest?] vacuum of information about covid policy-related deaths versus deaths caused by the virus (the latter minus the dishonest attributions of deaths to corona virus, like [pneumonia, cancer, car accidents, gun deaths, etc] perhaps not as bad as it sounds?). See the section "Covid policy-driven suicides : news items and Howell blog comments from the Spring of 2020" below my signature block on this issue, which I haven't followed since. With strange timing related to our current email exchanges (you guys are weird, right?), a week ago, 02Mar2021, I received Dobler's book "Solar Behaviour", then just a few days later, last Friday 05Mar2021, I read a Sacha Doble post about a study showing a DOUBLING of suicides in some regions of US states (see the link in the section "Children die from Covid Suicide, not the Virus: " below my signature block). It is very strange, somewhat incompetent that the study's article does NOT provide the numbers of suicide, just the percent jump (this may be a result of privacy laws, which have become a major impediment to truth), and that it does NOT compare covid "virus versus policy-driven" deaths. Sacha Dobler is not a professional, nor is he an expert in epidemiology or policy or anything related to this EXCEPT concepts at which essentiall the experts fail. I do NOT agree with everything he says, nor perhaps even most of what he says. As I mentioned above, I have two books of his (still reading the second), and I've read some of his exchanges with others. What I can say is that, right or wrong, he is comfortably beyond the one-in-ten-thousand "strong thinker" level (which includes less than one in 10,000 university professors in a given field of expertise). He may be a one-in-a-million [creative, revolutionary, breakthrough] thinker, but that is not yet shown. My guess that there isn't a single university professor in Canada, nor amateur, that can kiss his ass on this topic if he was to take the timme to look at it in detail. It's not about decades of rote memorization, it's about thinking. Even still, I take everything with a grain of salt. Comments on the lack of honest [suicide, health] statistics and studies of covid-19 "public policy versus corona virus disease" deaths While there is no end of yap in the media of [protecting, helping] people with [emotional, mental] health issues arising from the covid situation, there is essentially honesty regarding the [statistics, models, policy impacts]. Ergo, the yap can certainly be looked at as yet another massive marketing campaign by health-care professionals and government policy [experts, consultants] who will make a killing on [vast, extra] public money to do their work. I STILL don't have basic statistics on suicide, in spite of searching last spring, but I suspect it is available if you do enormous amount of digging, but not from [professionals, government policy, academics]. USA CDC is a great institution that somehow still does great work beyond the mandatory politics, and some data is likely there now to help. I have seen basically nothing in Canada, other than some [private, amateur] stuff, but nothing like the USA. +-----+ https://www.marketwatch.com/story/the-same-number-of-people-could-die-from-deaths-of-despair-as-have-already-died-in-the-us-from-coronavirus-new-study-finds-2020-05-08?mod=newsviewer_click The same number of people could die from ‘deaths of despair’ as have already died in the U.S. from coronavirus, new study finds Published: May 9, 2020 at 8:14 p.m. ET By Quentin Fottrell ‘More Americans could lose their lives to deaths of despair, deaths due to drug, alcohol, and suicide, if we do not do something immediately’ In addition to more than 75,000 deaths in the U.S. from COVID-19, the growing epidemic of "deaths of despair" in the U.S. is also increasing due to the pandemic — and another 75,000 more people will likely die from drug or alcohol misuse and suicide, according to new research released by Well Being Trust and the Robert Graham Center for Policy Studies in Family Medicine and Primary Care. Projections of additional "deaths of despair" range from 27,644, assuming a quick economic recovery and the smallest impact from unemployment, to 154,037, assuming a slow recovery and the greatest impact from unemployment. "We can prevent these deaths by taking meaningful and comprehensive action as a nation," the researchers wrote in the "deaths of despair" report published Friday. 200509 MarketWatch, Well Being Trust - deaths of despair with unemployment increases.png 08&&&&&&&&08 Howell : I don't get it. The table from Well Being Trust lists increases in mortality per 1% increase in unemployment, whereas unemployment has shot up by far more than that (say 10-20%). The [1, 1.3, 1.6]% groupings represent what? - I assumptions that the 1% is the base case, the rest are for higher scenarios, but it's confusing. Recalling the figure that apparently has been taught in economics classes, for every 1% increase in unemployment, 40,000 Americans due, so the table is in line with that, approximately. To me, it seems to suggest that FAR MORE Americans will die from the recession than corona virus, even if you take the higher range of model estimates. For example, the 08May2020 https://covid19-projections.com/#view-projections model has a high range off 300k deaths due to corona virus by 04Aug2020 (~180k as best guess, ~120k low). Compare that to a naive wild guess of 10% increase of unemployment times a medium projection of 50k deaths per 1% increase of unemployment = 500k deaths? I don't have much confidence in any of the numbers, but perhaps these are the best that we have. +-----+ https://www.marketwatch.com/story/big-short-investor-who-made-a-killing-during-the-financial-crisis-the-economic-shutdown-is-worse-than-the-coronavirus-2020-04-07?mod=newsviewer_click ‘Big Short’ investor says the shutdown is worse than the coronavirus: ‘It bleeds deep anguish and suicide’ Published: April 7, 2020 at 4:35 p.m. ET By Shawn Langlois ... He offered more detail in his emails this week to Bloomberg News as to why he would immediately lift stay-at-home orders for everybody but high-risk groups. "I would let the virus circulate in the population that is not likely to get severe disease from it," he wrote. "This is the only path that comes close to balancing the needs of all groups. Vaccines are not coming anytime soon, so natural immunity is the only way out for now. Every day, every week in the current situation is ruining innumerable lives in a criminally unjust manner." Meanwhile, the COVID-19 tally keeps rising in the U.S., home to the most confirmed cases at almost 400,000, with 11,851 deaths, according to Johns Hopkins University. Globally, here are now 1.39 million cases and 79,091 deaths. Another 292,973 people have recovered. >> Awesome, tuys (Trump and him) make sense! 08&&&&&&&&08 Howell - It's great to see someone stand out and question the current orthodoxy. It will be interesting to see what % of COVID-19 serious cases are saved by "flattening the curve" (eg reducing peak (shock) demands on hospital resources to reduce triaging and effects on other patients). Will this just end up as an exceptionally bad flu season? https://www.cdc.gov/flu/about/burden/index.html Nabil Istafananus - The problem with this reasoning is you can't prove the counterfactual. It is absolutely clear, this virus left unabated and no vaccines is more than 10 times more deadly than the flu. After we open up the economy in 60 days, these same folks will say, see, this was only as bad as the flu and they won't believe that social distancing actually saved millions of lives. We can't prove it. I trust the infectious disease experts and the massive mobilization of our scientists for effective treatment will be enough to open things up gradually. Folks who are saying opening up the economy without a strong testing and proven treatments are short-term thinkers and simply protecting their porfolios. The stock market will come back. Take a deep breath and calm down folks. We're in this together and I trust that we will not be locked down forever. Howell - Nabil Istafananus - Thanks, and I agree with your comments. Believe me, I am not looking for "proofs", nor could I expect that. But I am hoping to see a range of estimates over time based on diverse approaches (what I call "multiple conflicting hypothesis") that are transparent and available (subject to privacy constraints etc, in the health area, of course). At the end of the day, lessons learned and comparisons to past pandemics are not just inevitable, but part of the process of improving (we hope). Others will not have our perspective, nor do we have theirs, which is normal. +-----+ https://www.marketwatch.com/story/how-do-you-choose-between-economic-deaths-of-despair-and-coronavirus-victims-economists-lawmakers-grapple-with-a-moral-conundrum-2020-03-26?mod=newsviewer_click George Loewenstein, professor of economics and psychology at Carnegie Mellon University, said it’s not as simple as making a choice between the human lives of Americans and the long-term health of the American economy. "I think it might be a false dichotomy because we don’t have a very good understanding of what the impact of a severe [economic] depression would be on human life," he said. "It will dramatically decrease the quality of human life, and it will certainly kill people as well." "We’ve already have unprecedented levels of deaths of despair, and, if we lose a generation as a result of the coronavirus pandemic, that’s going to have mortality consequences," Loewenstein added. "They’re just going to be more difficult to discern from the statistical victims. If you ignore the impact on quality of life — which is potentially an immense thing that should be taken into account — we don’t really understand what the impact of the economy on mortality." +-----+ https://www.quora.com/The-Big-Short-2015-movie-Is-it-true-what-Ben-Rickert-Brad-Pitts-character-said-that-40-000-people-die-when-unemployment-goes-up-by-1 The Big Short (2015 movie): Is it true what Ben Rickert (Brad Pitt's character) said that 40,000 people die when unemployment goes up by 1%? 02--02 Hlynur Hallgrímsson, Political Economist Answered February 23, 2016 Yes, pretty much. The actual number mentioned in introductory econ classes is 37,000 deaths. It's often credited to Gregory Mankiw and his textbook "Macroeconomics", but I can't find it in my book (the 7th edition), perhaps it wasn't in the actual book but only in the accompanying slides. Anyway, looking online it shows up in "The American Economy: What it is and what it isn't" by Thomas and Carson on page 300 under the subheading "The cost of unemployment". They cite their source as Bluestone, Harrison and Baker, "The Causes and Consequences of Economic Dislocation" from 1981. The information put forth for a 1 %-point increase is as follows: 37.000 deaths... of which: 20.000 heart attacks 920 suicides 650 homicides (the rest is undisclosed as far as I can see) Hope that helps. 02--02 John Ross, physician, scribbler Answered February 22, 2016 There is evidence that unemployment is bad for your health. According to one meta-analysis of 42 studies involving 20 million people, the risk of death increases 63% when you lose your job. Some of this risk is attributable to the negative health effects of stress and poverty, some of this is due to crappy health behaviors that are more common with poverty and unemployment (bad diet, smoking, booze, drugs). One obvious criticism is reverse causation: people who are already unhealthy and have poor health behaviors are probably more likely to lose their jobs than other employees. Here's a link to the meta-analysis: Losing Life and Livelihood: A Systematic Review and Meta-Analysis of Unemployment and All-Cause Mortality http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3070776/ 08********08 25Jan2021 https://principia-scientific.com/indias-miraculous-ivermectin-covid-treatment-is-only-3-per-person/?utm_source=feedburner&utm_medium=email&utm_campaign=Feed%3A+psintl+%28Principia+Scientific+Intl+-+Latest+News%29 India’s ‘miraculous’ ivermectin COVID treatment is only $3 per person Published on January 22, 2021 Written by Patrick Delaney ...ivermectin, a Nobel Prize–winning anti-parasitic agent, “basically obliterates transmission of this virus,” with “miraculous effectiveness.” Ivermectin has been the subject of dozens of studies and anecdotal success stories since it was found to reduce COVID-19 in a laboratory last June. “I’ve been treating COVID pretty much every single day since the onset,” Kory said. “When I say ‘miracle’ I do not use that term lightly…that is a scientific recommendation based on mountains of data that has emerged in the last three months.” in India, they began treating coronavirus patients early, including the use of hydroxychloroquine (HCQ) Last March, as debates raged in the U.S. over the merits of HCQ, following President Trump’s endorsement of the drug, India had already recommended it in its national guidelines affirming it “should be used as early in the disease course as possible…and should be avoided in patients with severe disease.” Following the June discovery of ivermectin’s efficacy in treating the virus, along with significant subsequent testing, the largest state in their nation, Uttar Pradesh (UP) (pop. 230 million), announced in August that it was replacing their HCQ protocol with ivermectin for the prevention and treatment of COVID-19. 08********08 23Jan2021 CTV webSite - finally has world comparisons https://www.ctvnews.ca/health/coronavirus/covid-19-curves-compare-canada-and-other-key-nations-1.4881500 when did this start? even now, still nowhere near as good as BillHowell.ca - eight months later!!!! does CBC have this yet? https://newsinteractives.cbc.ca/coronavirustracker/ >> NOTHING - no [per capita, country, multi-nation regions] comparisons CBC is pure shit!!! 08********08 22Dec2020 World covid-19 summary by country https://www.worldometers.info/coronavirus/ see "$d_webRawe""Pandemics, health, and the Sun/corona virus/201222 worldometers.info World covid-19 summary by country.ods" /media/bill/SWAPPER/Website - raw/Pandemics, health, and the Sun/corona virus/201222 worldometers.info World covid-19 summary by country.ods 08********08 20Dec2020 emto Sarah see my email to her How embarrassing. I went back to an old website that I used last spring to find Canadian data, www.worldometers.info. This referred to a ctv webSite : https://www.ctvnews.ca/health/coronavirus/tracking-every-case-of-covid-19-in-canada-1.4852102#quebec However, I still haven't found a link to a Health Canada site where I can download the actual data. I will only look for that when I find the time to do a general update (make several months from now, but it's not a priority for me. Already, the numbers question the whole basis of modern thinking, even though a number of "experts" were concerned about a covid resurgence during the flu season. Maybe we have to get back to long-standing historical perspectives by specific "strong thinkers" (mostly amateurs), like Peter Doshi of https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2374803/ in USA (professional). https://www.worldometers.info/coronavirus/country/canada/ 201221 WorldOmeters.info Daily New Cases in Canada 3day avg.png 201221 WorldOmeters.info Daily New Deaths in Canada 3day avg.png 201221 WorldOmeters.info Outcome of Cases (Recovery or Death) in Canada 3day avg.png 211221 CTVnews.com Alberta 7-day avg [cases, deaths] per 100k.png 211221 CTVnews.com British Columbia 7-day avg [cases, deaths] per 100k.png 211221 CTVnews.com Canada 7-day avg [cases, deaths] per 100k.png 211221 CTVnews.com Ontario 7-day avg [cases, deaths] per 100k.png 211221 CTVnews.com Quebec 7-day avg [cases, deaths] per 100k.png These images have been saved to my webDirectory on corona virus : http://www.billhowell.ca/Pandemics,%20health,%20and%20the%20Sun/corona%20virus/ Are influenza deaths confounded with covid-19? Historally, pneumonia and influenza have always been confounded. I am not sure if influenza tests are like covid-19 now, making statistics more specific? If not, that should raise eyebrows... In the case of Alberta, re-imposition of stronger self-isolation started with strong guidance to self-isolate circa 24Nov?, then legally invoked the 2-person rule, and shut-down of small businesses and restaurants 08Dec. There is not much to suggest a strong effect of ck-downs, as what we are seing resembles the traditional influenza seasonal process. Even if it is working, it may be having no effect long-term other than avoidance hospital triaging, and some quite modest life savings there? https://www.bdplaw.com/publications/alberta-announces-updated-covid-19-restrictions/?utm_source=Mondaq&utm_medium=syndication&utm_campaign=LinkedIn-integration https://www.alberta.ca/covid-19-orders-and-legislation.aspx#toc-0 ******** 09Jul2020 OK - I have accumulated results in "1968-2018 suicides by date and sex.txt" BUT - I should have converted the [year, month, day] to a fractional year >> but from 2005 only the day-of-week is available! I can't get around that /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/suicide/USA monthly suicides 1968-2018 http://www.BillHowell.ca/Pandemics, health, and the Sun/suicide/USA monthly suicides 1968-2018.jpg http://www.BillHowell.ca/Pandemics,%20health,%20and%20the%20Sun/suicide/USA%20monthly%20suicides%201968-2018.jpg ******** 08Jul2020 +-----+ 1984 guide : /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/1984 CDC-NCHS-NVSS guide.pdf - is the same format used as 1979? >> YES!! see "1_US CDC-NCHS data table formats.txt" ******** 07Jul2020 view line codings across different files OUCH!! - file formats are all different : might be same : 1968-2004, 2005-2018 ?? qnial> sampleData +-----+ Mort68 8000 11110529999000211052079912220390613 5858 001 00300130080030 80000007021017960020 1001 0 02001 07 9600 8000 22340019999000234068039922220610818 5656 001 00300130080030 80000006021014272020 1001 0 02001 04 2720 +-----+ Vs79mort 790 790 +-----+ MORT85.PUB 850 01 110100136301010019999136301180 010910111075412110 5 30188 299099942051155909 01001010015240 1 431 191004406802000111431 0 01 431 0 850 01 220100136301010649999136301035 010320111088432311 5 30188 299099938051155909 01001011271000 2 410 174003606801700311410 0214149061514 0 03 410 041490514 0 +-----+ VS97MC.USPUB 0 11019993630101999999913630103299112301 10111066391909 6 4010067 990999380 99999 199701999019991000 009 410 174003606801700111410 0 0003207 01 410 0 0 11010083630101008999913630101233212301 10232055371708 6 2340074 990999310 99999 199701015010150450 009 199109800220080110011119910 0003207 01 19910 +-----+ Mult98.pub 0 11010453630101045999913630112933101101 10111080422210 6 2010066 990999400 99999 199801089010893440 009 428918600410680180011142890 0002108 01 42890 0 11010453630101045023313630112933112301 10111071402009 6 2180065 990999450 37000 199801089010893440 009 496 223005802002400211496 021311 0 0002108 02 311 0496 0 +-----+ Mort99us.dat 0 11019993630101999999913630106399100101 10111038331306 2 4570116 990999 99999 199901999019991800 009 7 R570380001101363600111R570 01 R570 0 11019993630101999999923630100099906101 10111086432311 6 2010066 990999 99999 199901999019990000 009 7 N19 327001000683100111N19 01 N19 +-----+ Mort00us.dat 0 11010083630101008999913630101233212301 10232070402009 2 2010071 990999 99999 200001015010150450 009 7 C900132000410271500311I469 21C900 31I500 03 C900 I469 I500 0 11010083630101008999913630101233212301 10111067391909 2 2010067 990999 99999 200001015010150450 009 7 J81 278000890623700211R570 21J81 02 J81 R570 +-----+ Mort05uspb.dat 1 11 001 F1045 351507 1M2 2005U7UN C439098 028 15 0111C439 01 C439 01 11 100 6 1 13 001 M1061 381808 1D7 2005U7UN J439266 084 28 0111J439 01 J439 01 11 100 6 +-----+ MORT06.DUSMCPUB 1 10 001 F1084 422210 4W2 2006U UN I500230 067 22 0111I500 01 I500 01 11 100 6 1 06 001 F1093 442411 1W1 2006U UU I251215 063 21 0311I500 12J81 21I251 03 I251 I500 J81 01 11 100 6 +-----+ VS07MORT.DUSMCPUB 3 02 001 M1072 402009 1M2 2007U7UN C259088 025 07 0111C259 01 C259 01 11 100 6 1 12 001 M1035 331306 7M2 2007U2UN 99X74 429 125 40 0211T141 12X74 02 X74 T141 01 11 100 6 +-----+ Mort2018US.PubUse.txt 3 3101 F1046 351507 1D2 2018U7CN A419023 010 37 0311J189 21J869 31A419 03 A419 J189 J869 01 11 100 601 1 3101 M1028 311105 7S4 2018N1BN 9 V475392 114 38 0511S099 12V475 13T099 14T149 15S021 05 V475 S021 S099 T099 T149 03 23 100 803 ******** 07Jul2020 US CDC-NCHS mortality multiple cause file downloads using QNial # download stats qnial> processCDC_1968_to_78 % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 21.9M 100 21.9M 0 0 245k 0 0:01:31 0:01:31 --:--:-- 383k download done : US CDC-NCHS mortality multiple cause file 1972.zip Archive: /media/bill/SWAPPER/Projects - 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mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Vs79mort % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 55.8M 100 55.8M 0 0 354k 0 0:02:41 0:02:41 --:--:-- 526k download done : US CDC-NCHS mortality multiple cause file 1980.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1980.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Vs80mort % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 48.0M 100 48.0M 0 0 491k 0 0:01:40 0:01:40 --:--:-- 545k download done : US CDC-NCHS mortality multiple cause file 1981.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1981.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Vs81mort % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 49.0M 100 49.0M 0 0 334k 0 0:02:30 0:02:30 --:--:-- 476k download done : US CDC-NCHS mortality multiple cause file 1982.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1982.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Vs82mort % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 61.6M 100 61.6M 0 0 398k 0 0:02:38 0:02:38 --:--:-- 570k download done : US CDC-NCHS mortality multiple cause file 1983.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1983.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Vs83mort % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 65.4M 100 65.4M 0 0 408k 0 0:02:44 0:02:44 --:--:-- 508k download done : US CDC-NCHS mortality multiple cause file 1984.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1984.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Vs84mort % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 72.3M 100 72.3M 0 0 410k 0 0:03:00 0:03:00 --:--:-- 502k download done : US CDC-NCHS mortality multiple cause file 1985.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1985.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/MORT85.PUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 73.2M 100 73.2M 0 0 460k 0 0:02:42 0:02:42 --:--:-- 365k download done : US CDC-NCHS mortality multiple cause file 1986.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1986.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/MORT86.PUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 74.3M 100 74.3M 0 0 432k 0 0:02:55 0:02:55 --:--:-- 168k download done : US CDC-NCHS mortality multiple cause file 1987.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1987.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/MORT87.PUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 73.1M 100 73.1M 0 0 430k 0 0:02:53 0:02:53 --:--:-- 555k download done : US CDC-NCHS mortality multiple cause file 1988.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1988.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Vs88mort % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 82.0M 100 82.0M 0 0 197k 0 0:07:04 0:07:04 --:--:-- 317k download done : US CDC-NCHS mortality multiple cause file 1989.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1989.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/MORT89.PUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 81.3M 100 81.3M 0 0 218k 0 0:06:21 0:06:21 --:--:-- 120k download done : US CDC-NCHS mortality multiple cause file 1990.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1990.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/MORT90.PUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 82.4M 100 82.4M 0 0 318k 0 0:04:25 0:04:25 --:--:-- 579k download done : US CDC-NCHS mortality multiple cause file 1991.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1991.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/MORT91.PUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 76.4M 100 76.4M 0 0 408k 0 0:03:11 0:03:11 --:--:-- 294k download done : US CDC-NCHS mortality multiple cause file 1992.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1992.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/MORT92.PUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 77.8M 100 77.8M 0 0 346k 0 0:03:49 0:03:49 --:--:-- 575k download done : US CDC-NCHS mortality multiple cause file 1993.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1993.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/MORT93.PUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 78.9M 100 78.9M 0 0 319k 0 0:04:12 0:04:12 --:--:-- 571k download done : US CDC-NCHS mortality multiple cause file 1994.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1994.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/MORT94.PUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 79.6M 100 79.6M 0 0 300k 0 0:04:31 0:04:31 --:--:-- 422k download done : US CDC-NCHS mortality multiple cause file 1995.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1995.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/MORT95.PUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 79.6M 100 79.6M 0 0 339k 0 0:04:00 0:04:00 --:--:-- 513k download done : US CDC-NCHS mortality multiple cause file 1996.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1996.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/MORT96.PUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 84.0M 100 84.0M 0 0 388k 0 0:03:41 0:03:41 --:--:-- 484k download done : US CDC-NCHS mortality multiple cause file 1997.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1997.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/VS97MC.USPUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 77.7M 100 77.7M 0 0 254k 0 0:05:13 0:05:13 --:--:-- 372k^[[1;2B download done : US CDC-NCHS mortality multiple cause file 1998.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1998.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Mult98.pub % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 83.9M 100 83.9M 0 0 282k 0 0:05:04 0:05:04 --:--:-- 320k download done : US CDC-NCHS mortality multiple cause file 1999.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 1999.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Mort99us.dat % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 78.4M 100 78.4M 0 0 298k 0 0:04:29 0:04:29 --:--:-- 544k download done : US CDC-NCHS mortality multiple cause file 2000.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2000.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Mort00us.dat % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 45 79.2M 45 35.9M 0 0 41968 0 0:33:00 0:14:59 0:18:01 0 curl: (56) Recv failure: Connection timed out download done : US CDC-NCHS mortality multiple cause file 2001.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2001.zip End-of-central-directory signature not found. Either this file is not a zipfile, or it constitutes one disk of a multi-part archive. In the latter case the central directory and zipfile comment will be found on the last disk(s) of this archive. unzip: cannot find zipfile directory in one of /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2001.zip or /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2001.zip.zip, and cannot find /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2001.zip.ZIP, period. % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 84.4M 100 84.4M 0 0 155k 0 0:09:15 0:09:15 --:--:-- 531k download done : US CDC-NCHS mortality multiple cause file 2002.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2002.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Mort02us.dat % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 24 85.2M 24 20.7M 0 0 31644 0 0:47:03 0:11:26 0:35:37 0 curl: (56) Recv failure: Connection timed out download done : US CDC-NCHS mortality multiple cause file 2003.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2003.zip End-of-central-directory signature not found. Either this file is not a zipfile, or it constitutes one disk of a multi-part archive. In the latter case the central directory and zipfile comment will be found on the last disk(s) of this archive. unzip: cannot find zipfile directory in one of /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2003.zip or /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2003.zip.zip, and cannot find /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2003.zip.ZIP, period. % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 84.1M 100 84.1M 0 0 192k 0 0:07:27 0:07:27 --:--:-- 426k download done : US CDC-NCHS mortality multiple cause file 2004.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2004.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Mort04us.dat % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 79.1M 100 79.1M 0 0 465k 0 0:02:54 0:02:54 --:--:-- 570k download done : US CDC-NCHS mortality multiple cause file 2005.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2005.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/Mort05uspb.dat % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 85.2M 100 85.2M 0 0 458k 0 0:03:10 0:03:10 --:--:-- 40506 download done : US CDC-NCHS mortality multiple cause file 2006.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2006.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/MORT06.DUSMCPUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 85.4M 100 85.4M 0 0 325k 0 0:04:29 0:04:29 --:--:-- 374k download done : US CDC-NCHS mortality multiple cause file 2007.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2007.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/VS07MORT.DUSMCPUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 95 87.2M 95 83.4M 0 0 96089 0 0:15:52 0:15:10 0:00:42 0 curl: (56) Recv failure: Connection timed out download done : US CDC-NCHS mortality multiple cause file 2008.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2008.zip End-of-central-directory signature not found. Either this file is not a zipfile, or it constitutes one disk of a multi-part archive. In the latter case the central directory and zipfile comment will be found on the last disk(s) of this archive. unzip: cannot find zipfile directory in one of /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2008.zip or /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2008.zip.zip, and cannot find /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2008.zip.ZIP, period. % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 83 86.3M 83 72.0M 0 0 67031 0 0:22:30 0:18:46 0:03:44 0 curl: (56) Recv failure: Connection timed out download done : US CDC-NCHS mortality multiple cause file 2009.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2009.zip End-of-central-directory signature not found. Either this file is not a zipfile, or it constitutes one disk of a multi-part archive. In the latter case the central directory and zipfile comment will be found on the last disk(s) of this archive. unzip: cannot find zipfile directory in one of /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2009.zip or /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2009.zip.zip, and cannot find /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2009.zip.ZIP, period. % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 88.0M 100 88.0M 0 0 141k 0 0:10:38 0:10:38 --:--:-- 75455 download done : US CDC-NCHS mortality multiple cause file 2010.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2010.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/VS10MORT.DUSMCPUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 90.3M 100 90.3M 0 0 184k 0 0:08:22 0:08:22 --:--:-- 114k download done : US CDC-NCHS mortality multiple cause file 2011.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2011.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/VS11MORT.DUSMCPUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 91.7M 100 91.7M 0 0 138k 0 0:11:18 0:11:18 --:--:-- 240k download done : US CDC-NCHS mortality multiple cause file 2012.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2012.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/VS12MORT.DUSMCPUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 94.3M 100 94.3M 0 0 150k 0 0:10:40 0:10:40 --:--:-- 461k download done : US CDC-NCHS mortality multiple cause file 2013.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2013.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/VS13MORT.DUSMCPUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 83.6M 100 83.6M 0 0 330k 0 0:04:19 0:04:19 --:--:-- 519k download done : US CDC-NCHS mortality multiple cause file 2014.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2014.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/VS14MORT.DUSMCPUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 87.2M 100 87.2M 0 0 363k 0 0:04:05 0:04:05 --:--:-- 507k download done : US CDC-NCHS mortality multiple cause file 2015.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2015.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/VS15MORT.DUSMCPUB % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 102M 100 102M 0 0 259k 0 0:06:43 0:06:43 --:--:-- 342k download done : US CDC-NCHS mortality multiple cause file 2016.zip Archive: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/US CDC-NCHS mortality multiple cause file 2016.zip inflating: /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA CDC-NCHS/VS16MORT.DUSMCPUB ******** 06Jul2020 Suicides weekly - with CDC wonder, maybe even daily using day of week turn off export /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/suicide/CDC Wonder suicides month 1999-01 results.txt /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/influenza/USA NCHS/US CDC mortality multiple cause file 1968.REVISED.txt /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/influenza/USA NCHS/US CDC mortality multiple cause file users guide.pdf +-----+ https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm#Mortality_Multiple Mortality Multiple Cause Files 1968-1978 /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA NCHS/US CDC mortality multiple cause file 1968 https://www.cdc.gov/nchs/nvss/mortality_public_use_data.htm see page 22 for data layout in each line 31-32 month of death 33-34 day of month of death, 99=day of death not stated 35 sex (1=male, 2=female) 36 race (0-8 depending on race) 37 race (1=white, 2=non-white) 38 race (1=white, 2=black, 3=other) 39-41 age (mashed stuff) 42-43 age (simpler grouped for infants then per 10 years) 44-45 age (simpler grouped for infants then per 05 years) ... 60-63 underlying cause of death (See the “Eighth Revision International Classification of Diseases,” Volume 1, adapted for use in the United States. For accidents, poisonings and violence, the external cause of injury [E800-E999] is coded. The nature of injury (800-999) is not coded. These positions do NOT include the letter E for the external cause of injury. For those underlying causes that do not have a 4th digit, location 124 is blank (Hex 40). 64-68 281 cause recode A recode of the underlying cause into 281 groups for NCHS publications. See Appendix 4-2 for a complete list of recodes and the undell)’lng causes included. 69-71 69 cause recode A recode of the groups for NCHS code range [not m~lusi~’el und=ll>”in: cause into 69 publications See Appenclix I-3 for a complete llst of recode> and the underl?lng causes included. 01-810... Code range (not incluslve) suicide codes CDC Wonder : uses U03,X60-X84,Y87.0 CDC-NCHS Leading causes of death 1900-1998 : E950-E959 https://stackoverflow.com/questions/14462529/how-to-get-first-n-characters-in-unix-data-file $ cat "/media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/influenza/USA NCHS/US CDC mortality multiple cause file 1968.REVISED.txt" | sed 's/\(.{30}\)\(.{4}\)\(.{26}\)\(.{4}\)/1968 \2 \4/' >"/media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/suicide/USA CDC-NCHS/1968 suicides.txt" $ cat "/media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/influenza/USA NCHS/US CDC mortality multiple cause file 1968.REVISED.txt" | sed 's/.{30}\(.{4}\).{26}\(.{4}\)/1968 \1 \2/' >"/media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/suicide/USA CDC-NCHS/1968 suicides.txt" $ cat "/media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/influenza/USA NCHS/US CDC mortality multiple cause file 1968.REVISED.txt" | sed 's/^\(.\)\{30\}\(.\)\{4\}\(.\)\{26\}\(.\)\{4\}\(.*\)/1968 \2 \4/' >"/media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/suicide/USA CDC-NCHS/1968 suicides.txt" >> can't get sed to work $ cat "/media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/influenza/USA NCHS/US CDC mortality multiple cause file 1968.REVISED.txt" | cut -b 31-34,60-63 >"/media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/suicide/USA CDC-NCHS/1968 suicides.txt" >> not terribly useful I used QNial : qnial> loaddefs link d_QNial_mine 'readDataFile fixed cols.ndf' >> WORKED! for 1968 : 21,372 suicides from "/media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/influenza/USA NCHS/US CDC mortality multiple cause file 1968.REVISED.txt" 21,372 lines in output file "/media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/suicide/USA CDC-NCHS/1968 suicides.txt" >> ALL suicide causes were present (950-959) >> However, day of month data was not input, so I only have the month +-----+ https://wonder.cdc.gov/ https://www.cdc.gov/nchs/nvss/mortality_tables.htm https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm https://www.cdc.gov/nchs/products/vsus/ta.htm See the criteria below or in "CDC Wonder suicides 1998-2018 request details, notes.txt" with notes >> Can't seem to get the data!? Just get : +-----+ Try : ICD-10 113 Cause List https://www.cdc.gov/nchs/data/dvs/lead1900_98.pdf /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/CDC-NCHS Leading Causes of Death, 1900-1998.pdf Actually, suicides are only reported in this document for : nyet 1900-1957, 1970 all [sexes, races, ages] only 1958-1969,1977,1980 male only, all [races, ages] 1971 Male & total, all [races, ages] 1991-1998 male & female, all [races, ages] 1972-1976,1978-1979,1981-1990, +-----+ https://www.nimh.nih.gov/health/statistics/suicide.shtml#part_154969 National Institute of Mental Health >> 2001-2017, but just use CDC Wonder +-----+ https://afsp.org/suicide-statistics/ American Foundation for Suicide prevention Suicide statistics /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/suicide/AFPS suicide facts & figures 2009-2018 >> not useful +-----+ https://www.nimh.nih.gov/health/statistics/suicide.shtml >> not so useful... +-----+ CDC Wonder : https://wonder.cdc.gov/ +--+ FAQ - How do I download my data extract as a file for use in other software? You can download a simple text file, which is a tab-delimited (the columns of data values are separated by Tabs) line-listing of your data results. First, you must send a request for data. The "By-Variables" you select in your data request define the columns and rows, as well as the detail of your data. See tables for a quick example. After you have the results of your data request, you can click on the Table tab near the top of the screen, to go to the Table Options page, where you can set whether to show totals and sub-totals, zero value rows, labels on every row and the decimal precision of data items, such as rates. Where are the options? Click on the link that says "Options" or look near the bottom of the page, below the the table of data, and above the data description, citation and other issues, for a box with the table option controls. Then press the Tab Export button, located at the top of the page, above the data results. Your web browser then asks you whether to save the file, or to open it now. If you open it now, you can later select your File menu's Save As option to save the file to computer with your preferred folder and filename. Most analysis software packages can load delimited simple text, when the rows and columns are separated by commas or by tabs. If your software has trouble importing a delimited file, you may wish to remove all titles and descriptive text included in the file above and below the numeric values. Note: More information about importing the data extract into Epi Info and other applications can be found here. Notes About the data extract file: Tabs separate the data values (columns). Character values are encapsulated with double quotation marks. Character values are limited to 130 characters. The descriptive information items, such as the title, citation and other issues, appear as character values in rows at the bottom of the file. +--+ Request : 1. Organize table layout Group results by : ICD-10 1133 cause list (and bys : none) Measures : Deaths, population No checks for : 95% confidence interval, standard error age adjusted rate, percent of total deaths Title : CDC Wonder suicides 1998-2018 2. Select location State, Census region, or HHS region : All 2013 urbanization : All categories 3. Select demographics Ten-year age groups : All ages Gender : all Hispnocs origin : aall Race : all races 4. Select year and month : All 5. sELECT WEEKDAY, AUTOPSY, AND PLACE OF DEATH All Weekdays Autopsy : All values pLACE OF DEATH : All places 6. Select causes of deaths ICD-10 113 cause list. #Intentional self-harm (suicide) (*U03.X60-X84,y87.0) 7. Other options, uncheck : export results (useless for one month, day ata a time?) uncheck : show totals (gives error) uncheck : show zero values uncheck : show suppressed values precision : 1 decimal places data access timeout : 10 minutes Send (at bottom of page) Messages: Message Totals and Percent of Total are disabled when data are grouped by 113 or 130 Cause Lists. Check Caveats below for more information. ICD-10 113 Cause List Results are sorted in by-variable order Move this column one place to the right Deaths Click to sort by Deaths ascending Click to sort by Deaths descending Move this column one place to the rightMove this column one place to the left Population Click to sort by Population ascending Click to sort by Population descending Move this column one place to the left Crude Rate Per 100,000 Click to sort by Crude Rate Per 100,000 ascending Click to sort by Crude Rate Per 100,000 descending #Intentional self-harm (suicide) (*U03,X60-X84,Y87.0) 745,360 6,088,633,001 12.2 Note: A '#' symbol preceding the label indicates a rankable cause of death. More information. TopOptionsNotesCitationQuery Criteria Notes: Caveats: Totals and Percent of Total are disabled when data are grouped by a 113 or 130 Cause List because both aggregate and detailed values are displayed in the table. Also be aware that charts and maps containing both aggregate and detail data could be misleading. As of April 3, 2017, the underlying cause of death has been revised for 125 deaths in 2014. More information. Circumstances in Georgia for the years 2008 and 2009 have resulted in unusually high death counts for the ICD-10 cause of death code R99, "Other ill-defined and unspecified causes of mortality." Caution should be used in interpreting these data. More information. Circumstances in New Jersey for the year 2009 have resulted in unusually high death counts for the ICD-10 cause of death code R99, "Other ill-defined and unspecified causes of mortality" and therefore unusually low death counts in other ICD-10 codes, most notably R95, "Sudden Infant Death Syndrome" and X40-X49, "Unintentional poisoning." Caution should be used in interpreting these data. More information. Circumstances in California resulted in unusually high death counts for the ICD-10 cause of death code R99, "Other ill-defined and unspecified causes of mortality" for deaths occurring in years 2000 and 2001. Caution should be used in interpreting these data. More information. The population figures for year 2018 are bridged-race estimates of the July 1 resident population, from the Vintage 2018 postcensal series released by NCHS on June 25, 2019. The population figures for year 2017 are bridged-race estimates of the July 1 resident population, from the Vintage 2017 postcensal series released by NCHS on June 27, 2018. The population figures for year 2016 are bridged-race estimates of the July 1 resident population, from the Vintage 2016 postcensal series released by NCHS on June 26, 2017. The population figures for year 2015 are bridged-race estimates of the July 1 resident population, from the Vintage 2015 postcensal series released by NCHS on June 28, 2016. The population figures for year 2014 are bridged-race estimates of the July 1 resident population, from the Vintage 2014 postcensal series released by NCHS on June 30, 2015. The population figures for year 2013 are bridged-race estimates of the July 1 resident population, from the Vintage 2013 postcensal series released by NCHS on June 26, 2014. The population figures for year 2012 are bridged-race estimates of the July 1 resident population, from the Vintage 2012 postcensal series released by NCHS on June 13, 2013. The population figures for year 2011 are bridged-race estimates of the July 1 resident population, from the Vintage 2011 postcensal series released by NCHS on July 18, 2012. Population figures for 2010 are April 1 Census counts. The population figures for years 2001 - 2009 are bridged-race estimates of the July 1 resident population, from the revised intercensal county-level 2000 - 2009 series released by NCHS on October 26, 2012. Population figures for 2000 are April 1 Census counts. Population figures for 1999 are from the 1990-1999 intercensal series of July 1 estimates. Population figures for the infant age groups are the number of live births. Note: Rates and population figures for years 2001 - 2009 differ slightly from previously published reports, due to use of the population estimates which were available at the time of release. The population figures used in the calculation of death rates for the age group 'under 1 year' are the estimates of the resident population that is under one year of age. More information. Beginning with the 2018 data, changes have been implemented that affect the counts for ICD-10 cause of death codes O00-O99 compared to previous practice. In addition, data for the cause of death codes O00-O99 for 2003 through 2017 reflect differences in information available to individual states and probable errors. Caution should be used in interpreting these data. More information can be found at: https://www.cdc.gov/nchs/maternal-mortality/. Help: See Underlying Cause of Death, 1999-2018 Documentation for more information. Query Date: Jul 6, 2020 3:31:08 PM ******** 28Jun2020 find "/home/bill/PROJECTS/" -type f -name "*Prechter*" ADD Alex Fournier - Thunderbolts presentation on consciousness Create separate web-pages for [Prechter, Puetz]? eg use in investments web-page ******** 27Jun2020 Web-page [updates, postings] +-----+ central web-page : /media/bill/SWAPPER/Website - raw/Cool stuff/suicide - Berk, Dodd, Henry 2006 Australian female suicides with geomanetic activity 1970-2000.png /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/suicide/Berk, Dodd, Henry 2006 Do ambient electromagnetic fields affect behaviour. A demonstration of the relationship between geomagnetic storm activity and suicide.pdf https://crise.ca/en/membre/melissa-henry/ Adjunct Professor Department of Oncology, Jewish General Hospital, McGill University >> one of authors? Melissa, not Margaret? Michael Berk - Department of Clinical and Biomedical Sciences—Barwon Health, University of Melbourne, Geelong, Australia *Seetal Dodd - Department of Clinical and Biomedical Sciences—Barwon Health, University of Melbourne, Geelong, Australia Margaret Henry - Department of Clinical and Biomedical Sciences—Barwon Health, University of Melbourne, Geelong, Australia Dr. Jerry Tennant 17Aug2017 "Healing is voltage" EU2017 Electric Universe Future Science conference >> resembles Bill Lucas's electric field concepts /media/bill/SWAPPER/Website - raw/Pandemics, health, and the Sun/Jerry Tennant 16Jun2020 Healing of [bone, muscle, skin].png https://www.slideserve.com/kateb/emf-health-the-science-or-some-of-it-but-when-will-anyone-take-any-notice Kateb Feryal ?date? EMF & Health The Science, or some of it – but when will anyone take any notice? University of Bristol ******** 17Jun2020 Web-page [updates, postings] http://www.billhowell.ca/Pandemics, health, and the Sun/_Pandemics, health, and the sun.html http://www.billhowell.ca/Pandemics, health, and the Sun/corona virus/Howell - corona virus.html http://www.billhowell.ca/Pandemics, health, and the Sun/corona virus/Howell - corona virus of countries, by region.html http://www.billhowell.ca/Pandemics, health, and the Sun/influenza/Howell - influenza virus.html http://www.billhowell.ca/Pandemics,%20health,%20and%20the%20Sun/_Pandemics,%20health,%20and%20the%20sun.html http://www.billhowell.ca/Pandemics,%20health,%20and%20the%20Sun/corona%20virus/Howell%20-%20corona%20virus.html http://www.billhowell.ca/Pandemics,%20health,%20and%20the%20Sun/corona%20virus/Howell%20-%20corona%20virus%20of%20countries,%20by%20region.html http://www.billhowell.ca/Pandemics,%20health,%20and%20the%20Sun/influenza/Howell%20-%20influenza%20virus.html 18Jun2020 posted the 3 web-pages as is ******** 11Jun2020 Sacha Dobler 2018 "Solar History: The Connection of Solar Activity, War, Peace and the Human Mind in the 2nd Millennium" ISBN: 1730722873 https://www.amazon.ca/Solar-History-Connection-Activity-Millennium-ebook/dp/B07JQJTF6C/ref=sr_1_1?dchild=1&keywords=Sacha+Dobler+%22Solar+History%22&qid=1591938819&sr=8-1 ******** 29May2020 graph of flu versus pneumonia Sub-title : 1976-2006 CDC nchs_pneumonia_flu_annual, https://www.cdc.gov/nchs/data/series/sr_24/sr24_006.pdf 1999-2008 CDC nchs_flu_annual, https://www.cdc.gov/nchs/nvss/mortality/gmwk250f.htm 2009-2015 CDC wonder_[flu, pneumonia]_monthly, https://wonder.cdc.gov/ 2015-2020 CDC fluview_[flu, pneumonia]_weekly, https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html Only the "pneumonia_deaths" (green) are read from the right axis. All data are from the USA CDC, expressed as deaths/ 1M population/ year. Weekly data : FluView. Monthly data : Wonder. Annual data : rest https://wonder.cdc.gov/controller/datarequest/D76;jsessionid=3C5F07C998E9E6A0C39CD1930B48091C CDC Wonder influenza deaths 2009-2018 >> took a while to get the hang of it!!! nchs_flu pneumonia_flu_annual +-----+ Flu-only graph : 1942-1976 Peter Doshi analysis, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2374803/ 1999-2008 CDC nchs_flu_annual, https://www.cdc.gov/nchs/nvss/mortality/gmwk250f.htm 2009-2015 CDC wonder_flu_monthly, https://wonder.cdc.gov/ 2015-2020 CDC fluview_flu_weekly, https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html 2015-2020 CDC fluview_flu_cases, https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html Only the "flu cases" (green) are read from the right axis. All data are from the USA CDC. Weekly data : FluView. Monthly data : Wonder. Annual data : rest +-----+ Both graphs of "USA flu virus [cases, deaths] 1942-2020.ods" : Influenza deaths and cases from the US [Center for Disease Control, Natioanl Institutes of Health] 1942-1976 Peter Doshi analysis, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2374803/ 1999-2008 CDC nchs_flu_annual, https://www.cdc.gov/nchs/nvss/mortality/gmwk250f.htm 2009-2015 CDC wonder_flu_monthly, https://wonder.cdc.gov/ 2015-2020 CDC fluview_flu_weekly, https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html 2015-2020 CDC fluview_flu_cases, https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html Weekly data : FluView. Monthly data : Wonder. Annual data : rest /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA flu virus [cases, deaths] 1942-2020.jpg /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA [flu virus, pneumonia condition] deaths 1942-2020.jpg /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA flu virus [cases, deaths] 1942-2020 legend2.xcf /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA flu virus [cases, deaths] 1942-2020 graph no-[titles, legend, axis numbers].xcf /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Influenza, sunspots, Kp index, zero Kp bins 1930-2020 updated.xcf ******** 28May2020 [1976-1997, 1997-2015] influenza data Howell : it's hard to find data that separates the flu from pneumonia https://www.statista.com/statistics/184574/deaths-by-influenza-and-pneumonia-in-the-us-since-1950/ Deaths by influenza and pneumonia in the U.S. from 1950 to 2017 Influenza, or the flu, is a viral infection that is highly contagious and especially common in the winter season. Influenza is a common cause of pneumonia, although most cases of the flu do not develop into pneumonia. Pneumonia is an infection or inflammation of the lungs and is particularly deadly among young children and the elderly. search "what is the differnce between influenza and pneumonia?" flu is a viral disease, common cause of pneumonia pneumonia seems to be a chronic condition? search "is pneumonia a condition or a disease?" https://en.wikipedia.org/wiki/Pneumonia Pneumonia - Wikipedia Pneumonia is an inflammatory condition of the lung affecting primarily the small air sacs known as alveoli. Symptoms typically include some combination of productive or dry cough, chest pain, fever and difficulty breathing. The severity of the condition is variable. ... Pneumonia is usually caused by infection with viruses or bacteria and less commonly by other microorganisms, certain medications or conditions such as autoimmune diseases.[3][4] Risk factors include cystic fibrosis, chronic obstructive pulmonary disease (COPD), sickle cell disease, asthma, diabetes, heart failure, a history of smoking, a poor ability to cough (such as following a stroke), and a weak immune system.[5][7] Diagnosis is often based on symptoms and physical examination.[8] Chest X-ray, blood tests, and culture of the sputum may help confirm the diagnosis.[8] The disease may be classified by where it was acquired, such as community- or hospital-acquired or healthcare-associated pneumonia.[15] ... Pneumonia often shortens the period of suffering among those already close to death and has thus been called "the old man's friend". +-----+ 1976-1997 https://wwwn.cdc.gov/nndss/infectious-tables.html CDC Stacks Collections of Weekly Infectious Disease Tables (1951 to present) https://stacks.cdc.gov/cbrowse?parentId=cdc:49375&pid=cdc:49375 Annual reports - I want weekly if possible +--+ https://www.cdc.gov/mmwr/preview/mmwrhtml/mm5933a1.htm Estimates of Deaths Associated with Seasonal Influenza --- United States, 1976--2007 August 27, 2010 / 59(33);1057-1062 +-----+ CDC search "1980 113 leading causes of death" https://www.cdc.gov/nchs/data/nvsr/nvsr50/nvsr50_15.pdf >> 2000 I already had this 07Jan1992 advance report 1989 influenza all 1593 scan - manual extraction 29Feb1996 Advance Report of Final Mortality Statistics, 1993 10 leading, pools flu & pneumonia https://www.cdc.gov/nchs/data/series/sr_24/sr24_006.pdf Advance reports, 1989 & 1990 pools flu & pneumonia BINGO!!! by [type of flu, age group] >> Howell : this pools [flu, pneumonia] TABLE 1. Estimated number of annual influenza-associated deaths with underlying pneumonia and influenza causes*, by age group --- United States, 1976--77 through 2006--07 influenza seasons Season Prominent influenza type/subtype† <19 yrs 19--64 yrs ≥65 yrs Overall No. (95% CI§) No. (95% CI) No. (95% CI) No. (95% CI) 1976--77 B / A(H3N2) 155 (85--488) 485 (357--958) 2,126 (1,847--3,013) 2,766 (2,289--4,459) 1977--78 A(H3N2) / A(H1N1) 234 (171--458) 771 (671--1,139) 3,889 (3,668--4,610) 4,894 (4,510--6,207) 1978--79 A(H1N1) 128 (86--343) 235 (159--530) 673 (511--1,327) 1,036 (756--2,200) 1979--80 B 100 (65--280) 336 (270--594) 1,706 (1,530--2,321) 2,142 (1,865--3,195) 1980--81 A(H3N2) / A(H1N1) 115 (78--284) 483 (411--715) 3,054 (2,878--3,650) 3,652 (3,367--4,649) 1981--82 B / A(H1N1) 41 (18--155) 173 (112--402) 903 (746--1,490) 1,117 (876--2,047) 1982--83 A(H3N2) 114 (78--222) 621 (512--859) 4,393 (4,091--5,035) 5,128 (4,681--6,116) 1983--84 A(H1N1) / B 123 (78--241) 466 (343--735) 2,548 (2,168--3,279) 3,137 (2,589--4,255) 1984--85 A(H3N2) 130 (100--217) 805 (743--1,056) 6,663 (6,459--7,363) 7,598 (7,302--8,636) 1985--86 B / A(H3N2) 88 (52--172) 487 (388--728) 3,607 (3,328--4,313) 4,182 (3,768--5,213) 1986--87 A(H1N1) 70 (47--167) 186 (127--454) 705 (510--1,478) 961 (684--2,099) 1987--88 A(H3N2) 75 (44--144) 509 (425--729) 4,375 (4,087--5,017) 4,959 (4,556--5,890) 1988--89 B / A(H1N1) 120 (71--212) 536 (391--798) 3,559 (3,095--4,331) 4,215 (3,557--5,341) 1989--90 A(H3N2) 91 (65--158) 662 (581--888) 6,158 (5,882--6,857) 6,911 (6,528--7,903) 1990--91 B 56 (35--123) 363 (284--598) 2,907 (2,624--3,659) 3,326 (2,943--4,380) 1991--92 A (H3N2) / A(H1N1) 82 (53--158) 592 (496--833) 5,494 (5,151--6,269) 6,168 (5,700--7,260) 1992--93 B / A(H3N2) 88 (57--164) 638 (533--913) 5,673 (5,290--6,587) 6,399 (5,880--7,664) 1993--94 A (H3N2) 77 (63--142) 647 (592--881) 6,705 (6,491--7,535) 7,429 (7,146--8,558) 1994--95 A(H3N2) / B 71 (47--128) 599 (512--818) 5,997 (5,692--6,752) 6,667 (6,251--7,698) 1995--96 A(H1N1) / A(H3N2) 76 (38--144) 508 (377--761) 4,357 (3,877--5,236) 4,941 (4,292--6,141) 1996--97 A(H3N2) / B 97 (71--153) 857 (764--1,103) 8,719 (8,348--9,582) 9,673 (9,183--10,838) 1997--98 A(H3N2) 78 (66--141) 787 (725--1,038) 8,528 (8,271--9,405) 9,393 (9,062--10,584) 1998--99 A(H3N2) / B 85 (65--146) 854 (749--1,102) 8,716 (8,336--9,589) 9,655 (9,150--10,837) 1999--00 A(H3N2) 85 (67--159) 911 (826--1,187) 9,598 (9,242--10,540) 10,594 (10,135--11,886) 2000--01 B / A(H1N1) 67 (43--136) 482 (340--774) 3,362 (2,824--4,350) 3,911 (3,207--5,260) 2001--02 A(H3N2) 107 (80--176) 1,218 (1,086--1,535) 11,966 (11,471--13,001) 13,291 (12,637--14,712) 2002--03 B / A(H1N1) 82 (40--148) 677 (483--990) 5,097 (4,421--6,068) 5,856 (4,944--7,206) 2003--04 A(H3N2) 103 (87--184) 1,367 (1,250--1,741) 13,245 (12,777--14,422) 14,715 (14,114--16,347) 2004--05 A(H3N2) / B 115 (83--192) 1,459 (1,269--1,781) 12,872 (12,276--13,854) 14,446 (13,628--15,827) 2005--06 A(H3N2) 101 (64--193) 1,268 (1,080--1,646) 10,415 (9,782--11,449) 11,784 (10,926--13,288) 2006--07 A(H1N1) / B / A(H3N2) 67 (20--212) 657 (355--1,147) 3,906 (2,973--5,176) 4,630 (3,348--6,535) Average 97 (65--201) 666 (555--949) 5,546 (5,182--6,373) 6,309 (5,802--7,524) Minimum 41 (18--123) 173 (112--402) 673 (510--1,327) 961 (684--2,047) Maximum 234 (171--488) 1,459 (1,269--1,781) 13,245 (12,777--14,422) 14,715 (14,114--16,347) * Deaths were categorized using the International Classification of Diseases eighth revision (ICD-8), ninth revision (ICD-9), or 10th revision (ICD-10), as appropriate. † Prominent influenza type and subtype were defined as at least 20% of all isolates that were typed or subtyped in that season. § Confidence interval. +-----+ 2008-2015 https://search.cdc.gov/search/index.html?query=Multiple+cause+mortality&sitelimit=&utf8=%E2%9C%93&affiliate=cdc-main https://wwwn.cdc.gov/nndss/data-and-statistics.html https://wwwn.cdc.gov/nndss/infectious-tables.html https://www.cdc.gov/mmwr/index2018.html WONDER Weekly Tables of Infectious Diseases (1996 to present) +-----+ NYET - not useful for me 1999-2018 only? https://wonder.cdc.gov/controller/datarequest/D76;jsessionid=37CE57970AC262C37EE11030D94E8275 Underlying Cause of Death, 1999-2018 Results CDC Wonder 15 leading causes of death >> pooled influenza and pneumonia total for all years https://wonder.cdc.gov/controller/datarequest/D76;jsessionid=37CE57970AC262C37EE11030D94E8275 Underlying Cause of Death, 1999-2018 Results CDC Wonder 15 leading causes of death 1999 Influenza (J09-J11) 1,665 279,040,168 0.60 2000 Influenza (J09-J11) 1,765 281,421,906 0.63 2001 nfluenza (J09-J11) 257 284,968,955 0.09 >> This is the same as what I already have! +-----+ NYET - not useful for me National Notifiable Infectious Diseases and Conditions: United States Data Tables 1980 Reported morbidity and mortality in the United States annual summary 1979 https://stacks.cdc.gov/view/cdc/1577 Reported Deaths by year 1969-1978 does NOT include influenza!! +-----+ NYET - not useful for me Influenza surveillance reports Example : https://stacks.cdc.gov/view/cdc/288 page 2 & 3 The expected number of deaths is based on fitting weekly mortality reports for the previous 5 years (omitting epidemic weeks) to the following equation by a least squares Fourier Regression Model: ^/gamma = u +r*t + A1*cos(2*pi*t/52) + B1*sin(2*pi*t/52) + A2*cos(4*pi*t/52) + B2*sin(4*pi*t/52) >> Howell - not so good, except for clamoring about an epidemic The equation contains terms for a linear trend over time and seasonal variation. Omission of the epidemic observations of previous years prevents an artifactual inflation of the expected level during the influenza season. The epidemic threshold is calculated by multiplying the standard error of the residual by 1.65 and adding the product to the expected number. Two successive weeks of reported deaths that exceed the threshold indicate an event of epidemiological interest. Based on the equations, graphs are prepared for publication which show the number of reported deaths, expected deaths, and the epidemic threshold by week (45-47). +-----+ NYET - not useful for me Morbidity & Mortality weekly reports - don't contain influenza! https://stacks.cdc.gov/view/cdc/291 1952 https://stacks.cdc.gov/view/cdc/1574 1980 ******** 27May2020 /media/bill/SWAPPER/Climate static/Datasets/Sunspots/sunspot daily total sidc.be-silso-datafiles 1930-2020.ods /media/bill/SWAPPER/Climate static/Datasets/Sunspots/sunspot daily total 1930-2020.png full graph : /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Influenza, sunspots, Kp index, zero Kp.jpg email to Ken Tapping CDC Wonder session - didn't work, save page : https://wonder.cdc.gov/controller/saved/D76/D85F179 ********* 27May2020 upgrade references on flu [data, chart] Sub-title : Influenza cases and deaths data from US [CDC, NIH] : 1942-1976 Peter Doshi analysis, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2374803/ 1977-1997 no data shown, possibly in https://www.cdc.gov/nchs/data/dvs/dt78icd8.pdf 1999-2008 CDC NCHS-DVS, https://www.cdc.gov/nchs/nvss/mortality/gmwk250f.htm 2009-2015 CDC Wonder, https://wonder.cdc.gov/ 2015-2020 CDC FluView, https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html maybe Multiple casues of death, https://www.cdc.gov/nchs/data/dvs/dt78icd8.pdf or https://wonder.cdc.gov/wonder/help/main.html#QueryingDataSets to use logarithmic scale, zero rate values were replaced by 0.001 /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA flu virus [cases, deaths].jpg ********* 26May2020 USA flu deaths +-----+ Peter Doshi paper - section "Assessing the Impact of Influenza" In this study, I have primarily considered the relative (rather than absolute) value of recorded influenza death rate statistics, which allowed me to compare 1 influenza season (or 1 month) with another. The use of the data in this way is supported by the consistent seasonality seen year after year in the monthly recorded influenza death data, which suggests that influenza-classed deaths have a nonrandom distribution. Others have also found recorded influenza-classed deaths to be a good predictor of excess all-cause mortality.25 Nevertheless, knowing the true cause of influenza-classed deaths and developing an accurate numerical assessment of the impact of influenza-related mortality remain problematic. The CDC4 and others26 have argued that recorded influenza deaths underrepresent influenza’s true impact on mortality and have offered various statistical models to calculate “influenza-associated mortality.” Although the effort to know influenza’s true impact is important and relevant from the perspective of potential public health interventions, there are several points of concern with present modeling efforts. First, current CDC estimates of seasonal influenza-associated mortality consistently dwarf recorded influenza deaths, varying from 5 to 60 times as large. Second, the CDC’s model projects that influenzaassociated mortality rose 67% from the 1980s to the 1990s; however, over this same period, recorded influenza deaths declined 38%, as shown in Figure 3 and the table available as a supplement to the online version of this article at http://www.ajph.org. Third, there are unresolved discrepancies between various published models. For the category “influenza-associated underlying influenza and pneumonia mortality” (a statistic that describes those deaths already classified as caused by influenza or pneumonia but claimed by the CDC to be associated with influenza), the CDC’s model estimated around 6000 deaths per season between 1976–1977 and 1998–1999,4 but the model of Dushoff et al. estimated over 14000 deaths per season between 1979 and 2001.26 These problems highlight the weaknesses and inconsistencies in present estimates of influenzaassociated mortality. A related problem stemming from the confusion between influenza and ILI is the use of so-called “excess mortality” or “winter mortality” in the computation of influenza’s impact. The historical monthly influenza data presented here show that for most seasons, influenza deaths were recorded for almost every month of the year, an unlikely event considering that the circulation of influenza virus is seasonal, not year-round. It is plausible that many cases and deaths from other (i.e., noninfluenza) ILIs are being misclassified as influenza, particularly when they occur during the winter season. A portion of these deaths are probably associated with other viruses such as rhinovirus and respiratory syncytial virus, which sometimes co-circulate with influenza. Moreover, cold weather itself causes upswings in mortality even without the presence of influenza.22 Further complicating the objective of gauging influenza’s true impact on mortality is the confusion between influenza and influenza-like illnesses (ILI). Influenza is but one of scores of respiratory viruses and some bacteria that cause ILI. Without laboratory testing, influenza infection is clinically indistinguishable from other ILI.27 Official annual respiratory viral surveillance data for the seasons 1976—1977 through 1998—1999 have shown that a mean of only 12% of “influenza specimens” actually tested positive for influenza virus.4 Between 1999 and 2001, there was positive confirmation of influenza virus for fewer than 10% of deaths recorded as caused by influenza. Although this proportion has increased in recent years (14% in 2002, 23% in 2003, 18% in 2004), in the absence of testing, cause of death is still only speculative. +-----+ /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA NCHS/Leading deaths 1900-98.ods >> capture (manually) https://www.cdc.gov/nchs/data/dvs/lead1900_98.pdf https://www.cdc.gov/nchs/data/nvsr/nvsr58/nvsr58_19.pdf https://www.cdc.gov/nchs/products/vsus/ta.htm >> This webpage is key ... https://www.cdc.gov/nchs/nvss/mortality_tables.htm https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm https://www.cdc.gov/nchs/products/vsus/ta.htm Easiest - but combines pneumonia & flu, hand data entry : https://www.cdc.gov/nchs/data/dvs/lead1900_98.pdf Pneumonia (all forms) and influenza 1900 107-109,33 1947 107-109,33 1949-57 480-493 1976 470-474,480-486 1997 (480-487) https://wonder.cdc.gov/ https://www.cdc.gov/nchs/data/dvs/Record_Layout_2010.pdf Multiple casues of death https://www.cdc.gov/nchs/data/dvs/dt78icd8.pdf ********************* 25May2020 US annual flu cases +-----+ https://www.foxnews.com/media/dr-scott-jensen-cdc-coronavirus-death-guidelines Fox News Flash Published April 28 Minnesota doctor questions coronavirus death toll, claims 'influenza deaths ... have been called COVID-19' By Yael Halon | Fox News Dr. Scott Jensen, a Minnesota family physician and Republican state senator, told "The Ingraham Angle" Tuesday that the Centers for Disease Control and Prevention (CDC) guidelines for doctors to certify whether a patient has died of coronavirus are a "mess" and predicted that some fatalities initially reported to be COVID-19-related would be reclassified. "We both know," Jensen told host Laura Ingraham, "that there have been influenza deaths, influenza cases, that have been called COVID-19 [deaths] because nobody bothered to swab their throats. If you want to find out what the data is, I don't care if they're dead or alive, swab them. We can always run a test later and then actually get real information." Earlier this month, Jensen told Ingraham that under the CDC guidelines, a patient who died after being hit by a bus and tested positive for coronavirus would be listed as having presumed to have died from the virus regardless of whatever damage was caused by the bus. Jensen also gave a hypothetical example of a patient who died while suffering from influenza. If the patient was elderly and had symptoms like fever and cough a few days before passing away, the doctor explained, he would have listed "respiratory arrest" as the primary cause of death. "There's been so much garbage going in that we are going to get garbage out," Jensen said Tuesday. "Three weeks ago, you and I talked about this and we've seen since then, [in] Pennsylvania, the coroners have pushed back and said 'These aren't COVID-19 deaths,' and Pennsylvania reduces its numbers. "New York says it's going to come out and add 3,700 [coronavirus deaths] in a day," Jensen continued. "The Illinois public health director tried to define what a COVID-19 death looks like and stumbled all over herself -- made it very clear didn't she have a clue. "We've got people ... in the southeastern part of the country saying they want accountability, we’ve got California and Minnesota saying 'We're going to count only confirmed cases' ... so it's a mess," Jensen said. New data published this week by the University of Washington's Institute for Health Metrics and Evaluation (IHME) projected more than than 74,000 coronavirus-related deaths in the United States by Aug. 4, an increase of nearly 6,000 projected deaths from its latest report. Fox News' Charles Creitz contributed to this report. +-----+ https://aspe.hhs.gov/cdc-%E2%80%94-influenza-deaths-request-correction-rfc CDC — Influenza Deaths: Request for Correction (RFC) US data on influenza deaths are false and misleading. The Centers for Disease Control and Prevention (CDC) acknowledges a difference between flu death and flu associated death yet uses the terms interchangeably. Additionally, there are significant statistical incompatibilities between official estimates and national vital statistics data. Compounding these problems is a marketing of fear—a CDC communications strategy in which medical experts "predict dire outcomes" during flu seasons. The CDC website states what has become commonly accepted and widely reported in the lay and scientific press: annually "about 36 000 [Americans] die from flu" (www.cdc.gov/flu/about/disease.htm) and "influenza/pneumonia" is the seventh leading cause of death in the United States (www.cdc.gov/nchs/fastats/lcod.htm). But why are flu and pneumonia bundled together? Is the relationship so strong or unique to warrant characterizing them as a single cause of death? David Rosenthal, director of Harvard University Health Services, said, "People don't necessarily die, per se, of the [flu] virus—the viraemia. What they die of is a secondary pneumonia. So many of these pneumonias are not viral pneumonias but secondary [pneumonias]." But Dr Rosenthal agreed that the flu/pneumonia relationship was not unique. For instance, a recent study (JAMA 2004;292: 1955-60[Abstract/Free Full Text]) found that stomach acid suppressing drugs are associated with a higher risk of community acquired pneumonia, but such drugs and pneumonia are not compiled as a single statistic. CDC states that the historic 1968-9 "Hong Kong flu" pandemic killed 34 000 Americans. At the same time, CDC claims 36 000 Americans annually die from flu. What is going on? Meanwhile, according to the CDC's National Center for Health Statistics (NCHS), "influenza and pneumonia" took 62 034 lives in 2001—61 777 of which were attributed to pneumonia and 257 to flu, and in only 18 cases was flu virus positively identified. Between 1979 and 2002, NCHS data show an average 1348 flu deaths per year (range 257 to 3006). The NCHS data would be compatible with CDC mortality estimates if about half of the deaths classed by the NCHS as pneumonia were actually flu initiated secondary pneumonias. But the NCHS criteria indicate otherwise: "Cause-of-death statistics are based solely on the underlying cause of death... defined by WHO as `the disease or injury which initiated the train of events leading directly to death.'" In a written statement, CDC media relations responded to the diverse statistics: "Typically, influenza causes death when the infection leads to severe medical complications." And as most such cases "are never tested for virus infection...CDC considers these [NCHS] figures to be a very substantial undercounting of the true number of deaths from influenza. Therefore, the CDC uses indirect modelling methods to estimate the number of deaths associated with influenza." CDC's model calculated an average annual 36 155 deaths from influenza associated underlying respiratory and circulatory causes (JAMA 2003;289: 179-86[Abstract/Free Full Text]). Less than a quarter of these (8097) were described as flu or flu associated underlying pneumonia deaths. Thus the much publicised figure of 36 000 is not an estimate of yearly flu deaths, as widely reported in both the lay and scientific press, but an estimate—generated by a model—of flu-associated death. William Thompson of the CDC's National Immunization Program (NIP), and lead author of the CDC's 2003 JAMA article, explained that "influenza-associated mortality" is "a statistical association between deaths and viral data available." He said that an association does not imply an underlying cause of death: "Based on modelling, we think it's associated. I don't know that we would say that it's the underlying cause of death." Yet this stance is incompatible with the CDC assertion that the flu kills 36 000 people a year—a misrepresentation that is yet to be publicly corrected. Before 2003 CDC said that 20 000 influenza-associated deaths occurred each year. The new figure of 36 000 reported in the January 2003 JAMA paper is an estimate of influenza-associated mortality over the 1990s. Keiji Fukuda, a flu researcher and a co-author of the paper, has been quoted as offering two possible causes for this 80% increase: "One is that the number of people older than 65 is growing larger...The second possible reason is the type of virus that predominated in the 1990s [was more virulent]." However, the 65-plus population grew just 12% between 1990 and 2000. And if flu virus was truly more virulent over the 1990s, one would expect more deaths. But flu deaths recorded by the NCHS were on average 30% lower in the 1990s than the 1980s. At the 2004 "National Influenza Vaccine Summit," co-sponsored by CDC and the American Medical Association, Glen Nowak, associate director for communications at the NIP, spoke on using the media to boost demand for the vaccine. One step of a "Seven-Step `Recipe' for Generating Interest in, and Demand for, Flu (or any other) Vaccination" occurs when "medical experts and public health authorities publicly...state concern and alarm (and predict dire outcomes)—and urge influenza vaccination" (www.ama-assn.org/ama1/pub/upload/mm/36/2004_flu_nowak.pdf). Another step entails "continued reports...that influenza is causing severe illness and/or affecting lots of people, helping foster the perception that many people are susceptible to a bad case of influenza." Preceding the summit, demand had been low early into the 2003 flu season. "At that point, the manufacturers were telling us that they weren't receiving a lot of orders for vaccine for use in November or even December," recalled Dr Nowak on National Public Radio. "It really did look like we needed to do something to encourage people to get a flu shot." If flu is in fact not a major cause of death, this public relations approach is surely exaggerated. Moreover, by arbitrarily linking flu with pneumonia, current data are statistically biased. Until corrected and until unbiased statistics are developed, the chances for sound discussion and public health policy are limited. I am a pediatrician and this propaganda affects my practice directly. Kenneth Stoller International Hyperbaric Medical Association +-----+ https://www.cdc.gov/flu/weekly/ Outpatient Illness Surveillance ILINet Nationwide during week 20, 1.1% of patient visits reported through the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet) were due to influenza-like illness (ILI). This percentage is below the national baseline of 2.4%. https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html FluView - USA National, Regional, and State Level Outpatient Illness and Viral Surveillance Viral Surveillance — Data collection from both the U.S. World Health Organization (WHO) Collaborating Laboratories and National Respiratory and Enteric Virus Surveillance System (NREVSS) laboratories began during the 1997-98 season. The volume of tested specimens has greatly increased during this time due to increased participation and increased testing. During the 1997-98 season 43 state public health laboratories participated in surveillance, and by the 2004-05 season all state public health laboratories were participating in surveillance. The addition of NREVSS data during the 1997-98 season roughly doubled the amount of virologic data reported each week. The number of specimens tested and % positive rate vary by region and season based on different testing practices including triaging of specimens by the reporting labs, therefore it is not appropriate to compare the magnitude of positivity rates or the number of positive specimens between regions or seasons. The U.S. WHO and NREVSS collaborating laboratories report the total number of respiratory specimens tested and the number positive for influenza types A and B each week to CDC. Most of the U.S. WHO collaborating laboratories also report the influenza A subtype (H1 or H3) of the viruses they have isolated, but the majority of NREVSS laboratories do not report the influenza A subtype. For more information on virologic surveillance please visit:http://www.cdc.gov/flu/weekly/overview.htm#Viral Outpatient Illness Surveillance — Information on patient visits to health care providers for influenza-like illness is collected through the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). This collaborative effort between CDC, state and local health departments, and health care providers started during the 1997-98 influenza season when approximately 250 providers were enrolled. Enrollment in the system has increased over time and there were >3,000 providers enrolled during the 2010-11 season. The number and percent of patients presenting with ILI each week will vary by region and season due to many factors, including having different provider type mixes (children present with higher rates of ILI than adults, and therefore regions with a higher percentage of pediatric practices will have higher numbers of cases). Therefore it is not appropriate to compare the magnitude of the percent of visits due to ILI between regions and seasons. Baseline levels are calculated both nationally and for each region. Percentages at or above the baseline level are considered to be elevated. For more information on ILI surveillance and baselines please visit:http://www.cdc.gov/flu/weekly/overview.htm#Outpatient /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA flu cases, combined public & clinical labs 1997-2020.ods /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/USA flu cases, combined public & clinical labs 1997-2020.jpg ********* 24May2020 US annual flu cases +-----+ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2374803/ Peter Doshi May2008 Trends in Recorded Influenza Mortality: United States, 1900–2004 Am J Public Health. 2008 May; 98(5): 939–945. Objectives. I sought to describe trends in historical influenza mortality data in the United States since 1900 and compare pandemic with nonpandemic influenza seasons. Methods. I compiled a database of monthly influenza-classed death rates from official US mortality tables for the years 1900 to 2004 (1905–1909 excluded), from which I calculated adjusted influenza season (July 1–June 30) mortality rates. Results. An overall and substantial decline in influenza-classed mortality was observed during the 20th century, from an average seasonal rate of 10.2 deaths per 100 000 population in the 1940s to 0.56 per 100 000 by the 1990s. The 1918–1919 pandemic stands out as an exceptional outlier. The 1957–1958 and 1968–1969 influenza pandemic seasons, by contrast, displayed substantial overlap in both degree of mortality and timing compared with nonpandemic seasons. Conclusions. The considerable similarity in mortality seen in pandemic and non-pandemic influenza seasons challenges common beliefs about the severity of pandemic influenza. The historical decline in influenza-classed mortality rates suggests that public health and ecological factors may play a role in influenza mortality risk. Nevertheless, the actual number of influenza-attributable deaths remains in doubt. +--+ /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Peter Doshi May2008 Crude mortality, United States, 1900–2004 FIGURE 1— Crude mortality per 100000 population, by influenza season (July to June of the following year), for seasons 1900–1901 to 2003–2004 (a) and 1930–1931 to 2003–2004 (b), United States. Note. International Classification of Diseases (ICD) revision 1 was used from 1900 to 1909, revision 2 from 1910 to 1920, revision 3 from 1921 to 1929. Comparability ratios are unavailable for revisions 1 to 3. Beginning in 1930, influenza mortality rates have been adjusted for changes in ICD revisions to reflect conditions in the current ICD revision 10. +--+ /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Peter Doshi May2008 Trends in Recorded Influenza Mortality: United States, 1900–2004 FIGURE 2— Crude influenza-classed mortality per 100 000 population, by month, for 1900–2004 (a) and 1930–2004 (b), United States. Note. International Classification of Diseases (ICD) revision 1 was used from 1900 to 1909, revision 2 from 1910 to 1920, revision 3 from 1921 to 1929. Comparability ratios are unavailable for revisions 1 to 3. Beginning in 1930, influenza mortality rates have been adjusted for changes in ICD revisions to reflect conditions in the current ICD revision 10. Peter Doshi May2008 Trends in Recorded Influenza Mortality: United States, 1900–2004 Am J Public Health. 2008 May; 98(5): 939–945. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2374803/ TABLE 1 Comparison of Adjusted Influenza Death Rates for 12 Influenza Seasons: United States, 1941–1976 Peter Doshi May2008 Trends in Recorded Influenza Mortality: United States, 1900–2004 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2374803/ Influenza Deaths per 100 000 Population Season Type Mean Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 1941–1942 Nonpandemic 9.9 3.4 2.8 2.9 5.2 9.7 12.1 18.9 19.5 21.5a 12.7 7.0 3.4 1942–1943 Nonpandemic 10.8 2.7 2.5 3.7 6.9 9.1 14.8 20.9a 19.7 20.8 15.0 8.8 4.4 1943–1944 Nonpandemic 22.2 3.1 3.0 3.2 6.5 9.0 78.8 92.0a 29.4 19.4 11.9 6.6 3.5 1944–1945 Nonpandemic 7.4 2.5 2.5 2.8 5.3 7.2 11.7 14.2a 14.0 12.2 7.1 5.8 3.5 1945–1946 Nonpandemic 11.2 2.2 2.1 3.0 4.3 8.4 36.9a 34.2 19.3 11.6 5.6 4.1 2.6 1946–1947 Nonpandemic 6.9 1.3 1.4 2.0 3.2 4.0 6.7 8.7 7.0 24.0a 18.2 4.8 1.8 1952–1953 Nonpandemic 5.9 0.9 0.7 0.8 1.6 2.2 3.3 19.1 27.1a 9.4 3.5 1.7 0.8 1957–1958 Pandemic 5.4 0.6 0.8 1.7 13.1 18.8a 6.2 5.6 6.9 6.2 2.8 1.2 0.6 1959–1960 Nonpandemic 4.1 0.4 0.4 0.6 0.8 1.1 1.8 10.1 21.9a 9.4 1.9 0.9 0.4 1967–1968 Nonpandemic 2.3 0.2 0.2 0.2 0.4 0.6 3.0 17.1a 4.2 1.2 0.4 0.2 0.2 1968–1969 Pandemic 4.2 0.1 0.2 0.2 0.5 1.0 16.4 23.3a 4.8 2.6 0.9 0.4 0.2 1975–1976 Nonpandemic 3.6 0.2 0.1 0.2 0.3 0.3 0.4 0.8 12.8 22.1a 4.5 0.6 0.3 a Denotes peak monthly mortality during given season. +-----+ https://www.cdc.gov/flu/about/burden/past-seasons.html >> use hospitalisations - better assurance of ID Table 1: Estimated Influenza Disease Burden, by Season — United States, 2010-11 through 2018-19 Influenza Seasons Symptomatic Illnesses Medical Visits Hospitalizations Deaths Season Estimate 95% U I Estimate 95% U I Estimate 95% U I Estimate 95% U I 2010-2011 21,000,000 (20,000,000 – 25,000,000) 10,000,000 (9,300,000 – 12,000,000) 290,000 (270,000 – 350,000) 37,000 (32,000 – 51,000) 2011-2012 9,300,000 (8,700,000 – 12,000,000) 4,300,000 (4,000,000 – 5,600,000) 140,000 (130,000 – 190,000) 12,000 (11,000 – 23,000) 2012-2013 34,000,000 (32,000,000 – 38,000,000) 16,000,000 (15,000,000 – 18,000,000) 570,000 (530,000 – 680,000) 43,000 (37,000 – 57,000) 2013-2014 30,000,000 (28,000,000 – 33,000,000) 13,000,000 (12,000,000 – 15,000,000) 350,000 (320,000 – 390,000) 38,000 (33,000 – 50,000) 2014-2015 30,000,000 (29,000,000 – 33,000,000) 14,000,000 (13,000,000 – 16,000,000) 590,000 (540,000 – 680,000) 51,000 (44,000 – 64,000) 2015-2016 24,000,000 (20,000,000 – 33,000,000) 11,000,000 (9,000,000 – 15,000,000) 280,000 (220,000 – 480,000) 23,000 (17,000 – 35,000) 2016-2017 29,000,000 (25,000,000 – 45,000,000) 14,000,000 (11,000,000 – 23,000,000) 500,000 (380,000 – 860,000) 38,000 (29,000 – 61,000) Preliminary estimates* Estimate 95% UI Estimate 95% UI Estimate 95% UI Estimate 95% UI 2017-2018* 45,000,000 (39,000,000 – 58,000,000) 21,000,000 (18,000,000 – 27,000,000) 810,000 (620,000 – 1,400,000) 61,000 (46,000 – 95,000) 2018-2019* 35,520,883 (31,323,881, 44,995,691) 16,520,350 (14,322,767, 21,203,231) 490,561 (387,283, 766,472) 34,157 (26,339, 52,664) * Estimates from the 2017-2018 and 2018-2019 seasons are preliminary and may change as data are finalized. Table 2: Estimated rates of influenza-associated disease outcomes, per 100,000, by age group — United States, 2017-2018 influenza season Illness rate Medical visit rate Hospitalization rate Mortality rate Age group Estimate 95% Cr UI Estimate 95% Cr UI Estimate 95% Cr UI Estimate 95% Cr UI 0-4 yrs 18,448.1 (12,856.5 – 36,475.0) 12,360.2 (8,501.3 -24,596.7) 128.6 (89.6 – 254.3) 0.6 (0.0, 1.8) 5-17 yrs 13,985.6 (10,983.6 – 18,987.0) 7,272.5 (5,589.3 -9,972.2) 38.3 (30.1 – 52.1) 1.0 (0.4, 2.6) 18-49 yrs 10,469.7 ( 8,895.6 – 14,075.1) 3,873.8 (3,092.9 – 5,321.7) 58.8 (49.9 – 79.0) 2.0 (1.2, 5.0) 50-64 yrs 20,881.1 (14,828.2 – 36,378.8) 8,978.9 (6,145.3 -15,818.0) 221.4 (157.2 – 385.8) 10.6 (6.7, 25.0) 65+ yrs 11,690.6 ( 7,682.1 -23,175.5) 6,546.7 (4,207.2 -13,023.8) 1,062.8 (698.4 – 2,106.9) 100.1 (70.8, 163.7) * Uncertainty interval All estimates from the 2017-2018 influenza season are preliminary and may change as data from the season are cleaned and finalized. The model to generate burden estimates uses data on influenza testing practices at FluSurv-NET hospitals to correct for known under-detection of influenza and mortality data from the National Center for Health Statistics for estimation of deaths. The most recent estimates for the burden of influenza during 2017-2018 in Tables 1-2 above use more recent data on testing practices and mortality and are lower than those previously reported. ********* 23May2020 Historical pandemics (all) /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Kp average monthly NOAA-Potsdam 1933-2020.jpg /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Kp average monthly NOAA-Potsdam 1933-2020 Title.xcf /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Kp average monthly NOAA-Potsdam 1933-2020.jpg +-----+ https://www.history.com/topics/middle-ages/pandemics-timeline +-----+ https://thefederalist.com/2020/04/18/10-deadliest-pandemics-in-history-were-much-worse-than-coronavirus-so-far/ 10 Deadliest pandemics in historyy were much worse than coronavirus so far 18Apr2020 Dan Carpenter Dan Carpenter is a proponent of preparedness, homesteads, and modern self sufficiency. He is the founder and principal of Homestead Launch and SCP Survival. Contact him at Dan@HomesteadLaunch.com. >> nice summary Antonine Plague: Rome,165-180,?measles, smallpox, or a combination of both?,5M Plague of Justinian: Eastern Roman Empire,541-750,Yersinia pestis? (bubonic plague),30-50M Black Death (bubonic plague): Europe and Asia,1347-1351,Yersinia pestis,200M New World Smallpox: Americas,1520-1600s,variola virus/rats,56M The Great Plague of Milan: Italy,1629-1631,bubonic plague,Ferrara in northern Italy did not experience a single death from the plague because it implemented strict border controls; sanitation laws; and personal hygiene practices. The Great Plague of Milan was so deadly -it is thought to be a major contributor to the decline in power of the Republic of Venice- which had risen to prominence during the Renaissance. Cholera: India/Indonesia,1817-Present,bacterium Vibrio cholerae,95k/yr 1M total,The cholera pandemic consists of a series of smaller pandemics that have been occurring on and off since 1817. We are now within the seventh cholera pandemic. Six of the seven major cholera pandemics have originated in India. However the current pandemic originated in Indonesia. Third bubonic plague: China,1885-1950s,bacteria Yersinia pestis, 12M Spanish Flu: Unknown,1918-1920,H1N1 virus (similar to swine flu)/ originated in birds,40-50M,did not fade entirely until 750 Hong Kong Flu: China,1968-1970,Influenza A virus H3N2,1-4M,The Hong Kong flu (H3N2) originated in China and was the second-worst flu pandemic of the 20th century HIV/AIDS: Sub-Saharan Africa,1981-Present,Human immunodeficiency virus (HIV)/ chimps,23-35M,HIV is not transmitted from casual contact +-----+ https://www.visualcapitalist.com/history-of-pandemics-deadliest/ Visualizing the History of Pandemics March 14, 2020 By Nicholas LePan >> Nice table Name,Time period,Type/Pre-human host,Death toll Antonine Plague,165-180,Believed to be either smallpox or measles,5M Japanese smallpox epidemic,735-737,Variola major virus,1M Plague of Justinian,541-542,Yersinia pestis bacteria/Rats fleas,30-50M Black Death,1347-1351,Yersinia pestis bacteria/Rats fleas,200M New World Smallpox Outbreak,1520 – onwards,Variola major virus,56M Great Plague of London,1665,Yersinia pestis bacteria/Rats fleas,100,000 Italian plague,1629-1631,Yersinia pestis bacteria/Rats fleas,1M Cholera Pandemics 1-6,1817-1923,V. cholerae bacteria,1M+ Third Plague,1885,Yersinia pestis bacteria/Rats fleas,12M (China and India) Yellow Fever,Late 1800s,Virus/Mosquitoes,100k-150k (U.S.) Russian Flu,1889-1890,Believed to be H2N2 (avian origin),1M Spanish Flu,1918-1919,H1N1 virus/Pigs,40-50M Asian Flu,1957-1958,H2N2 virus,1.1M Hong Kong Flu,1968-1970,H3N2 virus,1M HIV/AIDS,1981-present,Virus/Chimpanzees,25-35M Swine Flu,2009-2010,H1N1 virus/Pigs,200,000 SARS,2002-2003,Coronavirus/Bats Civets,770 Ebola,2014-2016,Ebolavirus/Wild animals,11,000 MERS,2015-Present,Coronavirus/Bats camels,850 COVID-19,2019-Present,Coronavirus/Unknown (possibly pangolins),333.5k (Johns Hopkins University estimate as of 5:32am PT 22May2020) Note: Many of the death toll numbers listed above are best estimates based on available research. Some, such as the Plague of Justinian and Swine Flu, are subject to debate based on new evidence. +-----+ https://www.forbes.com/sites/ericmack/2020/03/16/see-how-coronavirus-compares-to-other-pandemics-through-history/#152cfca37d1e Coronavirus|103,921 views|Mar 16, 2020,05:03pm EDT See How Coronavirus Compares To Other Pandemics Through History Eric Mack I cover science and innovation and products and policies they create. /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/200316 Forbes, Eric Mack - See How Coronavirus Compares To Other Pandemics Through History.png +-----+ https://www.cdc.gov/flu/pandemic-resources/basics/past-pandemics.html Influenza (Flu) 1918 H1N1 Spanish flu 1957-58 H2N2 1968 H3N3 2009 H1N1pdm09 The (H1N1)pdm09 virus was very different from H1N1 viruses that were circulating at the time of the pandemic. Few young people had any existing immunity (as detected by antibody response) to the (H1N1)pdm09 virus, but nearly one-third of people over 60 years old had antibodies against this virus, likely from exposure to an older H1N1 virus earlier in their lives. Since the (H1N1)pdm09 virus was very different from circulating H1N1 viruses, vaccination with seasonal flu vaccines offered little cross-protection against (H1N1)pdm09 virus infection. While a monovalent (H1N1)pdm09 vaccine was produced, it was not available in large quantities until late November—after the peak of illness during the second wave had come and gone in the United States. From April 12, 2009 to April 10, 2010, CDC estimated there were 60.8 million cases (range: 43.3-89.3 million), 274,304 hospitalizations (range: 195,086-402,719), and 12,469 deaths (range: 8868-18,306) in the United States due to the (H1N1)pdm09 virus. ********* 22May2020 Geomagnetic field strength geoMagField vs globaT 1860-2000, Vukcevic.gif from SuspObs : J. E. T. Channell, L. Vigliotti 29May2019 "The Role of Geomagnetic Field Intensity in Late Quaternary Evolution of Humans and Large Mammals" Reviews of Geophysics, Volume 57, Issue 3 Plain Language Summary : The strength of Earth's magnetic field in the past, recorded by rocks and sediments, provides a proxy for past flux of ultraviolet radiation (UVR) to Earth's surface due to the role of the field in modulating stratigraphic ozone. About 40,000 years ago, mammalian fossils in Australia and Eurasia record an important die‐off of large mammals that included Neanderthals in Europe. In the Americas and Europe, a large mammalian die‐off appears to have occurred ~13,000 years ago. Both die‐offs can be linked to minima in Earth's magnetic field strength implying that UVR flux variations to Earth's surface influenced mammalian evolution. For the last ~200,000 years, estimates of the timing of branching episodes in the human evolutionary tree, from modern and fossil DNA and Y chromosomes, can be linked to minima in field strength, which implies a long‐term role for UVR in human evolution. New fossil finds, improved fossil dating, knowledge of the past strength of Earth's magnetic field, and refinements in the human evolutionary tree, are sharpening the focus on a possible link between UVR arriving at the Earth's surface, magnetic field strength, and events in mammalian evolution. Suspicious Observers - Space Weather and Health video ********* 22May2020 Mar2018 overlap of NOAA & Potsdam 1. remove the month from Potsdam "music", save as : /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Kp data daily Potsdam Mar2018, music.txt 2. compare results for Mar2018 - see "Kp data check NOAA-Potsdam Mar2018.ods" >> all values are the same, so the equivalence of the data is confirmed Export image /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Kp_bins by3hr NOAA-Potsdam 1933-2020.jpg ********* 21May2020 zero-Kp days - links # loaddefs link d_Qndfs 'Kp geomag index - translate data files [NOAA, Potsdam].ndf' https://www.gfz-potsdam.de/en/kp-index/ ftp://ftp.ngdc.noaa.gov/STP/GEOMAGNETIC_DATA/INDICES/KP_AP/MONTHLY.DAT >> very different format, missing sunspots etc? >> This is Ap ONLY!! ftp://ftp.ngdc.noaa.gov/STP/GEOMAGNETIC_DATA/INDICES/KP_AP/MONTHLY.FMT ------------------------------------------------------------------------------- FORMAT FOR MONTHLY MEANS OF SELECTED GEOMAGNETIC INDICES ------------------------------------------------------------------------------- COLUMNS FMT DESCRIPTION ------------------------------------------------------------------------------- 1- 4 I4 YEAR 5- 6 I2 MONTH 7-10 I4 Monthly mean Ap PLANETARY EQUIVALENT DAILY AMPLITUDE 11-12 2X Blank 13-16 I4 Monthly mean ap or PLANETARY EQUIVALENT AMPLITUDE for 00-03 UT. 17-20 I4 Monthly mean ap or PLANETARY EQUIVALENT AMPLITUDE for 03-06 UT. 21-24 I4 Monthly mean ap or PLANETARY EQUIVALENT AMPLITUDE for 06-09 UT. 25-28 I4 Monthly mean ap or PLANETARY EQUIVALENT AMPLITUDE for 09-12 UT. 29-32 I4 Monthly mean ap or PLANETARY EQUIVALENT AMPLITUDE for 12-15 UT. 33-36 I4 Monthly mean ap or PLANETARY EQUIVALENT AMPLITUDE for 15-18 UT. 37-40 I4 Monthly mean ap or PLANETARY EQUIVALENT AMPLITUDE for 18-21 UT. 41-44 I4 Monthly mean ap or PLANETARY EQUIVALENT AMPLITUDE for 21-24 UT. 45-50 F6.2 Monthly mean Cp or PLANETARY DAILY CHARACTER FIGURE--a qualitative estimate of overall level of magnetic activity for the day determined from the sum of the eight ap amplitudes. Cp ranges, in steps of one-tenth, from 0 (quiet) to 2.5 (highly disturbed). 51-53 I3 Monthly mean C9--a conversion of the 0-to-2.5 range of the Cp index to one digit between 0 and 9. ftp://ftp.ngdc.noaa.gov/STP/GEOMAGNETIC_DATA/INDICES/KP_AP/MONTHLY.FMT save in : /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Pandemics, Kp, sunspot data 2019-20.txt After copying 1932-2018 daily tables, I need last two years! Must go to German source : https://www.gfz-potsdam.de/en/kp-index/ Definitive Kp Index and derived indices since 1932 ftp://ftp.gfz-potsdam.de/pub/home/obs/kp-ap/ ftp://ftp.gfz-potsdam.de/pub/home/obs/kp-ap/tab/ tab/: Subdirectory. Contains the monthly Kp/ap tables in a simple text format readable for both humans and computers (*.tab). The file tab_fmt.txt provides a format description. The tables distributed by regular mail (PostScript format) are also provided in this directory ftp://ftp.gfz-potsdam.de/pub/home/obs/kp-ap/tab/tab_fmt.txt The table begins with the daily lines Column Format Description ====== ====== =========== 1- 2 i2 yy, last two digits of year 3- 4 i2 mm, month (1-12) 5- 6 i2 dd, day of month (1-31) 8-19 4a3 3-hourly Kp indices, first 4 values 21-32 4a3 3-hourly Kp indices, last 4 values 35-38 a4 Daily Kp sum (supplied only for tradition, use Ap scientific purposes!) 39-42 a4 Most disturbed and quiet days; Q: most quiet days (1-10, 10th quiet day is marked Q0) D: most disturbed days (1-5) A, K: not really quiet day *: not really disturbed day 43-45 i3 Ap index 46-50 f5.2 Cp geomagnetic index. Either one line or four lines follow the daily lines 1. This line contains the monthly mean values for Ap and Cp 1- 2 i2 yy, last two digits of year 3- 4 i2 mm, month (1-12) 5- 6 i2 day is blank, may be read as zero 39-42 a4 "Mean", denotes monthly mean average of Ap and Cp 43-45 i3 Ap index (monthly mean) 46-50 f5.2 Cp geomagnetic index (monthly mean). Lines 2-4 in monthly distribution only 2. Empty line 3. This line contains the ordered most quiet days 1- 2 i2 yy, last two digits of year 3- 4 i2 mm, month (1-12) 5- 6 a2 " Q" 7-46 10a4 most quiet days 1 to 10 (day of month) A, K: not really quiet day 4. This line contains the ordered most disturbed days 1- 2 i2 yy, last two digits of year 3- 4 i2 mm, month (1-12) 5- 6 a2 " D" 7-26 5a4 most disturbed days 1 to 5 (day of month) *: not really disturbed day Accumulate data in : /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Pandemics, Kp data 2018-20 Potsdam.txt image : /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Pandemics, Kp data 2018-20 Potsdam.txt /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Pandemics, sunspots, Kp +-----+ ftp://ftp.ngdc.noaa.gov/STP/GEOMAGNETIC_DATA/INDICES/KP_AP/kp_ap.fmt describes data files ftp://ftp.swpc.noaa.gov/pub/indices/old_indices/ >> historical! >> pain in the ass to process! https://www.ngdc.noaa.gov/stp/GEOMAG/image/aastar07.jpg NOAA - AA geomagnetic index, annual number of days >=60 1868-2007.jpg NOAA - Sunspots and AA geomagnetic index, annual averages 1868-1992.gif Better data source https://www.ngdc.noaa.gov/geomag/indices/indices.html ftp://ftp.ngdc.noaa.gov/STP/GEOMAGNETIC_DATA/INDICES/KP_AP/ : save in : /media/bill/SWAPPER/Projects - mini/Pandemics, Kp index, sunspots/Pandemics, Kp, sunspot data 1932-2020 dailyy.txt >> I "melded" 2015 F5.1 data from : into : >> after that, no more F5.1??? (did Penticton shut down?) FORMAT FOR RECORDS OF SELECTED GEOMAGNETIC AND SOLAR ACTIVITY INDICES ------------------------------------------------------------------------------- COLUMNS FMT DESCRIPTION ------------------------------------------------------------------------------- 1- 2 I2 YEAR 3- 4 I2 MONTH 5- 6 I2 DAY 7-10 I4 BARTELS SOLAR ROTATION NUMBER--a sequence of 27-day intervals counted continuously from February 8, 1832. 11-12 I2 NUMBER OF DAY within the Bartels 27-day cycle. 13-14 I2 Kp or PLANETARY 3-HOUR RANGE INDEX for 0000 - 0300 UT. 15-16 I2 Kp or PLANETARY 3-HOUR RANGE INDEX for 0300 - 0600 UT. 17-18 I2 Kp or PLANETARY 3-HOUR RANGE INDEX for 0600 - 0900 UT. 19-20 I2 Kp or PLANETARY 3-HOUR RANGE INDEX for 0900 - 1200 UT. 21-22 I2 Kp or PLANETARY 3-HOUR RANGE INDEX for 1200 - 1500 UT. 23-24 I2 Kp or PLANETARY 3-HOUR RANGE INDEX for 1500 - 1800 UT. 25-26 I2 Kp or PLANETARY 3-HOUR RANGE INDEX for 1800 - 2100 UT. 27-28 I2 Kp or PLANETARY 3-HOUR RANGE INDEX for 2100 - 2400 UT. 29-31 I3 SUM of the eight Kp indices for the day expressed to the near- est third of a unit. 32-34 I3 ap or PLANETARY EQUIVALENT AMPLITUDE for 0000 - 0300 UT. 35-37 I3 ap or PLANETARY EQUIVALENT AMPLITUDE for 0300 - 0600 UT. 38-40 I3 ap or PLANETARY EQUIVALENT AMPLITUDE for 0600 - 0900 UT. 41-43 I3 ap or PLANETARY EQUIVALENT AMPLITUDE for 0900 - 1200 UT. 44-46 I3 ap or PLANETARY EQUIVALENT AMPLITUDE for 1200 - 1500 UT. 47-49 I3 ap or PLANETARY EQUIVALENT AMPLITUDE for 1500 - 1800 UT. 50-52 I3 ap or PLANETARY EQUIVALENT AMPLITUDE for 1800 - 2100 UT. 53-55 I3 ap or PLANETARY EQUIVALENT AMPLITUDE for 2100 - 2400 UT. 56-58 I3 Ap or PLANETARY EQUIVALENT DAILY AMPLITUDE--the arithmetic mean of the day's eight ap values. 59-61 F3.1 Cp or PLANETARY DAILY CHARACTER FIGURE--a qualitative estimate of overall level of magnetic activity for the day determined from the sum of the eight ap amplitudes. Cp ranges, in steps of one-tenth, from 0 (quiet) to 2.5 (highly disturbed). 62-62 I1 C9--a conversion of the 0-to-2.5 range of the Cp index to one digit between 0 and 9. 63-65 I3 INTERNATIONAL SUNSPOT NUMBER. Records contain the Zurich num- ber through December 31, 1980, and the International Brus- sels number thereafter. 66-70 F5.1 OTTAWA 10.7-CM SOLAR RADIO FLUX ADJUSTED TO 1 AU--measured at 1700 UT daily and expressed in units of 10 to the -22 Watts/ meter sq/hertz. Observations began on February 14, 1947. From that date through December 31, 1973, the fluxes given here don't reflect the revisions Ottawa made in 1966. NOTE: If a solar radio burst is in progress during the observation the pre-noon or afternoon value is used (as indicated by a flux qualifier value of 1 in column 71. 71-71 I1 FLUX QUALIFIER. "0" indicates flux required no adjustment; "1" indicates flux required adjustment for burst in progress at time of measurement; "2" indicates a flux approximated by either interpolation or extrapolation; and "3" indicates no observation. -------------------------------------------------------------------------------