"The battle against the Covid-19 Pandemic that is being waged by the United States is not over. And the battle against the Covid-19 Pandemic being waged by each state will not be over when individual states get tired of the battle. The battle will be over when the battle is won, when this horrible disease has claimed its last victim."
SEE MY ESSAY ON THE RELAXATION OF TEXAS AND MISSISSIPPI COVID-19 RULES BELOW.
SEE MY ESSAY ON THE RELAXATION OF TEXAS AND MISSISSIPPI COVID-19 RULES BELOW.
NOTE: UPDATES OF THIS PAGE ARE PRESENTLY INCOMPLETE. PLEASE CHECK BACK ON SATURDAY 4/10/21 OR WHEN THIS NOTE IS REMOVED.
THIS PAGE REPRESENTS A FRESH APPROACH TO COVID-19 DATA.
IT'S THE DATA COMPILATION - AND ROUGH DRAFTS - FOR MY FUTURE WRITING ON THE PANDEMIC.
BUT, FOR NOW, IT'S A FREE RESOURCE FOR STUDENTS, TEACHERS, PARENTS, AND WRITERS.
I HAVE DECADES OF EXPERIENCE COLLECTING AND ANALYZING DATA,
AND I DO A NEW COVID-19 DATA RUN EVERY SATURDAY MORNING.
MY ANALYSES ARE FOCUSED ON THE NUMBERS OF CV-19 DEATHS AND THE DEATH-RATES IN EACH
JURISDICTION, BECAUSE THOSE STATISTICS ARE MUCH MORE RELIABLE THAN CASE COUNTS.
MY USUAL SOURCE IS:
https://www.worldometers.info/coronavirus
PROCESSING AND UPLOADING THE DATA USUALLY TAKES ABOUT A WEEK,
UNLESS THERE HAVE BEEN MAJOR DATA SHIFTS THAT REQUIRE A REWRITE.
LIKE NOW.
NOTE: Like all the pages on this site, this page is a "work in progress" with text and data being added all the time.
It's offered as a free research aid for students and as an information source for parents, teachers, and writers.
Best wishes to all, and I hope it helps.
HOTTEST TOPIC:
RELAXATION OF TEXAS AND MISSISSIPPI COVID-19 RULES A POTENTIAL DISASTER FOR ALL AMERICA
I. Background.
Over the last two weeks, the Governors of the US states of Texas and Mississippi have announced the termination of all statewide Covid-19 restrictions applying to individuals, organizations, and businesses within their states. The reasons given were the lessening of the impact of the disease within their states along with the increased availability of anti-Covid-19 vaccines.
II. Conclusions.
The impact of Covid-19, as measured by the current - and previous - numbers of CV-19 deaths and death-rates within Texas and Mississippi, is now growing rather than receding. Therefore:
A. Any lessening of Covid-19 restrictions within those states is unwarranted;
B. If allowed to proceed, that lessening will likely result in increased deaths within those states; and
C. If allowed to proceed, that lessening presents a broader danger to the United Sates as a whole.
III. Facts.
A. Death-Rates.
Covid-19 death-rates, in the states of Texas and Mississippi are already too high and they are trending still higher. The number of deaths-per-million residents (DPMs) is the typical population-adjusted statistic used by analysts in comparing the relative impact of the Covid-19 Pandemic between jurisdictions. I have published a map each week for the last eighteen weeks showing the current death-rates in each of the US states using data published in:
www.worldometers.info/coronavirus/country/us/
Additionally, I have published another map each week for the last twelve weeks showing the percentage increase in death-rates for each state over the previous six weeks.
My most current published maps are below, and they show that the Covid-19 death-rate in Texas increased from 1,114 to 1,508 deaths-per-million residents, an increase of 35.37%, over just the six weeks ending on 2/27/2021, while the Covid-19 death-rate in Mississippi increased from 1,818 to 2,241 over the same six weeks, an increase of 23.27%. I will also note that the upward trend in both states is continuing, with the Texas CV-19 death-rate increasing from 1,508 to 1,561 and the Mississippi death-rate increasing from 2,241 to 2,287 from 2/27/21 to 3/6/2021.
Placing those death-rates in a worldwide context, if you think of Texas and Mississippi as independent nations and compare them to other nations having populations larger than some micro-nations listed in the table of nations on this page,
www.worldometers.info/coronavirus/
you will find that the Covid-19 death-rate for Texas is merely bad, while the death-rate for Mississippi is about 14% worse than the worst national death-rate in the world.
RELAXATION OF TEXAS AND MISSISSIPPI COVID-19 RULES A POTENTIAL DISASTER FOR ALL AMERICA
I. Background.
Over the last two weeks, the Governors of the US states of Texas and Mississippi have announced the termination of all statewide Covid-19 restrictions applying to individuals, organizations, and businesses within their states. The reasons given were the lessening of the impact of the disease within their states along with the increased availability of anti-Covid-19 vaccines.
II. Conclusions.
The impact of Covid-19, as measured by the current - and previous - numbers of CV-19 deaths and death-rates within Texas and Mississippi, is now growing rather than receding. Therefore:
A. Any lessening of Covid-19 restrictions within those states is unwarranted;
B. If allowed to proceed, that lessening will likely result in increased deaths within those states; and
C. If allowed to proceed, that lessening presents a broader danger to the United Sates as a whole.
III. Facts.
A. Death-Rates.
Covid-19 death-rates, in the states of Texas and Mississippi are already too high and they are trending still higher. The number of deaths-per-million residents (DPMs) is the typical population-adjusted statistic used by analysts in comparing the relative impact of the Covid-19 Pandemic between jurisdictions. I have published a map each week for the last eighteen weeks showing the current death-rates in each of the US states using data published in:
www.worldometers.info/coronavirus/country/us/
Additionally, I have published another map each week for the last twelve weeks showing the percentage increase in death-rates for each state over the previous six weeks.
My most current published maps are below, and they show that the Covid-19 death-rate in Texas increased from 1,114 to 1,508 deaths-per-million residents, an increase of 35.37%, over just the six weeks ending on 2/27/2021, while the Covid-19 death-rate in Mississippi increased from 1,818 to 2,241 over the same six weeks, an increase of 23.27%. I will also note that the upward trend in both states is continuing, with the Texas CV-19 death-rate increasing from 1,508 to 1,561 and the Mississippi death-rate increasing from 2,241 to 2,287 from 2/27/21 to 3/6/2021.
Placing those death-rates in a worldwide context, if you think of Texas and Mississippi as independent nations and compare them to other nations having populations larger than some micro-nations listed in the table of nations on this page,
www.worldometers.info/coronavirus/
you will find that the Covid-19 death-rate for Texas is merely bad, while the death-rate for Mississippi is about 14% worse than the worst national death-rate in the world.
| map_of_us_dpms_by_states_2-27-21.pdf |
| map_of_us_6-week_deaths_2-27-21.pdf |
B. Deaths-per-Day
Both Texas and Mississippi are now also experiencing increases in their numbers of Covid-19 deaths-per-day. As measured by the 7-Day Moving Averages of daily CV-19 deaths in each state, both states endured a mini-surge in CV-19 deaths during December, January, and February - probably as the result of the Holidays. But each state has begun a new surge in daily deaths over the last three weeks.
Texas entered December with an average of 125 Covid-19 deaths-per-day for the week ending 12/1/2020. Then its number of CV-19 deaths-per-day peaked at 343 for the week ending 1/26/2021, but fell to an interim low average of 129 deaths-per-day for the week ending 2/20/2021. Since then, however, the average number of new CV-19 deaths-per-day in Texas has gone up from 129 to 188, an increase of 45.7%, for the week ending 3/10/2021.
Mississippi, with its much smaller population, began with an average of 15 CV-19 deaths-per-day for the week ending 12/1/2020. Its number of CV-19 deaths-per-day peaked at 51 for the week ending 1/17/2021, but fell to an interim low average of 10 deaths-per-day for the week ending 2/23/2021. But, since then, the average number of new CV-19 deaths-per-day in Mississippi has gone up from 10 to 15, an increase of 50%, for the week ending 3/10/2021.
I should note that my source for the all these statistics is worldometers.info, and you can check my work on these two pages:
www.worldometers.info/coronavirus/usa/texas/
And:
www.worldometers.info/coronavirus/usa/mississippi/
Just scroll down to the graph labeled "Daily Deaths", then take the bumps out of the statistical road by clicking the "7-Day Moving Average" button, and you can use your cursor - or fingers - to choose any 7-day period during the whole Pandemic.
IV. Summary
The battle against the Covid-19 Pandemic that is being waged by the United States is not over. And the battle against the Covid-19 Pandemic being waged by each state will not be over when individual states get tired of the battle. The battle will be over when the battle is won, when this horrible disease has claimed its last victim.
The recent actions of Texas and Mississippi will harm the other states. Texas and Mississippi will become magnets for the travel of other persons - especially college students on Spring Break - who have grown tired of the battle. Those persons will be further exposed to the disease - perhaps even new variants of the disease - and then those persons will return to home or school to potentially infect others.
Therefore, realizing that we are all in this together, the United States as a nation, along with all the other states individually, should act as one to see the recent actions of Texas and Mississippi reversed.
Both Texas and Mississippi are now also experiencing increases in their numbers of Covid-19 deaths-per-day. As measured by the 7-Day Moving Averages of daily CV-19 deaths in each state, both states endured a mini-surge in CV-19 deaths during December, January, and February - probably as the result of the Holidays. But each state has begun a new surge in daily deaths over the last three weeks.
Texas entered December with an average of 125 Covid-19 deaths-per-day for the week ending 12/1/2020. Then its number of CV-19 deaths-per-day peaked at 343 for the week ending 1/26/2021, but fell to an interim low average of 129 deaths-per-day for the week ending 2/20/2021. Since then, however, the average number of new CV-19 deaths-per-day in Texas has gone up from 129 to 188, an increase of 45.7%, for the week ending 3/10/2021.
Mississippi, with its much smaller population, began with an average of 15 CV-19 deaths-per-day for the week ending 12/1/2020. Its number of CV-19 deaths-per-day peaked at 51 for the week ending 1/17/2021, but fell to an interim low average of 10 deaths-per-day for the week ending 2/23/2021. But, since then, the average number of new CV-19 deaths-per-day in Mississippi has gone up from 10 to 15, an increase of 50%, for the week ending 3/10/2021.
I should note that my source for the all these statistics is worldometers.info, and you can check my work on these two pages:
www.worldometers.info/coronavirus/usa/texas/
And:
www.worldometers.info/coronavirus/usa/mississippi/
Just scroll down to the graph labeled "Daily Deaths", then take the bumps out of the statistical road by clicking the "7-Day Moving Average" button, and you can use your cursor - or fingers - to choose any 7-day period during the whole Pandemic.
IV. Summary
The battle against the Covid-19 Pandemic that is being waged by the United States is not over. And the battle against the Covid-19 Pandemic being waged by each state will not be over when individual states get tired of the battle. The battle will be over when the battle is won, when this horrible disease has claimed its last victim.
The recent actions of Texas and Mississippi will harm the other states. Texas and Mississippi will become magnets for the travel of other persons - especially college students on Spring Break - who have grown tired of the battle. Those persons will be further exposed to the disease - perhaps even new variants of the disease - and then those persons will return to home or school to potentially infect others.
Therefore, realizing that we are all in this together, the United States as a nation, along with all the other states individually, should act as one to see the recent actions of Texas and Mississippi reversed.
HOT TOPICS NOW:
1. THE MEDIA ARE CONTINUING TO CONCENTRATE ON INCREASES IN COVID-19 CASES WHILE MISSING THE REAL STORY WORLDWIDE. THE STRENGTH OF A PANDEMIC ISN'T "SCORED" ON THE BASIS OF CASES - BECAUSE, FOR INSTANCE, 98% OF INDIVIDUAL CV-19 CASES RECOVER - PANDEMICS ARE SCORED ON THE BASIS OF DEATHS. AND THE USUAL MEASURE , ONE THAT LEVELS THE PLAYING FIELD BY CORRECTING FOR POPULATION SIZE, IS A DEATH-RATE STATISTIC, THE NUMBER OF DEATHS-PER-MILLION RESIDENTS OF THE JURISDICTION. I CALL THEM "DPMs", AND I THINK THAT MOST ANALYSTS WOULD CALL A NATIONAL DPM VALUE OF 1,000 A HORRIBLE RESULT IN OUR CURRENT PANDEMIC.
SO, HOW DOES THE UNITED STATES COMPARE TO ALL THE COUNTRIES ON ALL THE WORLD'S
CONTINENTS IN COVID-19 DEATH-RATES RIGHT NOW?
ON 3/27/2021 HERE WERE THE RESULTS PUBLISHED IN: www.worldometers.info/coronavirus/
(FOR CURRENT RESULTS, CLICK EACH CONTINENT'S TAB IN THE TABLE OF COUNTRIES.)
OCEANIA: 12 COUNTRIES LISTED. NONE OVER 1,000 DPMs. FRENCH POLYNESIA HIGHEST AT 500.
(NEW ZEALAND = 5 DPMs; AUSTRALIA = 35)
AFRICA: 57 COUNTRIES LISTED. NONE OVER 1,000 DPMs. SOUTH AFRICA HIGHEST AT 879.
(TUNISIA = 729 DPMs; LIBYA = 375; EGYPT = 114; KENYA = 39; GHANA = 23; NIGERIA = 10)
SOUTH AMERICA: 14 COUNTRIES LISTED. SIX OVER 1,000 DPMs. NONE OVER 2,000.
(PERU = 1,532 DPMs; BRAZIL = 1,438; COLUMBIA = 1,222; ARGENTINA = 1,214; CHILE = 1,178;
BOLIVIA = 1,030).
ASIA: 49 COUNTRIES LISTED. ONE OVER 1,000 (ARMENIA 1,163). NONE OVER 2,000.
(IRAN = 735 DPMs; ISRAEL = 670; PALESTINE = 493; TURKEY = 362; INDIA = 116; JAPAN = 71;
SOUTH KOREA = 34; CHINA = 3; VIETNAM AND TAIWAN BOTH = .4 DPMs)
EUROPE: 48 COUNTRIES LISTED. AMONG COUNTRIES WITH POPULATIONS ABOVE 100,000 THERE
WERE 22 COUNTRIES BETWEEN 1,000 & 2,000 DPMs; AND TWO OVER 2,000 (HUNGARY = 2,048;
AND CZECHIA = 2,404). CZECHIA NOW HAS THE WORLD'S WORST NATIONAL CV-19 DEATH-RATE.
NORTH AMERICA: 39 COUNTRIES LISTED. 3 OVER 1,000 (USA 1,688; MEXICO 1,546; PANAMA 1,395).
NO NATIONAL DEATH-RATES ABOVE 2,000 DPMs.
BUT, CONSIDERING THE INDIVIDUAL UNITED "STATES" AS IF THEY WERE SEPARATE NATIONS:
USA. 50 STATES AND THE DISTRICT OF COLUMBIA. ONLY 8 STATES UNDER 1,000 DPMs. 33 FROM
1,000 TO 2,000. AND 10 OVER 2,000 - WITH FOUR OF THEM HAVING HIGHER DEATH-RATES THAN
CZECHIA'S 2,404 - MAKING THEIR DEATH-RATES WORSE THAN "THE WORST IN THE WORLD."
HERE'S THE LIST OF THE WORLD'S WORST:
NEW JERSEY = 2,742; NEW YORK = 2,578; MASSACHUSETTS = 2,474; RHODE ISLAND = 2,462.
AND HERE ARE THE OTHER STATES ABOVE 2,000 DPMs:
MISSISSIPPI = 2,352; ARIZONA = 2,322; CONNECTICUT = 2,206; SOUTH DAKOTA = 2,179;
LOUISIANA = 2,170; AND ALABAMA = 2,147.
AND, ON THE SAME TOPIC, THE FIVE BOROUGHS THAT MAKE UP NEW YORK CITY CURRENTLY
HAVE A COMBINED CV-19 DEATH-RATE OF 3,650 DEATHS-PER-MILLION, WHERE MANHATTAN =
2,556; STATEN ISLAND = 3,324; BROOKLYN = 3,682; QUEENS = 4,017; AND THE BRONX = 4,284.
OBVIOUSLY, AMERICAN PERFORMANCE IN MANY STATES DURING THE PANDEMIC HAS BEEN HORRIBLE, BUT THIS FACT RAISES A QUESTION:
WHY DO TOP GOVERNMENT AND HEALTHCARE OFFICIALS IN THE USA AND IN THE STATES WITH THE WORLD'S HIGHEST CV-19 DEATH-RATES STILL HAVE THEIR JOBS?
I CONSIDER THAT QUESTION IN PART 4 OF "FIRST THE GOOD NEWS" BELOW.
2. THE MEDIA ARE ALSO CONTINUING TO MISS THE BLOWOUT OF CV-19 DEATHS AND DEATH-RATES IN MOST EUROPEAN COUNTRIES - RADIATING OUT FROM THE NATIONS HIT HARDEST BY THE "FIRST SURGE" OF THE PANDEMIC, AND FROM EAST TO WEST ACROSS THE UNITED STATES. SEE MAPS AND TEXT BELOW.
3. CONGRATULATIONS ARE IN ORDER FOR THE UNITED KINGDOM. ON 1/23/2021, THE SEVEN-DAY MOVING AVERAGE OF DAILY COVID-19 DEATHS IN THE UK REACHED ITS "SECOND SURGE" PEAK, AN AVERAGE OF 1,248 DEATHS PER DAY FOR THE PRECEDING WEEK. BUT JUST NINE WEEKS LATER, ON 3/27/21, THE UK HAD CUT ITS AVERAGE DAILY CV-19 DEATHS BY 94 % TO JUST 69. WOW!
THAT DEATH-RATE IS STILL WAY HIGHER THAN THE AVERAGE OF SEVEN DEATHS-PER-DAY THAT THE UK ACHIEVED FOR THE WEEK ENDING 9/2/2020, AT THE VERY END OF THE FIRST SURGE, BUT BRITAIN HAS MADE WONDERFUL PROGRESS TOWARD GETTING TO ZERO. IT'S ESPECIALLY IMPRESSIVE THAT THE UK HAS ACHIEVED THIS SUCCESS AS THE NEW "KENT VARIANT" FLOURISHED.
BRAVO!
1. THE MEDIA ARE CONTINUING TO CONCENTRATE ON INCREASES IN COVID-19 CASES WHILE MISSING THE REAL STORY WORLDWIDE. THE STRENGTH OF A PANDEMIC ISN'T "SCORED" ON THE BASIS OF CASES - BECAUSE, FOR INSTANCE, 98% OF INDIVIDUAL CV-19 CASES RECOVER - PANDEMICS ARE SCORED ON THE BASIS OF DEATHS. AND THE USUAL MEASURE , ONE THAT LEVELS THE PLAYING FIELD BY CORRECTING FOR POPULATION SIZE, IS A DEATH-RATE STATISTIC, THE NUMBER OF DEATHS-PER-MILLION RESIDENTS OF THE JURISDICTION. I CALL THEM "DPMs", AND I THINK THAT MOST ANALYSTS WOULD CALL A NATIONAL DPM VALUE OF 1,000 A HORRIBLE RESULT IN OUR CURRENT PANDEMIC.
SO, HOW DOES THE UNITED STATES COMPARE TO ALL THE COUNTRIES ON ALL THE WORLD'S
CONTINENTS IN COVID-19 DEATH-RATES RIGHT NOW?
ON 3/27/2021 HERE WERE THE RESULTS PUBLISHED IN: www.worldometers.info/coronavirus/
(FOR CURRENT RESULTS, CLICK EACH CONTINENT'S TAB IN THE TABLE OF COUNTRIES.)
OCEANIA: 12 COUNTRIES LISTED. NONE OVER 1,000 DPMs. FRENCH POLYNESIA HIGHEST AT 500.
(NEW ZEALAND = 5 DPMs; AUSTRALIA = 35)
AFRICA: 57 COUNTRIES LISTED. NONE OVER 1,000 DPMs. SOUTH AFRICA HIGHEST AT 879.
(TUNISIA = 729 DPMs; LIBYA = 375; EGYPT = 114; KENYA = 39; GHANA = 23; NIGERIA = 10)
SOUTH AMERICA: 14 COUNTRIES LISTED. SIX OVER 1,000 DPMs. NONE OVER 2,000.
(PERU = 1,532 DPMs; BRAZIL = 1,438; COLUMBIA = 1,222; ARGENTINA = 1,214; CHILE = 1,178;
BOLIVIA = 1,030).
ASIA: 49 COUNTRIES LISTED. ONE OVER 1,000 (ARMENIA 1,163). NONE OVER 2,000.
(IRAN = 735 DPMs; ISRAEL = 670; PALESTINE = 493; TURKEY = 362; INDIA = 116; JAPAN = 71;
SOUTH KOREA = 34; CHINA = 3; VIETNAM AND TAIWAN BOTH = .4 DPMs)
EUROPE: 48 COUNTRIES LISTED. AMONG COUNTRIES WITH POPULATIONS ABOVE 100,000 THERE
WERE 22 COUNTRIES BETWEEN 1,000 & 2,000 DPMs; AND TWO OVER 2,000 (HUNGARY = 2,048;
AND CZECHIA = 2,404). CZECHIA NOW HAS THE WORLD'S WORST NATIONAL CV-19 DEATH-RATE.
NORTH AMERICA: 39 COUNTRIES LISTED. 3 OVER 1,000 (USA 1,688; MEXICO 1,546; PANAMA 1,395).
NO NATIONAL DEATH-RATES ABOVE 2,000 DPMs.
BUT, CONSIDERING THE INDIVIDUAL UNITED "STATES" AS IF THEY WERE SEPARATE NATIONS:
USA. 50 STATES AND THE DISTRICT OF COLUMBIA. ONLY 8 STATES UNDER 1,000 DPMs. 33 FROM
1,000 TO 2,000. AND 10 OVER 2,000 - WITH FOUR OF THEM HAVING HIGHER DEATH-RATES THAN
CZECHIA'S 2,404 - MAKING THEIR DEATH-RATES WORSE THAN "THE WORST IN THE WORLD."
HERE'S THE LIST OF THE WORLD'S WORST:
NEW JERSEY = 2,742; NEW YORK = 2,578; MASSACHUSETTS = 2,474; RHODE ISLAND = 2,462.
AND HERE ARE THE OTHER STATES ABOVE 2,000 DPMs:
MISSISSIPPI = 2,352; ARIZONA = 2,322; CONNECTICUT = 2,206; SOUTH DAKOTA = 2,179;
LOUISIANA = 2,170; AND ALABAMA = 2,147.
AND, ON THE SAME TOPIC, THE FIVE BOROUGHS THAT MAKE UP NEW YORK CITY CURRENTLY
HAVE A COMBINED CV-19 DEATH-RATE OF 3,650 DEATHS-PER-MILLION, WHERE MANHATTAN =
2,556; STATEN ISLAND = 3,324; BROOKLYN = 3,682; QUEENS = 4,017; AND THE BRONX = 4,284.
OBVIOUSLY, AMERICAN PERFORMANCE IN MANY STATES DURING THE PANDEMIC HAS BEEN HORRIBLE, BUT THIS FACT RAISES A QUESTION:
WHY DO TOP GOVERNMENT AND HEALTHCARE OFFICIALS IN THE USA AND IN THE STATES WITH THE WORLD'S HIGHEST CV-19 DEATH-RATES STILL HAVE THEIR JOBS?
I CONSIDER THAT QUESTION IN PART 4 OF "FIRST THE GOOD NEWS" BELOW.
2. THE MEDIA ARE ALSO CONTINUING TO MISS THE BLOWOUT OF CV-19 DEATHS AND DEATH-RATES IN MOST EUROPEAN COUNTRIES - RADIATING OUT FROM THE NATIONS HIT HARDEST BY THE "FIRST SURGE" OF THE PANDEMIC, AND FROM EAST TO WEST ACROSS THE UNITED STATES. SEE MAPS AND TEXT BELOW.
3. CONGRATULATIONS ARE IN ORDER FOR THE UNITED KINGDOM. ON 1/23/2021, THE SEVEN-DAY MOVING AVERAGE OF DAILY COVID-19 DEATHS IN THE UK REACHED ITS "SECOND SURGE" PEAK, AN AVERAGE OF 1,248 DEATHS PER DAY FOR THE PRECEDING WEEK. BUT JUST NINE WEEKS LATER, ON 3/27/21, THE UK HAD CUT ITS AVERAGE DAILY CV-19 DEATHS BY 94 % TO JUST 69. WOW!
THAT DEATH-RATE IS STILL WAY HIGHER THAN THE AVERAGE OF SEVEN DEATHS-PER-DAY THAT THE UK ACHIEVED FOR THE WEEK ENDING 9/2/2020, AT THE VERY END OF THE FIRST SURGE, BUT BRITAIN HAS MADE WONDERFUL PROGRESS TOWARD GETTING TO ZERO. IT'S ESPECIALLY IMPRESSIVE THAT THE UK HAS ACHIEVED THIS SUCCESS AS THE NEW "KENT VARIANT" FLOURISHED.
BRAVO!
AND, IF YOU'D LIKE TO SEE HOW BRITAIN IS DOING TODAY, CHECK:
www.worldometers.info/coronavirus/country/uk/
THEN SCROLL DOWN TO THE "DAILY DEATHS" GRAPH AND CLICK "7-DAY MOVING AVERAGE", A TOOL USED BY ANALYSTS TO TAKE THE BUMPS OUT OF THE STATISTICAL ROAD. THEN, BY MOVING YOUR CURSOR OR FINGERS, YOU CAN CHOOSE ANY 7-DAY PERIOD.
4. CHINA HAD NO ADDITIONAL CV-19 DEATHS IN THE NINE MONTHS FROM LAST APRIL UNTIL 1/13/2021 WHEN IT LOST ONE MORE. THEN CHINA LOST ANOTHER THE NEXT WEEK, GOING FROM 4,634 TO 4,636 TOTAL CV-19 DEATHS FOR THE ENTIRE PANDEMIC. FOR COMPARISON, THE U.S. LOST 9,794 IN NEW CV-19 DEATHS IN THE WEEK ENDING 3/13/21, WHICH WAS MORE THAN TWICE CHINA'S TOTAL FOR THE WHOLE PANDEMIC, AND TOTAL U.S. CV-19 DEATHS WERE 545,592 AS OF 3/13, MORE THAN 117 TIMES HIGHER THAN CHINA'S 4,636.
www.worldometers.info/coronavirus/country/uk/
THEN SCROLL DOWN TO THE "DAILY DEATHS" GRAPH AND CLICK "7-DAY MOVING AVERAGE", A TOOL USED BY ANALYSTS TO TAKE THE BUMPS OUT OF THE STATISTICAL ROAD. THEN, BY MOVING YOUR CURSOR OR FINGERS, YOU CAN CHOOSE ANY 7-DAY PERIOD.
4. CHINA HAD NO ADDITIONAL CV-19 DEATHS IN THE NINE MONTHS FROM LAST APRIL UNTIL 1/13/2021 WHEN IT LOST ONE MORE. THEN CHINA LOST ANOTHER THE NEXT WEEK, GOING FROM 4,634 TO 4,636 TOTAL CV-19 DEATHS FOR THE ENTIRE PANDEMIC. FOR COMPARISON, THE U.S. LOST 9,794 IN NEW CV-19 DEATHS IN THE WEEK ENDING 3/13/21, WHICH WAS MORE THAN TWICE CHINA'S TOTAL FOR THE WHOLE PANDEMIC, AND TOTAL U.S. CV-19 DEATHS WERE 545,592 AS OF 3/13, MORE THAN 117 TIMES HIGHER THAN CHINA'S 4,636.
Much of the United States is still mired in the Second Wave of the Novel Coronavirus Pandemic of 2019. The disastrous effect of the First Wave varied throughout the United States, however, let's remember that there are no "national" Covid-19 cases, sicknesses, and deaths. There are only local cases, sicknesses, and deaths - those happening in our communities or in other communities like ours. And let's also remember that the right number of Covid-19 cases, sicknesses, and deaths in any of our communities is zero.
So, let's be vigilant, and let's follow the instructions of our local health authorities to help our communities...
GET TO ZERO!
TOP TOPICS FOR THE WEEK OF MARCH 27, 2021
Uploads and updates for 3/27/21 are in process. Maps and data first, and then text. Sorry for the delay.
FIRST THE GOOD NEWS
I. EXEMPLARY NEW ZEALAND
Thus far in this whole Pandemic, New Zealand's Covid-19 death-rate, as measured in deaths-per-million residents, is a paltry five. That's 2 DPMs higher than China's 3 DPMs and equal to Singapore's 5 DPMs. For purposes of comparison and remembering that DPMs are automatically adjusted for population size, that means that the US total of 1,575 DPMs as of last week was 315 times higher than New Zealand's five.
Additionally, New Zealand has had only one Covid-19 death since September 16th, while the US had suffered 333,340 more CV-19 deaths from 9/16/2020 till my 3/6/2021 data report. To see how New Zealand is doing today, open this page and scroll down to the Daily Deaths graph. It automatically updates.
www.worldometers.info/coronavirus/country/new-zealand/
II. EXEMPLARY NEW JERSEY AND CONNECTICUT? WELL, SORT OF...
New Jersey and Connecticut are two of the states in the US Northeast - along with New York, Massachusetts, Rhode Island, and Pennsylvania - that appeared to get hit early and hard by the highly lethal Covid-19 variant that initially impacted Italy. So, the death-rate statistics, as measured in deaths-per-million people, for all of those states have remained highly elevated as a result, and that points out one of the few problems with death-rate statistics.
DPMs are cumulative, so if a jurisdiction has had one death, that death affects its DPM count for the rest of the Pandemic. Now, that doesn't matter over the short haul or if heightened DPMs in a jurisdiction reflect a current problem - like the death-rate increases now coming out of Ohio, Virginia, Alabama, and California. But, as our Pandemic has lingered past six months, DPM statistics heavily based on a huge increase in CV-19 deaths in the First Surge have begun to lose relevance. They just don't reflect the current reality.
So, here's a new weekly map. It shows the percentage increase in Covid-19 death-rates (expressed in deaths-per-million people) for each of the 50 states and the District of Columbia over the last six weeks.
And, sorry, you'll probably have to download and rotate it to get a clear view.
Uploads and updates for 3/27/21 are in process. Maps and data first, and then text. Sorry for the delay.
FIRST THE GOOD NEWS
I. EXEMPLARY NEW ZEALAND
Thus far in this whole Pandemic, New Zealand's Covid-19 death-rate, as measured in deaths-per-million residents, is a paltry five. That's 2 DPMs higher than China's 3 DPMs and equal to Singapore's 5 DPMs. For purposes of comparison and remembering that DPMs are automatically adjusted for population size, that means that the US total of 1,575 DPMs as of last week was 315 times higher than New Zealand's five.
Additionally, New Zealand has had only one Covid-19 death since September 16th, while the US had suffered 333,340 more CV-19 deaths from 9/16/2020 till my 3/6/2021 data report. To see how New Zealand is doing today, open this page and scroll down to the Daily Deaths graph. It automatically updates.
www.worldometers.info/coronavirus/country/new-zealand/
II. EXEMPLARY NEW JERSEY AND CONNECTICUT? WELL, SORT OF...
New Jersey and Connecticut are two of the states in the US Northeast - along with New York, Massachusetts, Rhode Island, and Pennsylvania - that appeared to get hit early and hard by the highly lethal Covid-19 variant that initially impacted Italy. So, the death-rate statistics, as measured in deaths-per-million people, for all of those states have remained highly elevated as a result, and that points out one of the few problems with death-rate statistics.
DPMs are cumulative, so if a jurisdiction has had one death, that death affects its DPM count for the rest of the Pandemic. Now, that doesn't matter over the short haul or if heightened DPMs in a jurisdiction reflect a current problem - like the death-rate increases now coming out of Ohio, Virginia, Alabama, and California. But, as our Pandemic has lingered past six months, DPM statistics heavily based on a huge increase in CV-19 deaths in the First Surge have begun to lose relevance. They just don't reflect the current reality.
So, here's a new weekly map. It shows the percentage increase in Covid-19 death-rates (expressed in deaths-per-million people) for each of the 50 states and the District of Columbia over the last six weeks.
And, sorry, you'll probably have to download and rotate it to get a clear view.
| map_of_us_6-week_deaths_3-27-21.pdf |
I'll discuss the worst numbers on that map later, but for now let's focus on two of the best. New Jersey, which has had the highest Covid-19 death-rate of any US state thus far in the Pandemic, has had one of the the lowest increases in its death-rate over the past six weeks nationwide, just +13% , half the US national increase, and that +13% rate was matched by Connecticut.
Now, granted that a 13% increase in a number that's already too high results in a number that's even higher, but congratulations to New Jersey and Connecticut anyway. And the people of those states should realize that they're within reach of getting to zero. In fact, if you students, teachers, and journalists in NJ and CT get to work on it, I bet you'll find plenty of counties in your states that have already gotten to zero, and those counties need to be recognized.
One last thing: US Covid-19 statistics are generally shown on websites by counties, rather than cities. So, for instance, New York City does not have a separate listing in:
www.worldometers.info/coronavirus/usa/new-york/
Now, granted that a 13% increase in a number that's already too high results in a number that's even higher, but congratulations to New Jersey and Connecticut anyway. And the people of those states should realize that they're within reach of getting to zero. In fact, if you students, teachers, and journalists in NJ and CT get to work on it, I bet you'll find plenty of counties in your states that have already gotten to zero, and those counties need to be recognized.
One last thing: US Covid-19 statistics are generally shown on websites by counties, rather than cities. So, for instance, New York City does not have a separate listing in:
www.worldometers.info/coronavirus/usa/new-york/
Instead, the five boroughs that make up New York City are listed individually by their county names. The county names of the boroughs match their common names except for Brooklyn, "Kings County", and Staten Island, "Richmond County." And you'll have to add the five county totals together to get the NYC total. I've done that for you on Page 1 of each of my 42 Weekly Reports included below along with DPM calculations for each borough.
And, as I've said, deaths-per-million is the usual population-adjusted death-rate statistic, but I've never seen DPMs calculated in lists of counties. You'll see the same thing, so you should know how to calculate DPMs.
There's probably an app, but I've found that doing them on my phone or calculator is easy as well as a good mind-focusing tool.
You'll need to know two numbers for each jurisdiction: its total CV-19 deaths to date and its population. Start by rounding the population to the nearest thousand. Then divide total deaths plus three zeros by the population minus three zeros. Then round the result to the nearest whole number, and that's your DPM for that jurisdiction right then.
With a little practice, that calculation will become second-nature to you.
And, as I've said, deaths-per-million is the usual population-adjusted death-rate statistic, but I've never seen DPMs calculated in lists of counties. You'll see the same thing, so you should know how to calculate DPMs.
There's probably an app, but I've found that doing them on my phone or calculator is easy as well as a good mind-focusing tool.
You'll need to know two numbers for each jurisdiction: its total CV-19 deaths to date and its population. Start by rounding the population to the nearest thousand. Then divide total deaths plus three zeros by the population minus three zeros. Then round the result to the nearest whole number, and that's your DPM for that jurisdiction right then.
With a little practice, that calculation will become second-nature to you.
III. SOME EXEMPLARY COUNTIES IN WASHINGTON STATE
On the topic of getting to zero, I live in Washington State, one of the eight US states with a CV-19 death-rate under 1,000 deaths-per-million, so I'm going to focus on good news coming from my state for just a minute. For the week ending on 3/6/21, twenty-three of Washington's thirty-nine counties had no increases in Covid-19 deaths for that week, and the names of those counties are highlighted in the following table:
On the topic of getting to zero, I live in Washington State, one of the eight US states with a CV-19 death-rate under 1,000 deaths-per-million, so I'm going to focus on good news coming from my state for just a minute. For the week ending on 3/6/21, twenty-three of Washington's thirty-nine counties had no increases in Covid-19 deaths for that week, and the names of those counties are highlighted in the following table:
| washington_counties_-_no_new_deaths_-_3-27-2021.pdf |
But, in addition to the twenty-three Washington counties with no CV-19 death increases last week, three counties had just one new death. That means that twenty-six of Washington's thirty-nine counties had one or fewer new Covid-19 deaths last week. Wow!
Here, special recognition is due San Juan and Wahkiakum Counties, which have still had no CV-19 deaths at all during the entire Pandemic.
Using a regional measure, the City and County of San Francisco, California has set the standard on the West Coast of America in limiting the local impact of the Covid-19 Pandemic, so I use San Francisco as my gauge in comparing jurisdictions on the US West Coast - and in Asia, for that matter.
Thankfully, fourteen of Washington's thirty-nine counties have maintained Covid-19 death-rates during the whole Pandemic that are even lower than San Francisco's exemplary 473, and I have highlighted the names of those counties in the following table:
Here, special recognition is due San Juan and Wahkiakum Counties, which have still had no CV-19 deaths at all during the entire Pandemic.
Using a regional measure, the City and County of San Francisco, California has set the standard on the West Coast of America in limiting the local impact of the Covid-19 Pandemic, so I use San Francisco as my gauge in comparing jurisdictions on the US West Coast - and in Asia, for that matter.
Thankfully, fourteen of Washington's thirty-nine counties have maintained Covid-19 death-rates during the whole Pandemic that are even lower than San Francisco's exemplary 473, and I have highlighted the names of those counties in the following table:
| washington_counties_-_less_than_sfe_-_3-27-2021.pdf |
While I'm at it, I should explain a data line toward the bottom of Page Three in each of my 42 Weekly Reports, the one labeled "Six Peninsula Counties of WA." If you make a fist with your right hand, the map of Washington looks like the back of it, with the bigger part to the right (East) and the thumb to the left (West). The Six Peninsula Counties of Washington - Clallam, Jefferson, Kitsap (where we live), Mason, Thurston, and Grays Harbor, plus the communities of Gig Harbor and the Key Peninsula - are the ones on The Thumb, meaning the ones on the Kitsap and Olympic Peninsulas (plus Bainbridge Island). So, from your perspective, we're probably way over yonder, about as far away as you can get without getting wet.
About 900,000 people live here, roughly the same population as the City and County of San Francisco, my West Coast Covid-19 Gold Standard. But our CV-19 death-rate till now in the whole Pandemic is consistently better. In fact, we're running 34% better than our San Francisco Equivalent as of 3/6/21.
I'm not trying to gloat, but I wanted to give my neighbors a pat on the back for now, and then say:
LET'S GET TO ZERO!
About 900,000 people live here, roughly the same population as the City and County of San Francisco, my West Coast Covid-19 Gold Standard. But our CV-19 death-rate till now in the whole Pandemic is consistently better. In fact, we're running 34% better than our San Francisco Equivalent as of 3/6/21.
I'm not trying to gloat, but I wanted to give my neighbors a pat on the back for now, and then say:
LET'S GET TO ZERO!
IV. YEAH, BUT EXEMPLARY SOCIALISTS?
Sorry, Europe and North America.
Socialist nations aren't fudging their numbers, the data speak for themselves, and Covid-19 death-rates over the first year of the Pandemic vastly favor Socialist nations. Here, I'm not talking about the left-leaning Social Democrats that are frequently favored in European and North American elections. The Social Democrats have proved themselves to be at least as ineffective as their Conservative brethren - just study the US and European death-rate maps below. I'm talking about the real, live, old-school Marxist/Leninists - and their successors - those that more Conservative observers like me might fairly call "Unrepentant Commies."
So, if you open the following webpage, and if you slide your cursor down the "Deaths-Per-Million" column, you'll find that your favorite nations are probably getting slammed by the Real Reds. Here goes:
www.worldometers.info/coronavirus/
Remembering that my very own US of A is currently running a death-rate of 1,612 deaths-per-million, you'll find that the DPM numbers being rung up by the the Real Reds are almost microscopic. Examples:
Lao Peoples Democratic Republic = 0 (Not that unusual, because some nations have no CV-19 deaths so far.)
Socialist Republic of Vietnam = .4 (Actual value = .3575, meaning 35.75% of one DPM)
People's Republic of China = 3 (Hubei Province/Wuhan = 77, Beijing Province = .44, and Taiwan = .42)
Republic of Cuba = 32
And while we're at it, let's include another sort-of Socialist nation the US government currently loves to hate:
Venezuela = 50
So, what are the Commies doing right and the rest of us doing wrong? I don't think it has anything to do with political ideology, and I don't think it has much to do with authoritarianism. But I do think it has a lot to do with basic patterns of governance, and I think this will be a big issue in the post-Pandemic era.
For now, ask yourselves whether your city, county, state/province, and national health officials have what I call "Uninterrupted Vertical Accountability" from the lowest level to the highest. For instance - and given that Covid-19 cases, illnesses, recoveries, and deaths are always local phenomena - if your county health officials are getting horrible CV-19 results, can their incompetence get not only themselves, but also their bosses, fired right then?
That's the way it works in China, and it seems to be working very well. That's also the way it works in all of our US military services and many of the best commercial companies - and sports teams - throughout the world. And it doesn't typically result in nastiness or evil. It typically results in increased competence and better overall results.
Let's look at New York City as an example. At the end of the First Surge - call it the Fourth of July, 2020 - if NYC were an independent country, its Covid-19 death-rate, as measured by its number of deaths-per-million residents, would have been the worst in the world by a factor of more than three times. More than three times.
So, why wasn't any major political leader fired - from the Borough Presidents, through the Mayor of the City, and even the Governor of New York State? Because the US political structure doesn't have what I called "uninterrupted vertical accountability."
Should it?
Does our social and political disorganization add value; and, if so, how much and under what circumstances?
Has our experience in the Pandemic pointed out the practical limit of American Federalism in situations like this?
Let the debate begin.
Sorry, Europe and North America.
Socialist nations aren't fudging their numbers, the data speak for themselves, and Covid-19 death-rates over the first year of the Pandemic vastly favor Socialist nations. Here, I'm not talking about the left-leaning Social Democrats that are frequently favored in European and North American elections. The Social Democrats have proved themselves to be at least as ineffective as their Conservative brethren - just study the US and European death-rate maps below. I'm talking about the real, live, old-school Marxist/Leninists - and their successors - those that more Conservative observers like me might fairly call "Unrepentant Commies."
So, if you open the following webpage, and if you slide your cursor down the "Deaths-Per-Million" column, you'll find that your favorite nations are probably getting slammed by the Real Reds. Here goes:
www.worldometers.info/coronavirus/
Remembering that my very own US of A is currently running a death-rate of 1,612 deaths-per-million, you'll find that the DPM numbers being rung up by the the Real Reds are almost microscopic. Examples:
Lao Peoples Democratic Republic = 0 (Not that unusual, because some nations have no CV-19 deaths so far.)
Socialist Republic of Vietnam = .4 (Actual value = .3575, meaning 35.75% of one DPM)
People's Republic of China = 3 (Hubei Province/Wuhan = 77, Beijing Province = .44, and Taiwan = .42)
Republic of Cuba = 32
And while we're at it, let's include another sort-of Socialist nation the US government currently loves to hate:
Venezuela = 50
So, what are the Commies doing right and the rest of us doing wrong? I don't think it has anything to do with political ideology, and I don't think it has much to do with authoritarianism. But I do think it has a lot to do with basic patterns of governance, and I think this will be a big issue in the post-Pandemic era.
For now, ask yourselves whether your city, county, state/province, and national health officials have what I call "Uninterrupted Vertical Accountability" from the lowest level to the highest. For instance - and given that Covid-19 cases, illnesses, recoveries, and deaths are always local phenomena - if your county health officials are getting horrible CV-19 results, can their incompetence get not only themselves, but also their bosses, fired right then?
That's the way it works in China, and it seems to be working very well. That's also the way it works in all of our US military services and many of the best commercial companies - and sports teams - throughout the world. And it doesn't typically result in nastiness or evil. It typically results in increased competence and better overall results.
Let's look at New York City as an example. At the end of the First Surge - call it the Fourth of July, 2020 - if NYC were an independent country, its Covid-19 death-rate, as measured by its number of deaths-per-million residents, would have been the worst in the world by a factor of more than three times. More than three times.
So, why wasn't any major political leader fired - from the Borough Presidents, through the Mayor of the City, and even the Governor of New York State? Because the US political structure doesn't have what I called "uninterrupted vertical accountability."
Should it?
Does our social and political disorganization add value; and, if so, how much and under what circumstances?
Has our experience in the Pandemic pointed out the practical limit of American Federalism in situations like this?
Let the debate begin.
NOW THE BAD NEWS
I. US COVID-19 DEATHS CONTINUE TO SOAR
US Covid-19 deaths are continuing to increase dramatically, going from 424,434 to 535,798 - an increase of 111,364 in the six weeks ending on Saturday, February 27, 2021 - a 26% increase. Over those six weeks, the US CV-19 death-rate (measured in deaths-per-million persons) increased by the same 26%, going from 1,278 to 1,612.
And here's the US national data up to Saturday, 3/6/21:
US Covid-19 deaths are continuing to increase dramatically, going from 424,434 to 535,798 - an increase of 111,364 in the six weeks ending on Saturday, February 27, 2021 - a 26% increase. Over those six weeks, the US CV-19 death-rate (measured in deaths-per-million persons) increased by the same 26%, going from 1,278 to 1,612.
And here's the US national data up to Saturday, 3/6/21:
| delta_deaths_usa_3-27-2021.pdf |
Now here's my map of US CV-19 death-rates (in deaths-per-million people) by states as of 1/23/21 plus the same map with 3/6/21 data six weeks later. They include some ugly numbers, but they also show the increase - sometimes gradual and sometimes fast - in CV-19 death-rates from East to West across the United States. Again, you'll probably have to download and rotate these maps to see them clearly.
| map_of_us_dpms_by_states_2-13-21.pdf |
| map_of_us_dpms_by_states_3-27-21.pdf |
Now, here's my current map showing the percentage change in US CV-19 death-rates by states during the six week period from 1/23/2020 till 3/6/2021:
| map_of_us_6-week_deaths_3-27-21.pdf |
For the most current data, or to zero-in on a particular state, check:
https://www.worldometers.info/coronavirus/country/us/
https://www.worldometers.info/coronavirus/country/us/
On another US-related topic, I've started comparing death-rates in the 1918 Pandemic with our current one. The 1918 death-rate in deaths-per-million was right about 6,400 (1918 Pandemic deaths about 675,000; population in 1920 about 105,000,000; then turn the crank). And dividing the final 1918 death-rate by the 2019 Pandemic death-rate each week yields a multiple that I've recorded in the right hand column of the following table:
| delta_deaths_usa_plus_3-27-2021.pdf |
So, as of last July 4, the whole 1918 Pandemic was about sixteen times more deadly than the current 2019 Pandemic in the United States. But only eight months later, 1918 was down to 3.97 times more deadly than 2019, with the differential going down by a full multiple every four or five weeks.
That's an ugly trend that illustrates the continued strength of the 2019 Pandemic.
That's an ugly trend that illustrates the continued strength of the 2019 Pandemic.
II. COVID-19 DEATH RATES BLOWING OUT IN EUROPE
The increase in European Covid-19 death statistics that I first noted three months ago, and which had become more general two weeks later, is continuing and its effects are visible across the entire continent. I've provided four maps below that illustrate the problem in the affected area. The first two maps show cumulative DPM data for the weeks ending 1/23/2020 and 3/6/2021, the third map shows the change in CV-19 death-rates in percentages in those jurisdictions for the six-week period from 1/23 till 3/6, and the last map shows European death-rates as they existed less than five months ago on 10/24/21.
Previously, I've found that changes in national deaths-per-million statistics tend to be gradual, with little change from one week to the next. However, you will see that the increase in death-rates in that last map is stunning, with one nation doubling and others almost doubling during that period.
I should note that I've been reviewing Covid-19 death statistics and doing weekly reports on them for the last forty-one weeks, and all my weekly reports are included below. When I began, the nations apparently affected by the Italian Variant of Covid-19 in Europe were few in number - just the adjoining nations of Italy, Spain, France, Belgium, and the Netherlands - along with the United Kingdom and Ireland. And their deaths-per-million residents due to Covid-19 were the only ones above 300 in all of the Eurasian Continent - with the exception of outlier Sweden, whose laissez-faire approach to the disease amounted to a self-inflicted wound. DPM totals in the remaining nations on that entire continent tended to be much, much lower - most in the two-digits, some even less.
That situation was stable until recently, but it's now changing dramatically. Take a look at these maps, and you may have to download and rotate them to see them clearly.
Here are the two cumulative DPM maps:
The increase in European Covid-19 death statistics that I first noted three months ago, and which had become more general two weeks later, is continuing and its effects are visible across the entire continent. I've provided four maps below that illustrate the problem in the affected area. The first two maps show cumulative DPM data for the weeks ending 1/23/2020 and 3/6/2021, the third map shows the change in CV-19 death-rates in percentages in those jurisdictions for the six-week period from 1/23 till 3/6, and the last map shows European death-rates as they existed less than five months ago on 10/24/21.
Previously, I've found that changes in national deaths-per-million statistics tend to be gradual, with little change from one week to the next. However, you will see that the increase in death-rates in that last map is stunning, with one nation doubling and others almost doubling during that period.
I should note that I've been reviewing Covid-19 death statistics and doing weekly reports on them for the last forty-one weeks, and all my weekly reports are included below. When I began, the nations apparently affected by the Italian Variant of Covid-19 in Europe were few in number - just the adjoining nations of Italy, Spain, France, Belgium, and the Netherlands - along with the United Kingdom and Ireland. And their deaths-per-million residents due to Covid-19 were the only ones above 300 in all of the Eurasian Continent - with the exception of outlier Sweden, whose laissez-faire approach to the disease amounted to a self-inflicted wound. DPM totals in the remaining nations on that entire continent tended to be much, much lower - most in the two-digits, some even less.
That situation was stable until recently, but it's now changing dramatically. Take a look at these maps, and you may have to download and rotate them to see them clearly.
Here are the two cumulative DPM maps:
| map_of_european_dpms_2-13-21.pdf |
| map_of_european_dpms_3-27-21.pdf |
And here's the map showing the percentage change in single-jurisdiction CV-19 death-rates in Europe over the six weeks from 1/23/21 till 3/6/2021.
| map_of_european_6-week_death_increases_3-27-21.pdf |
Now, here's the map showing European death-rates as they existed on 10/24/20.
| map_of_european_dpms_10-24-2020.pdf |
| map_of_5-month_european_dpm_increase_multiples_3-27-21.pdf |
My comments here will be focused on a comparison of some of the death-rates shown in the 3/6/21 map with some shown in the 10/24/20 map, but other glaring examples abound. So, feel free to roam the continent, making your own comparisons.
I'm going to start from the southwest by comparing Spain and Portugal. More analysis coming soon.
But I think this unfolding situation can still be stopped if the leaders of all European nations recognize the gravity of this problem and guard against further surges in infections and deaths in their countries through an increased focus on standard inter-personal safety practices along with strict and selective border controls.
III. DISAPPOINTING NEWS OUT OF CANADA UPDATED DATA COMING SOON
Sadly, the 14-to-1 East-to-West DPM ratio in Canada reflected in the table below has compressed to 6-to-1 over the last two months, mirroring the drift-down of that ratio in the United States, and meaning that correlation is now in line with the American Northeast to West Coast correlations which you'll see below in my "Versus Tables."
The main cause is more CV-19 deaths in the West where, for example, British Columbia's CV-19 deaths-per-million people has increased from 49 to 151 in just two months. Expressed in percents, British Columbia's DPMs have increased 208%, Alberta's 203%, Saskatchewan's 405%, and Manitoba's 1376%. Meanwhile the DPM ratio between Quebec and British Columbia had dropped a lot, from 14-to-1 to 6-to-1.
IV. TWO UNFORTUNATE MONTHS IN SAN MARINO
In the nine months I've been doing the research that resulted in this webpage, I've learned that there are no "national" Covid-19 cases, treatments, recoveries, or deaths. There are only local ones. And Covid-19 won't be beaten until it's beaten locally, in every community and in every nation, by people who are absolutely devoted to getting their villages, towns and cities to zero. Zero covid cases hopefully, but especially zero covid deaths.
Internationally, I've found that zero is a rare number that's tough to achieve, but two nations stood out in my research, hyper-populous China with its 1.4 billion people and little, lovable San Marino with its 34 thousand. China had not had an additional CV-19 death for seven months till 1/13/21 when it lost one more, and San Marino hadn't lost one since May 23rd. Until mid-November.
San Marino has now suffered twenty-two new losses since November 18, and I would like to offer my condolences, my prayers, and my best wishes for San Marino in its continuing struggle.
And, by the way, if - like most people - you've never even heard of San Marino, it's a former Italian city-state perched on a mountain ridge between Florence and Rimini.
And here's a link to a five-minute introduction to that lovely place by Rick Steves:
www.youtube.com/watch?v=eSqoEhWd9cM
I'm going to start from the southwest by comparing Spain and Portugal. More analysis coming soon.
But I think this unfolding situation can still be stopped if the leaders of all European nations recognize the gravity of this problem and guard against further surges in infections and deaths in their countries through an increased focus on standard inter-personal safety practices along with strict and selective border controls.
III. DISAPPOINTING NEWS OUT OF CANADA UPDATED DATA COMING SOON
Sadly, the 14-to-1 East-to-West DPM ratio in Canada reflected in the table below has compressed to 6-to-1 over the last two months, mirroring the drift-down of that ratio in the United States, and meaning that correlation is now in line with the American Northeast to West Coast correlations which you'll see below in my "Versus Tables."
The main cause is more CV-19 deaths in the West where, for example, British Columbia's CV-19 deaths-per-million people has increased from 49 to 151 in just two months. Expressed in percents, British Columbia's DPMs have increased 208%, Alberta's 203%, Saskatchewan's 405%, and Manitoba's 1376%. Meanwhile the DPM ratio between Quebec and British Columbia had dropped a lot, from 14-to-1 to 6-to-1.
IV. TWO UNFORTUNATE MONTHS IN SAN MARINO
In the nine months I've been doing the research that resulted in this webpage, I've learned that there are no "national" Covid-19 cases, treatments, recoveries, or deaths. There are only local ones. And Covid-19 won't be beaten until it's beaten locally, in every community and in every nation, by people who are absolutely devoted to getting their villages, towns and cities to zero. Zero covid cases hopefully, but especially zero covid deaths.
Internationally, I've found that zero is a rare number that's tough to achieve, but two nations stood out in my research, hyper-populous China with its 1.4 billion people and little, lovable San Marino with its 34 thousand. China had not had an additional CV-19 death for seven months till 1/13/21 when it lost one more, and San Marino hadn't lost one since May 23rd. Until mid-November.
San Marino has now suffered twenty-two new losses since November 18, and I would like to offer my condolences, my prayers, and my best wishes for San Marino in its continuing struggle.
And, by the way, if - like most people - you've never even heard of San Marino, it's a former Italian city-state perched on a mountain ridge between Florence and Rimini.
And here's a link to a five-minute introduction to that lovely place by Rick Steves:
www.youtube.com/watch?v=eSqoEhWd9cM
THIS PANDEMIC CAN ONLY BE BEATEN LOCALLY,
SO LET'S GET TO ZERO HERE AND NOW!
SO LET'S GET TO ZERO HERE AND NOW!
INTRODUCTION TO THIS WEBPAGE
I. MY PURPOSE AND MY BACKGROUND
Students, no matter what your chosen career might be now, or what it might become later, the Novel Coronavirus Pandemic of 2019 will be a major component of your study and research this year and for the rest of your lives. Whether your career is in medicine, mathematics, the social sciences, business, engineering, journalism, literature, government, sports or any other field, the 2019 Pandemic will dramatically affect all aspects of your educations as well as your entire careers in the future just as it already has this year.
My primary purpose in publishing this page is to help you students get an early handle - an unbiased handle - on the whole topic, both to help your understanding and to improve the quality of your term papers. But this page will also be read by some journalists, analysts, public health professionals, and politicians - some of whom are interested in seeing this pandemic through an unbiased lens, and the rest of whom just clicked off this page.
Those who are still here deserve a little background about me. I have a BA in Social and Behavioral Sciences from Johns Hopkins and a JD from the University of Wyoming. After I quit practicing law and returned to business in 1988, I've been steadily engaged in analyzing data for the benefit of my clients, first as a stockbroker - I was the first Edward D. Jones representative on Bainbridge Island, Washington - later as a residential and commercial real estate broker, and for the last eight years as an independent college financial aid analyst - witness this website.
So, I guess it'd be fair to say that I'm alert to the numerical differences around me, I know how to count, and I can present numerical differences in an understandable way for the benefit of my clients. As you've already seen in the rest of this site, when I see a need that can be met by research - as in developing a method for helping students like you and your parents find really affordable colleges - I dive right in and do the research necessary to get it right.
So, there's a new approach to CV-19 with a lot of data on this page, but I think we should start with some basics.
Students, no matter what your chosen career might be now, or what it might become later, the Novel Coronavirus Pandemic of 2019 will be a major component of your study and research this year and for the rest of your lives. Whether your career is in medicine, mathematics, the social sciences, business, engineering, journalism, literature, government, sports or any other field, the 2019 Pandemic will dramatically affect all aspects of your educations as well as your entire careers in the future just as it already has this year.
My primary purpose in publishing this page is to help you students get an early handle - an unbiased handle - on the whole topic, both to help your understanding and to improve the quality of your term papers. But this page will also be read by some journalists, analysts, public health professionals, and politicians - some of whom are interested in seeing this pandemic through an unbiased lens, and the rest of whom just clicked off this page.
Those who are still here deserve a little background about me. I have a BA in Social and Behavioral Sciences from Johns Hopkins and a JD from the University of Wyoming. After I quit practicing law and returned to business in 1988, I've been steadily engaged in analyzing data for the benefit of my clients, first as a stockbroker - I was the first Edward D. Jones representative on Bainbridge Island, Washington - later as a residential and commercial real estate broker, and for the last eight years as an independent college financial aid analyst - witness this website.
So, I guess it'd be fair to say that I'm alert to the numerical differences around me, I know how to count, and I can present numerical differences in an understandable way for the benefit of my clients. As you've already seen in the rest of this site, when I see a need that can be met by research - as in developing a method for helping students like you and your parents find really affordable colleges - I dive right in and do the research necessary to get it right.
So, there's a new approach to CV-19 with a lot of data on this page, but I think we should start with some basics.
II. LET'S BEGIN WITH A DOSE OF HUMILITY
Before we're too harsh and judgmental with China, the origin of the 2019 Pandemic, let's take a brief look at the origins of the 1918 Pandemic.
It's called the "Spanish Flu" of 1918, but it would be more accurate to call it the "American Flu", because it didn't originate in Spain at all. It originated here in the USA, specifically on one farm in Haskell County, Kansas. It was only called the Spanish Flu because Spain was the only Western European country that was not a belligerent in World War I, so it was also the only country with a free press at that time, a press that fully covered the horrible effects of that disease in Spain. The belligerent nations in Europe - and in the US too, since America had just entered WWI and was gearing up its war effort - censored coverage of the growing pandemic, because the leaders of those nations believed that knowing its severity would be bad for public morale and for the overall war effort.
The disease at the center of the 1918 Pandemic was a "swine flu", a viral disease that initially sickened pigs, but mutated the capacity to also sicken humans. It was also not the last swine flu the world has seen, but it might have been the nastiest. It was especially lethal for young adults between the ages of twenty and forty, frequently taking its victims from their first symptoms to their deathbeds in a single day.
A local physician in Haskell County tried to make national health officials in America aware of the severity of the disease, but he got no response. So the disease spread to the new US Army training camps in that area and from there around America. That pandemic ultimately killed about 675,000 Americans, but it didn't stay in the US. It traveled with our troops overseas, and it ultimately killed between twenty and one hundred million additional people worldwide. And, to put that number in perspective, that's roughly the number of all the civilians killed in the Second World War.
The best recent treatise on that pandemic, The Great Influenza, was written by historian and author John Barry. His book is generally available, but there's probably a line to get it at your school or city library right now. In the meantime, here's a link to a 40 minute video on the 1918 Pandemic that's mainly based on Mr. Barry's research:
www.youtube.com/watch?v=UDY5COg2P2c&t=1443s
And here's the link to the Wikipedia article on Haskell County, Kansas, which includes a brief history of the beginning of the 1918 Pandemic with an important quote on its origin from Mr. Barry's book stating his thesis: that there were no tracks of the 1918 Pandemic leading toward Haskell County, only tracks leading away.
en.wikipedia.org/wiki/Haskell_County,_Kansas
Before we're too harsh and judgmental with China, the origin of the 2019 Pandemic, let's take a brief look at the origins of the 1918 Pandemic.
It's called the "Spanish Flu" of 1918, but it would be more accurate to call it the "American Flu", because it didn't originate in Spain at all. It originated here in the USA, specifically on one farm in Haskell County, Kansas. It was only called the Spanish Flu because Spain was the only Western European country that was not a belligerent in World War I, so it was also the only country with a free press at that time, a press that fully covered the horrible effects of that disease in Spain. The belligerent nations in Europe - and in the US too, since America had just entered WWI and was gearing up its war effort - censored coverage of the growing pandemic, because the leaders of those nations believed that knowing its severity would be bad for public morale and for the overall war effort.
The disease at the center of the 1918 Pandemic was a "swine flu", a viral disease that initially sickened pigs, but mutated the capacity to also sicken humans. It was also not the last swine flu the world has seen, but it might have been the nastiest. It was especially lethal for young adults between the ages of twenty and forty, frequently taking its victims from their first symptoms to their deathbeds in a single day.
A local physician in Haskell County tried to make national health officials in America aware of the severity of the disease, but he got no response. So the disease spread to the new US Army training camps in that area and from there around America. That pandemic ultimately killed about 675,000 Americans, but it didn't stay in the US. It traveled with our troops overseas, and it ultimately killed between twenty and one hundred million additional people worldwide. And, to put that number in perspective, that's roughly the number of all the civilians killed in the Second World War.
The best recent treatise on that pandemic, The Great Influenza, was written by historian and author John Barry. His book is generally available, but there's probably a line to get it at your school or city library right now. In the meantime, here's a link to a 40 minute video on the 1918 Pandemic that's mainly based on Mr. Barry's research:
www.youtube.com/watch?v=UDY5COg2P2c&t=1443s
And here's the link to the Wikipedia article on Haskell County, Kansas, which includes a brief history of the beginning of the 1918 Pandemic with an important quote on its origin from Mr. Barry's book stating his thesis: that there were no tracks of the 1918 Pandemic leading toward Haskell County, only tracks leading away.
en.wikipedia.org/wiki/Haskell_County,_Kansas
III. A NOTE ON MY APPROACH
I fully explain my method below, but it's based on an analysis of Covid-19 death statistics gathered each Saturday morning mainly from:
https://www.worldometers.info/coronavirus/
I focus on death statistics because that's how pandemics are "scored." Of course, knowing the number of new cases is essential for policy makers in determining where the next flareup may be within a jurisdiction - meaning in a city, county, state/province or nation - and where to devote the jurisdiction's resources. But relatively few of those cases will ever result in deaths, and it's the deaths the statisticians and historians count. Look at it this way: it's great when sick people get better, but the strength of the pandemic - and how well or how poorly local jurisdictions responded to it - will be based on the number who didn't get better, the number who passed away.
I present the data I collect in two ways, first with reference to a commonly known American city/county as a gauge - the City and County of Philadelphia, Pennsylvania on the American East Coast and in Europe and the City and County of San Francisco, California on the American West Coast and in Asia. And then I include a commonly used population-adjusted statistic for each jurisdiction, its deaths per million residents.
Additionally, I try to never engage in whatever the popular American prejudices might be that week, month, year, or presidential term. For instance, I consciously treat the Chinese, Russians, and Iranians just like other people. And I'm even capable of occasionally complimenting Socialists.
Finally, I place full trust in the good faith of the people who collect the data I analyze until those people give me a verifiable reason to doubt their word. That's because I know that, if I assume bad faith in the people collecting the data I analyze, I will never know anything at all. I will only have buckets of doubt.
I fully explain my method below, but it's based on an analysis of Covid-19 death statistics gathered each Saturday morning mainly from:
https://www.worldometers.info/coronavirus/
I focus on death statistics because that's how pandemics are "scored." Of course, knowing the number of new cases is essential for policy makers in determining where the next flareup may be within a jurisdiction - meaning in a city, county, state/province or nation - and where to devote the jurisdiction's resources. But relatively few of those cases will ever result in deaths, and it's the deaths the statisticians and historians count. Look at it this way: it's great when sick people get better, but the strength of the pandemic - and how well or how poorly local jurisdictions responded to it - will be based on the number who didn't get better, the number who passed away.
I present the data I collect in two ways, first with reference to a commonly known American city/county as a gauge - the City and County of Philadelphia, Pennsylvania on the American East Coast and in Europe and the City and County of San Francisco, California on the American West Coast and in Asia. And then I include a commonly used population-adjusted statistic for each jurisdiction, its deaths per million residents.
Additionally, I try to never engage in whatever the popular American prejudices might be that week, month, year, or presidential term. For instance, I consciously treat the Chinese, Russians, and Iranians just like other people. And I'm even capable of occasionally complimenting Socialists.
Finally, I place full trust in the good faith of the people who collect the data I analyze until those people give me a verifiable reason to doubt their word. That's because I know that, if I assume bad faith in the people collecting the data I analyze, I will never know anything at all. I will only have buckets of doubt.
IV. GENERAL THESIS
A. Method and Format
As the Covid-19 Pandemic spread out of China in January and February this year, it was obvious to me that the disease being endured by Italy was a new and different variant of the CV-19 virus, that it was more than ten times more lethal than the original Wuhan Variant affecting south and east Asia, and that the reasons being given in the press for its more extreme lethality - like "It's just those kissy-huggy Italians" - seemed rather childish. And those anecdotal reasons seemed all the less scientifically valid as the Italian Variant made its way from Italy through Spain, France, Belgium, The Netherlands, and then to Great Britain.
"Those kissy-huggy Brits?" Yeah, right.
B. Tracking Gorillas
Here, I'll take a pause and mention that many of you will have careers that involve in numerical analysis, and throughout your careers you'll see plenty of "multiplier events", where the numerical difference from one event to the next is obviously in multiples - meaning several times higher or lower, and equaling several hundreds or even thousands of percent. In those cases, I think it's best to not strain to explain obvious multiplier events with "fractional factors" that may only explain ten, twenty, thirty, or forty percent of those differences. Instead, be open to the possibility that you're looking at something new.
As an example, let's say that you're a primate biologist and you live in a world where no primates have been observed that are larger than chimpanzees. But then you come across a footprint made by a large gorilla. Then you spot another footprint like the first, and then more and more of them, and all the footprints are in one forest with none in any other forest. Now, you've never heard the word "gorilla" before, and you've never actually seen these. But you've seen their footprints, so you know that gorillas exist, and you know that what differentiates their vastly increased size from the chimpanzees you've actually seen is not eating more pasta. They're just different animals. And you know how to recognize the presence of gorillas in other forests, because you know their footprints.
End of pause.
C. Back to Method and Format
Thankfully, the quality of publicly available data on Covid-19 were and are superb, so by the middle of May I had a good idea just how much more lethal the Italian Variant was when compared to the common Wuhan Variant. So, after some numerical experimentation, and based solely on its numeric footprint - the numbers of deaths per million residents it was leaving in its wake - I came to opinion that the multiplier was between ten and twenty times.
As the weeks passed, the Italian Variant spread in an arc - a "Swath" might be more descriptive - from Italy west and northwest through Spain, France, Belgium, the Netherlands, the UK, and Ireland and with some apparent effect on bordering nations - such as Portugal to the west and Switzerland, Luxembourg, Germany and Denmark to the north and east. But the effect of the Italian Variant of CV-19 was limited to just those nations, and it did not affect any other jurisdictions throughout the entirety of Eurasia then - including China itself. Here I'll note that Sweden, with its disastrous laissez-faire approach to the Pandemic, is a special case with elevated death totals as the result.
In the United States and Canada, the data were also bifurcated. The disease affecting the hardest hit states in our Northeast - meaning New Jersey, New York, Massachusetts, Connecticut, Rhode Island, and Pennsylvania - along with the Province of Quebec - had the statistical signature of the Italian Variant. While the states on our West Coast, along with the Provinces of British Columbia and the Prairie Provinces (Alberta, Saskatchewan & Manitoba), had the statistical signature of the Wuhan Variant.
A. Method and Format
As the Covid-19 Pandemic spread out of China in January and February this year, it was obvious to me that the disease being endured by Italy was a new and different variant of the CV-19 virus, that it was more than ten times more lethal than the original Wuhan Variant affecting south and east Asia, and that the reasons being given in the press for its more extreme lethality - like "It's just those kissy-huggy Italians" - seemed rather childish. And those anecdotal reasons seemed all the less scientifically valid as the Italian Variant made its way from Italy through Spain, France, Belgium, The Netherlands, and then to Great Britain.
"Those kissy-huggy Brits?" Yeah, right.
B. Tracking Gorillas
Here, I'll take a pause and mention that many of you will have careers that involve in numerical analysis, and throughout your careers you'll see plenty of "multiplier events", where the numerical difference from one event to the next is obviously in multiples - meaning several times higher or lower, and equaling several hundreds or even thousands of percent. In those cases, I think it's best to not strain to explain obvious multiplier events with "fractional factors" that may only explain ten, twenty, thirty, or forty percent of those differences. Instead, be open to the possibility that you're looking at something new.
As an example, let's say that you're a primate biologist and you live in a world where no primates have been observed that are larger than chimpanzees. But then you come across a footprint made by a large gorilla. Then you spot another footprint like the first, and then more and more of them, and all the footprints are in one forest with none in any other forest. Now, you've never heard the word "gorilla" before, and you've never actually seen these. But you've seen their footprints, so you know that gorillas exist, and you know that what differentiates their vastly increased size from the chimpanzees you've actually seen is not eating more pasta. They're just different animals. And you know how to recognize the presence of gorillas in other forests, because you know their footprints.
End of pause.
C. Back to Method and Format
Thankfully, the quality of publicly available data on Covid-19 were and are superb, so by the middle of May I had a good idea just how much more lethal the Italian Variant was when compared to the common Wuhan Variant. So, after some numerical experimentation, and based solely on its numeric footprint - the numbers of deaths per million residents it was leaving in its wake - I came to opinion that the multiplier was between ten and twenty times.
As the weeks passed, the Italian Variant spread in an arc - a "Swath" might be more descriptive - from Italy west and northwest through Spain, France, Belgium, the Netherlands, the UK, and Ireland and with some apparent effect on bordering nations - such as Portugal to the west and Switzerland, Luxembourg, Germany and Denmark to the north and east. But the effect of the Italian Variant of CV-19 was limited to just those nations, and it did not affect any other jurisdictions throughout the entirety of Eurasia then - including China itself. Here I'll note that Sweden, with its disastrous laissez-faire approach to the Pandemic, is a special case with elevated death totals as the result.
In the United States and Canada, the data were also bifurcated. The disease affecting the hardest hit states in our Northeast - meaning New Jersey, New York, Massachusetts, Connecticut, Rhode Island, and Pennsylvania - along with the Province of Quebec - had the statistical signature of the Italian Variant. While the states on our West Coast, along with the Provinces of British Columbia and the Prairie Provinces (Alberta, Saskatchewan & Manitoba), had the statistical signature of the Wuhan Variant.
IV. GENERAL MATERIALS
A. When the Pandemic Began in the United States
Covid-19 arrived on both coasts of the United States at roughly the same time with the first CV-19 deaths on neither coast predating the other. Review the next graph - you'll probably have to rotate it - and also you'll see that, over just a three-week period beginning in the middle of March 2020, 49 states and the District of Columbia had suffered their first CV-19 deaths.
A. When the Pandemic Began in the United States
Covid-19 arrived on both coasts of the United States at roughly the same time with the first CV-19 deaths on neither coast predating the other. Review the next graph - you'll probably have to rotate it - and also you'll see that, over just a three-week period beginning in the middle of March 2020, 49 states and the District of Columbia had suffered their first CV-19 deaths.
| first_us_cv-19_deaths.pdf |
NOTE: I renewed my Canadian data on 12/23, and the news wasn't good. Deaths per million people in Quebec Province had increased from 704 to 909 in the two months since 10/18/2020. That was an increase of 29%, but it still left Quebec a little better than Pennsylvania, the state with the lowest DPMs in the hard-hit American Northeast.
More interesting were the DPM increases in British Columbia and the Prairie Provinces. British Columbia's DPMs had increased 208%, Alberta's 203%, Saskatchewan's 405%, and Manitoba's 1376%. Meanwhile the DPM ratio between Quebec and British Columbia had dropped a lot, from 14-to-1 to 6-to-1. That correlation is now in line with the current American Northeast to West Coast correlations which you'll see in the "Versus Tables" below. Obviously, this is not good news for Canada, and I'll update the next text section along with its table soon.
More interesting were the DPM increases in British Columbia and the Prairie Provinces. British Columbia's DPMs had increased 208%, Alberta's 203%, Saskatchewan's 405%, and Manitoba's 1376%. Meanwhile the DPM ratio between Quebec and British Columbia had dropped a lot, from 14-to-1 to 6-to-1. That correlation is now in line with the current American Northeast to West Coast correlations which you'll see in the "Versus Tables" below. Obviously, this is not good news for Canada, and I'll update the next text section along with its table soon.
B. Tracking the "Covid Gorilla" in Canada
The differences between the effects of Italian and Wuhan Variants of Covid-19 are still most visible in Canada. Let's focus the western province of British Columbia, with its orientation toward Asia - and especially China, and Quebec, with its orientation toward Europe - and especially France. In line with the numeric footprints of the two variants that I mentioned earlier, you'll see in the next graph that the Province of Quebec's 704 deaths per million residents is more than 14 times higher than British Columbia's 49 DPMs. And remember that Canada has national healthcare, which damps out healthcare differences as a cause for that extreme differential. Again, you'll probably have to rotate this graph to see it properly, and the provinces are arrayed as you'd see them on a map, with the west on the left and the east on the right.
The differences between the effects of Italian and Wuhan Variants of Covid-19 are still most visible in Canada. Let's focus the western province of British Columbia, with its orientation toward Asia - and especially China, and Quebec, with its orientation toward Europe - and especially France. In line with the numeric footprints of the two variants that I mentioned earlier, you'll see in the next graph that the Province of Quebec's 704 deaths per million residents is more than 14 times higher than British Columbia's 49 DPMs. And remember that Canada has national healthcare, which damps out healthcare differences as a cause for that extreme differential. Again, you'll probably have to rotate this graph to see it properly, and the provinces are arrayed as you'd see them on a map, with the west on the left and the east on the right.
| canadian_dpms_by_province.pdf |
Right here is a good spot for bringing up the danger of over-generalizing your research in your articles and term papers. For instance, it's true that Quebec's 704 DPMs is a huge number in the Canadian context, and it's also true that the Province of Quebec has 62% of Canada's CV-19 deaths while only having 22.5% of Canada's total population. But you'll see in my latest weekly summaries below that, for a jurisdiction hit hard by the Italian Variant, that 704 is about the best in all of North America and compares well with the seven hardest hit nations in Western Europe. Additionally, the DPM totals for the remaining Canadian Provinces vary between good, great, and amazing.
Also, the Province of Quebec - along with the other Provinces on Canada's southern flank - is an absolutely huge place with lots of cities, and you can bet that 704 is not a common DPM among those cities or throughout all of Quebec. So, if you're doing a paper on Quebec, you'll need to use available resources to dig deeper.
New York State provides a good example of this in America. You'll see below that New York State's current death-rate (2,407 DPMs) is the second worst in its six-state area - and the second worst in the US too, by the way. But, if you substitute out the current total CV-19 deaths in New York City, and substitute in NYC's Philadelphia Equivalent, you can then recalculate New York State's death-rate with a dose of reality. Then you'll find that the New York State DPM total drops to 1,776 taking the state from the second worst in its area to the best. So, New York State's CV-19 problems weren't generalized throughout the state, they were focused in the City, and that analytical approach changes the whole history of the Pandemic there.
Oops, back to Canada for one last comment. You can see from that bar graph that a national total for Canadian DPMs, the last column on the right side of the graph, doesn't make much sense analytically. A national total acts like an average DPM value for the nation, and you can see that in a nation - like Canada - with what you could call a distinct viral dichotomy (good SAT word), you essentially have Quebec with one very large value and everybody else with a variety of very small values. So, averaging those data is really meaningless.
Also, the Province of Quebec - along with the other Provinces on Canada's southern flank - is an absolutely huge place with lots of cities, and you can bet that 704 is not a common DPM among those cities or throughout all of Quebec. So, if you're doing a paper on Quebec, you'll need to use available resources to dig deeper.
New York State provides a good example of this in America. You'll see below that New York State's current death-rate (2,407 DPMs) is the second worst in its six-state area - and the second worst in the US too, by the way. But, if you substitute out the current total CV-19 deaths in New York City, and substitute in NYC's Philadelphia Equivalent, you can then recalculate New York State's death-rate with a dose of reality. Then you'll find that the New York State DPM total drops to 1,776 taking the state from the second worst in its area to the best. So, New York State's CV-19 problems weren't generalized throughout the state, they were focused in the City, and that analytical approach changes the whole history of the Pandemic there.
Oops, back to Canada for one last comment. You can see from that bar graph that a national total for Canadian DPMs, the last column on the right side of the graph, doesn't make much sense analytically. A national total acts like an average DPM value for the nation, and you can see that in a nation - like Canada - with what you could call a distinct viral dichotomy (good SAT word), you essentially have Quebec with one very large value and everybody else with a variety of very small values. So, averaging those data is really meaningless.
V. FILES UPDATED WEEKLY
A. Delta Deaths USA
In math and science, the Greek letter "delta" - the one that looks like a triangle - is used to indicate the change in a value, and this document records the numbers - and the change in those numbers - of US Covid-19 deaths and and the US Covid-19 death-rate, measured in deaths-per-million residents (DPMs) for the week ending February 20, 2021, while comparing it with the 33 previous weeks. You'll see that, as of 2/20, the US had sustained 507,922 CV-19 deaths, an increase of 15,259 deaths from the previous week. US total deaths-per-million residents as of 2/20 were 1,529 DPMs, an increase of 46 from the previous week.
For purposes of comparison, China had sustained total of 4,636 Covid-19 deaths as of 2/20, and China had sustained only two additional CV-19 deaths over the previous seven months. Additionally, China's total deaths-per-million residents as of 2/20/21 were 3, roughly comparable to Singapore's and New Zealand's 5 DPMs each. China's DPMs were also somewhat better than South Korea (26), Japan (39), and Australia (35) while being somewhat worse than Vietnam's spectacular .4 DPMs. Here, it's interesting to note that Taiwan's .3 DPMs are one tenth of Mainland China's 3 DPMs, but remember that Taiwan didn't have Wuhan and Hubei Province increasing its death-rate. In fact, 97.4% of the PRC's CV-19 deaths (4,512 out of 4,636) occurred in Hubei Province.
I should mention here that I only started recording national CV-19 death statistics for the United States in the seventh week of this project for a good reason. Up to that point US death data looked like the graph of Canadian data above, with a big lump in the Northeast and a much smaller lump on the West Coast - 3,000 miles away. So, averaging those lumps had no analytical value.
But all American states had relaxed their CV-19 restrictions by the last week of May, 2020. Cases surged, and deaths surged about six weeks later, around the 4th of July. Essentially, the virus pattern became more mixed, the catastrophe became more national, and national data became relevant.
By the way, that point-of-inflection around the Fourth of July - where the US Northeast vs West Coast distinction began to compress - is obvious in the four "Versus Tables" below.
A. Delta Deaths USA
In math and science, the Greek letter "delta" - the one that looks like a triangle - is used to indicate the change in a value, and this document records the numbers - and the change in those numbers - of US Covid-19 deaths and and the US Covid-19 death-rate, measured in deaths-per-million residents (DPMs) for the week ending February 20, 2021, while comparing it with the 33 previous weeks. You'll see that, as of 2/20, the US had sustained 507,922 CV-19 deaths, an increase of 15,259 deaths from the previous week. US total deaths-per-million residents as of 2/20 were 1,529 DPMs, an increase of 46 from the previous week.
For purposes of comparison, China had sustained total of 4,636 Covid-19 deaths as of 2/20, and China had sustained only two additional CV-19 deaths over the previous seven months. Additionally, China's total deaths-per-million residents as of 2/20/21 were 3, roughly comparable to Singapore's and New Zealand's 5 DPMs each. China's DPMs were also somewhat better than South Korea (26), Japan (39), and Australia (35) while being somewhat worse than Vietnam's spectacular .4 DPMs. Here, it's interesting to note that Taiwan's .3 DPMs are one tenth of Mainland China's 3 DPMs, but remember that Taiwan didn't have Wuhan and Hubei Province increasing its death-rate. In fact, 97.4% of the PRC's CV-19 deaths (4,512 out of 4,636) occurred in Hubei Province.
I should mention here that I only started recording national CV-19 death statistics for the United States in the seventh week of this project for a good reason. Up to that point US death data looked like the graph of Canadian data above, with a big lump in the Northeast and a much smaller lump on the West Coast - 3,000 miles away. So, averaging those lumps had no analytical value.
But all American states had relaxed their CV-19 restrictions by the last week of May, 2020. Cases surged, and deaths surged about six weeks later, around the 4th of July. Essentially, the virus pattern became more mixed, the catastrophe became more national, and national data became relevant.
By the way, that point-of-inflection around the Fourth of July - where the US Northeast vs West Coast distinction began to compress - is obvious in the four "Versus Tables" below.
| delta_deaths_usa_3-27-2021.pdf |
And here again is a Delta Deaths table that includes a comparison of death-rates in the 1918 Pandemic with our current one. The 1918 death-rate in deaths-per-million was right about 6,400 (1918 Pandemic deaths about 675,000; population in 1920 about 105,000,000; then turn the crank). And dividing the final 1918 death-rate by the current 2019 death-rate each week yields a multiple that I've recorded in the right hand column of this table:
| delta_deaths_usa_plus_3-27-2021.pdf |
B. Tracking the "Covid Gorilla" in the United States With The "Versus Tables" (More text coming soon.)
| philadelphia_vs_san_francisco_3-27-2021.pdf |
| pennsylvania_vs_oregon_3-27-2021.pdf |
| new_york_vs_california_3-27-2021.pdf |
| new_york_vs_california_3-27-2021.pdf |
VI. DEATHS PER MILLION RESIDENTS (This section to be revised soon.)
A. DPMs in General
1. Introduction.
If you look at the list of data by nations in the worldometers.info site I mentioned above,
https://www.worldometers.info/coronavirus/
you'll find my favorite column in that table, "Deaths/1M Pop." That stands for "deaths per million people", and it gives us an accurate, population-adjusted comparison statistic with no further effort. If you're looking at that site on a phone, you'll probably have to turn your phone to "landscape" and compress the image to see that column, because it's on the right-hand side of the table.
I abbreviate "deaths per million" to DPM, and if you scroll down that column you find that the highest DPM belongs to little, lovable San Marino, a former Italian city-state on the top of a ridge between Florence and Rimini. San Marino has a tiny population of about 34,000 but it suffered 42 deaths in the initial surge of the First Wave, giving it a DPM of 1235 - the worst in the world on that list. However, as a point of reference, San Marino has not had a CV-19 death for five months - meaning it GOT TO ZERO! - so, it won't get pinged by me.
By the way, San Marino looks like a great place to visit when this thing lightens up, and here's a five-minute video by Rick Steves on that topic:
www.youtube.com/watch?v=eSqoEhWd9cM
2. Trailing Indicators
And San Marino's DPM total points out two interesting attributes about DPMs and all CV-19 death statistics, for that matter - they are all "trailing indicators", and they are all cumulative in nature. (More text coming soon.)
3. Finding And Calculating DPMs
On worldometers.info can click on any country and go to its own webpage. If you click on the United States, you'll find a table listing all the states with DPM calculations provided for each. And if you click on the individual states you will get a list of all the counties in that state, but that list will not include DPMs, so you'll have to calculate the relevant ones for yourself. You're going to make that calculation a lot, and there may be an app for it, but here's a simple method I use.
Find out the exact number of CV-19 deaths to date from the table and the population of the jurisdiction rounding that number to the nearest thousand. Then, on any calculator enter the number of deaths plus three zeros, and then divide that number by the rounded population minus the last three zeros of that number. The result will be a good approximation of that jurisdiction's death per million.
Using San Marino as an example: enter its CV-19 deaths (42) plus three zeros (42000), then divide it by its rounded population (34,000) minus three zeros (34), and the result will be its DPM (1235) plus or minus a couple of Ds. Easy.
B. European CV-19 Death-Rate Maps (Most recent map at the bottom of this section.)
| map_of_european_dpms_10-24-2020.pdf |
| map_of_european_dpms_10-31-2020.pdf |
| map_of_european_dpms_11-7-2020.pdf |
| map_of_european_dpms_11-14-2020.pdf |
| map_of_european_dpms_11-21-20.pdf |
| map_of_european_dpms_11-28-2020.pdf |
| map_of_european_dpms_12-5-20.pdf |
| map_of_european_dpms_12-12-20.pdf |
| map_of_european_dpms_12-19-20.pdf |
| map_of_european_dpms_12-26-20.pdf |
| map_of_european_dpms_1-2-21.pdf |
| map_of_european_dpms_1-9-21.pdf |
| map_of_european_dpms_1-16-21.pdf |
| map_of_european_dpms_1-23-21.pdf |
| map_of_european_dpms_1-30-21.pdf |
| map_of_european_dpms_2-6-21.pdf |
| map_of_european_dpms_2-13-21.pdf |
| map_of_european_dpms_2-20-21.pdf |
| map_of_european_dpms_2-27-21.pdf |
| map_of_european_dpms_3-6-21.pdf |
| map_of_european_dpms_3-13-21.pdf |
| map_of_european_dpms_3-20-21.pdf |
| map_of_european_dpms_3-27-21.pdf |
C. European 6-Week CV-19 Death-Rate Maps (Most recent map at the bottom of this section.)
| map_of_european_6-week_death_increases_12-5-20.pdf |
| map_of_european_6-week_death_increases_12-12-20.pdf |
| map_of_european_6-week_death_increases_12-19-20.pdf |
| map_of_european_6-week_death_increases_12-26-20.pdf |
| map_of_european_6-week_death_increases_1-2-21.pdf |
| map_of_european_6-week_death_increases_1-9-21.pdf |
| map_of_european_6-week_death_increases_1-16-21.pdf |
| map_of_european_6-week_death_increases_1-23-21.pdf |
| map_of_european_6-week_death_increases_1-30-21.pdf |
| map_of_european_6-week_death_increases_2-6-21.pdf |
| map_of_european_6-week_death_increases_2-13-21_-_2.pdf |
| map_of_european_6-week_death_increases_2-20-21_-_2.pdf |
| map_of_european_6-week_death_increases_2-27-21_-_2.pdf |
| map_of_european_6-week_death_increases_3-6-21_-_2.pdf |
| map_of_european_6-week_death_increases_3-13-21.pdf |
| map_of_european_6-week_death_increases_3-20-21.pdf |
| map_of_european_6-week_death_increases_3-27-21.pdf |
D. US CV-19 Death-Rate Maps (Most recent map at the bottom of this section.)
| map_of_us_dpms_by_states_10-24-20.pdf |
| map_of_us_dpms_by_states_10-31-20.pdf |
| map_of_us_dpms_by_states_11-7-20.pdf |
| map_of_us_dpms_by_states_11-14-20.pdf |
| map_of_us_dpms_by_states_11-21-20.pdf |
| map_of_us_dpms_by_states_11-28-20.pdf |
| map_of_us_dpms_by_states_12-5-20.pdf |
| map_of_us_dpms_by_states_12-12-20.pdf |
| map_of_us_dpms_by_states_12-19-20.pdf |
| map_of_us_dpms_by_states_12-26-20.pdf |
| map_of_us_dpms_by_states_1-2-21.pdf |
| map_of_us_dpms_by_states_1-9-21.pdf |
| map_of_us_dpms_by_states_1-16-21.pdf |
| map_of_us_dpms_by_states_1-23-21.pdf |
| map_of_us_dpms_by_states_1-30-21.pdf |
| map_of_us_dpms_by_states_2-6-21.pdf |
| map_of_us_dpms_by_states_2-13-21.pdf |
| map_of_us_dpms_by_states_2-20-21.pdf |
| map_of_us_dpms_by_states_2-27-21.pdf |
| map_of_us_dpms_by_states_3-6-21.pdf |
| map_of_us_dpms_by_states_3-13-21.pdf |
| map_of_us_dpms_by_states_3-20-21.pdf |
| map_of_us_dpms_by_states_3-27-21.pdf |
E. US 6-Week CV-19 Death-Rate Maps (Most recent map at the bottom of this section.)
| map_of_us_6-week_deaths_12-5-20.pdf |
| map_of_us_6-week_deaths_12-12-20.pdf |
| map_of_us_6-week_deaths_12-19-20.pdf |
| map_of_us_6-week_deaths_12-26-20.pdf |
| map_of_us_6-week_deaths_1-2-21.pdf |
| map_of_us_6-week_deaths_1-9-21.pdf |
| map_of_us_6-week_deaths_1-16-21.pdf |
| map_of_us_6-week_deaths_1-23-21.pdf |
| map_of_us_6-week_deaths_1-30-21.pdf |
| map_of_us_6-week_deaths_2-6-21.pdf |
| map_of_us_6-week_deaths_2-13-21.pdf |
| map_of_us_6-week_deaths_2-20-21.pdf |
| map_of_us_6-week_deaths_2-27-21.pdf |
| map_of_us_6-week_deaths_3-6-21.pdf |
| map_of_us_6-week_deaths_3-13-21.pdf |
| map_of_us_6-week_deaths_3-20-21.pdf |
| map_of_us_6-week_deaths_3-27-21.pdf |
F. Washington State CV-19 Death-Rate Data and Maps (Most recent map at the bottom of this section.)
For the week ending February 6, 2021, sixteen of Washington's thirty-nine counties had no increase in Covid-19 deaths from the previous week, and thirteen counties had lower death-rates for the entire Pandemic than the City and County of San Francisco, California, my West Coast "Gold Standard."
Hurray!
For the week ending February 6, 2021, sixteen of Washington's thirty-nine counties had no increase in Covid-19 deaths from the previous week, and thirteen counties had lower death-rates for the entire Pandemic than the City and County of San Francisco, California, my West Coast "Gold Standard."
Hurray!
| washington_county_dpms_on_11-7-2020_-_alpha_list.pdf |
| map_of_washington_county_dpms_11-7-20.pdf |
| washington_county_dpms_on_11-14-2020_-_alpha_list.pdf |
| map_of_washington_county__dpms_11-14-20.pdf |
| washington_county_dpms_on_11-21-2020_-_alpha_list.pdf |
| map_of_washington_county_dpms_11-21-20.pdf |
| washington_county_dpms_on_11-28-2020_-_alpha_list.pdf |
| map_of_washington_county_dpms_11-28-20.pdf |
| washington_county_dpms_on_12-5-2020_-_alpha_list.pdf |
| map_of_washington_county_dpms_12-5-20.pdf |
| washington_county_dpms_on_12-12-2020_-_alpha_list.pdf |
| map_of_washington_county_dpms_12-12-20.pdf |
| washington_county_dpms_on_12-19-2020_-_alpha_list.pdf |
| map_of_washington_county_dpms_12-19-20.pdf |
| washington_county_dpms_on_12-26-2020_-_alpha_list.pdf |
| map_of_washington_county_dpms_12-26-20.pdf |
| washington_county_dpms_on_1-2-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_1-2-21.pdf |
| washington_county_dpms_on_1-9-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_1-9-21.pdf |
| washington_county_dpms_on_1-16-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_1-16-21.pdf |
| washington_county_dpms_on_1-23-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_1-23-21.pdf |
| washington_county_dpms_on_1-30-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_1-30-21.pdf |
| washington_county_dpms_on_2-6-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_2-6-21.pdf |
| washington_county_dpms_on_2-13-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_2-13-21.pdf |
| washington_county_dpms_on_2-20-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_2-20-21.pdf |
| washington_county_dpms_on_2-27-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_2-27-21.pdf |
| washington_county_dpms_on_3-6-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_3-6-21.pdf |
| washington_county_dpms_on_3-13-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_3-13-21.pdf |
| washington_county_dpms_on_3-20-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_3-20-21.pdf |
| washington_county_dpms_on_3-27-2021_-_alpha_list.pdf |
| map_of_washington_county_dpms_3-27-21.pdf |
IV. MY WEEKLY COVID-19 RESEARCH REPORTS
Below are my analyses of Covid-19 death statistics for the thirty-five weeks from May 23, 2020 to February 6, 2021. To be consistent, I collect data every Saturday morning using data published on:
https://www.worldometers.info/coronavirus/.
Then I crunch the numbers over the following week, usually completing my update by the following Friday.
I picked the jurisdictions - cities, counties, states, and nations - based on their relevance and their illustrative properties. So, if your favorite jurisdiction isn't listed, please don't feel slighted. Great data are available worldwide, and you can find them all via websites like the one I use.
https://www.worldometers.info/coronavirus/.
Then I crunch the numbers over the following week, usually completing my update by the following Friday.
I picked the jurisdictions - cities, counties, states, and nations - based on their relevance and their illustrative properties. So, if your favorite jurisdiction isn't listed, please don't feel slighted. Great data are available worldwide, and you can find them all via websites like the one I use.
B. Reports
Note: In https://www.worldometers.info/coronavirus/usa/, data breakouts for the sub-jurisdictions of individual US states are by county, rather than by city. For example, in https://www.worldometers.info/coronavirus/usa/new-york/ there is no separate entry for New York City, but there are entries for each of the five boroughs (counties) that make up New York City. For clarity, I have listed the five boroughs individually by their common names along with combined totals for the entire City of New York. If you see those data listed elsewhere, remember that Brooklyn is actually Kings County and Staten Island is actually Richmond County.
Note: In https://www.worldometers.info/coronavirus/usa/, data breakouts for the sub-jurisdictions of individual US states are by county, rather than by city. For example, in https://www.worldometers.info/coronavirus/usa/new-york/ there is no separate entry for New York City, but there are entries for each of the five boroughs (counties) that make up New York City. For clarity, I have listed the five boroughs individually by their common names along with combined totals for the entire City of New York. If you see those data listed elsewhere, remember that Brooklyn is actually Kings County and Staten Island is actually Richmond County.
Week 45: Data collected on Saturday, 27 March 2021
| analysis_of_covid-19_deaths_-_27_march_2021.pdf |
Week 44: Data collected on Saturday, 20 March 2021
| analysis_of_covid-19_deaths_-_13_march_2021.pdf |
Week 43: Data collected on Saturday, 13 March 2021
| analysis_of_covid-19_deaths_-_13_march_2021.pdf |
Week 42: Data collected on Saturday, 6 March 2021
| analysis_of_covid-19_deaths_-_6_march_2021.pdf |
Week 41: Data collected on Saturday, 27 February 2021
| analysis_of_covid-19_deaths_-_27_february_2021.pdf |
Week 40: Data collected on Saturday, 20 February 2021
| analysis_of_covid-19_deaths_-_20_february_2021.pdf |
Week 39: Data collected on Saturday, 13 February 2021
| analysis_of_covid-19_deaths_-_13_february_2021.pdf |
Week 38: Data collected on Saturday, 6 February 2021
| analysis_of_covid-19_deaths_-_6_february_2021.pdf |
Week 37: Data collected on Saturday, 30 January 2021
| analysis_of_covid-19_deaths_-_30_january_2021.pdf |
Week 36: Data collected on Saturday, 23 January 2021
Note: This is the first Weekly Report where Taiwan is given its own line. See it on Page 3.
Note: This is the first Weekly Report where Taiwan is given its own line. See it on Page 3.
| analysis_of_covid-19_deaths_-_23_january_2021.pdf |
Week 35: Data collected on Saturday, 16 January 2021
| analysis_of_covid-19_deaths_-_16_january_2021.pdf |
Week 34: Data collected on Saturday, 9 January 2021
| analysis_of_covid-19_deaths_-_9_january_2021.pdf |
Week 33: Data collected on Saturday, 2 January 2021
| analysis_of_covid-19_deaths_-_2_january_2021.pdf |
Week 32: Data collected on Saturday, 26 December 2020
| analysis_of_covid-19_deaths_-_26_december_2020.pdf |
Week 31: Data collected on Saturday, 19 December 2020
| analysis_of_covid-19_deaths_-_19_december_2020.pdf |
Week 30: Data collected on Saturday, 12 December 2020
| analysis_of_covid-19_deaths_-_12_december_2020.pdf |
Week 29: Data collected on Saturday, 5 December 2020
| analysis_of_covid-19_deaths_-_5_december_2020.pdf |
Week 28: Data collected on Saturday, 28 November 2020
| analysis_of_covid-19_deaths_-_28_november_2020.pdf |
Week 27: Data collected on Saturday, 21 November 2020
| analysis_of_covid-19_deaths_-_21_november_2020.pdf |
Week 26: Data collected on Saturday, 14 November 2020
| analysis_of_covid-19_deaths_-_14_november_2020.pdf |
Week 25: Data collected on Saturday, 7 November 2020
| analysis_of_covid-19_deaths_-_7_november_2020.pdf |
Week 24: Data collected on Saturday, 31 October 2020
Note: This is the first week of a new format for my weekly summary. I think that you'll find a clearer
distinction between the Italian and Wuhan Variants in Europe and the Northeastern USA.
Note: This is the first week of a new format for my weekly summary. I think that you'll find a clearer
distinction between the Italian and Wuhan Variants in Europe and the Northeastern USA.
| analysis_of_covid-19_deaths_-_31_october_2020.pdf |
Week 23: Data collected on Saturday, 24 October 2020
| analysis_of_covid-19_deaths_-_24_october_2020.pdf |
Week 22: Data collected on Saturday, 17 October 2020
| analysis_of_covid-19_deaths_-_17_october_2020.pdf |
Week 21: Data collected on Saturday, 10 October 2020
| analysis_of_covid-19_deaths_-_10_october_2020.pdf |
Week 20: Data collected on Saturday, 3 October 2020
| analysis_of_covid-19_deaths_-_3_october_2020.pdf |
Week 19: Data collected on Saturday, 26 September 2020
| analysis_of_covid-19_deaths_-_26_september_2020.pdf |
Week 18: Data collected on Saturday, 19 September 2020
| analysis_of_covid-19_deaths_-_19_september_2020.pdf |
Week 17: Data collected on Saturday, 12 September 2020
| analysis_of_covid-19_deaths_-_12_september_2020.pdf |
Week 16: Data collected on Saturday, 5 September 2020
| analysis_of_covid-19_deaths_-_5_september_2020.pdf |
Week 15: Data collected on Saturday, 29 August 2020
| analysis_of_covid-19_deaths_-_29_august_2020.pdf |
Week 14: Data collected on Saturday, 22 August 2020
| analysis_of_covid-19_deaths_-_22_august_2020.pdf |
Week 13: Data collected on Saturday, 15 August 2020
| analysis_of_covid-19_deaths_-_15_august_2020.pdf |
Week 12: Data collected on Saturday, 8 August 2020
| analysis_of_covid-19_deaths_-_8_august_2020.pdf |
Week 11: Data collected on Saturday, 1 August 2020
| analysis_of_covid-19_deaths_-_1_august_2020.pdf |
Week 10: Data collected on Saturday, 25 July 2020
| analysis_of_covid-19_deaths_-_25_july_2020.pdf |
Week 9: Data collected on Saturday, 18 July 2020
| analysis_of_covid-19_deaths_-_18_july_2020.pdf |
Week 8: Data collected on Saturday, 11 July 2020
| analysis_of_covid-19_deaths_-_11_july_2020.pdf |
Week 7: Data collected on Saturday, 4 July 2020
| analysis_of_covid-19_deaths_-_4_july_2020.pdf |
Week 6: Data collected on Saturday, 27 June 2020
| analysis_of_covid-19_deaths_-_27_june_2020.pdf |
Week 5: Data collected on Saturday, 20 June 2020
| analysis_of_covid-19_deaths_-_20_june_2020.pdf |
Week 4: Data collected on Saturday, 13 June 2020
| analysis_of_covid-19_deaths_-_13_june_2020.pdf |
Week 3: Data collected on Saturday, 6 June 2020
| analysis_of_covid-19_deaths_-_6_june_2020.pdf |
Week 2: Data collected on Saturday, 30 May 2020
| analysis_of_covid-19_deaths_-_30_may_2020.pdf |
Week 1: Data collected on Saturday, 23 May 2020
| analysis_of_covid-19_deaths_-_23_may_2020-2.pdf |
Copyright 2021, Mark Warns, All Rights Reserved
As on every page of the ACG website, here are Word versions of my Apple-to-Apples templates for finding out - before you ever apply to any college anywhere - your expected college costs and loans. There's also a Word version of my blank data input pages that you can download for use by your own family. Follow the instructions on each form, and they're all you really need to find affordable colleges.
| acg_apples-to-apples_stabilized_net_cost_comparison.docx |
| acg_apples-to-apples_expected_annual_loan_template.docx |
| acg_2019-2020_family_npc_input_data.docx |