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Description of Analysis, Data Sources and Assumptions

I collect numbers relating to the COVID-19 pandemic and create graphs in an attempt to visualize what is going on, and how different parts of the world are coping. Only reputable data sources are used, but the analysis is mine and the comments represent only my opinions. Feel free to disagree. Leave a comment!

A bit of terminology first:

Reported Case: this is a person who has, or had, a confirmed case of the virus. Reported case count never goes down, even when recovery (or death) happens. The only times it would go down is if there was a misdiagnosis (or a reporting error).  It is simply a reported case that happened. It is absolutely true that reported cases do not represent all cases,  reported cases only represent those cases that have been reported, tested, and confirmed. So its probably fair to say that reported cases are just the bad cases (and maybe also cases reported in essential/health care workers who are tested more routinely), not the mild cases where the person stayed at home to recover. However, as the testing rates increase, this number gets more and more accurate.

New Case: this is a reported case that was first reported today. The media generally presents new cases followed by reported cases. “Today there were 23 new cases for a total of 100 cases” for example.

Recovery
: A reported case that has now recovered. This can mean two negative tests in twenty four hour period, or perhaps the end of a two week isolation period with no more symptoms. There does not appear to be a common definition for recovery.

Death
: A reported case that has succumbed to the illness. Unless the health care system is completely overloaded, this almost always happens in a hospital.

Infection (or Active Infection): This is calculated by adding the recovery count and the death count and subtracting that total from the reported case count. For example, on a particular day if there are 100 reported cases, 35 recoveries and 5 deaths, the active infection count on that day is 100 – (35 + 5), which equals 60. The active infection count is a reasonable representation of the load on the health care system on that day. Even if there are many more unreported cases, they do not present a huge burden on the health care system because these people are likely at home recovering. Formula: Infections = Reported Cases – (Deaths + Recoveries)

Mortality Rate: this is the ratio of the number of deaths to the number of reported cases. This can be a bit misleading since there are usually a significant number of infections which have neither died nor recovered yet. The calculation of mortality rate assumes that all active infections will recover, so it tends to underestimate what the actual mortality rate will be when all reported cases have a known outcome. The mortality rate becomes more accurate as the number of cases with known outcomes grows closer to the total case count. Formula: Mortality Rate = Deaths / Reported Cases

Recovery Rate: this is the ratio of the number of recoveries to the sum of recoveries and deaths. It shows, for those reported cases with a known outcome, what percentage of these cases have recovered. This will line up with mortality rate once all reported cases have a known outcome, and will get closer and closer to lining up with the mortality rate as the number of active infections drop. For example, in China in mid April (with very few active infections) the mortality rate was about 5% when the recovery rate was 94%. They were close to adding up to 100%. In the USA in mid April, (with many active infections), the recovery rate was 63% when the mortality rate was 5.3%. They were nowhere near to adding up to 100% yet. Formula: Recovery Rate = Recoveries / (Recoveries + Deaths)

The diagram below shows how reported cases are broken down into recoveries, deaths, and active infections, showing sample counts and the calculations of mortality and recovery rates.

To help understand what these graphs represent, consider the analogy of a car:

Lets say you have a parked car that you want to race. When the car is stopped its speed and acceleration are both zero. This is like a region of the world before any COVID-19 infections have started.

When the car starts to move, the speed starts to increase, which is acceleration. This is like a region of the world where COVID-19 infections have started. The speed of the car is like the rate of new cases (measured as new cases per day).The faster the car increases speed, the greater the acceleration rate. This is like the growth of the number of new cases from one day to the next.

When the car starts to maintain a steady speed, the acceleration goes to zero but the car is still moving. This is like a region that has more or less the same number of new cases each day. There are still new cases, just not more new cases each day than the day before.

To “flatten the curve”, the car needs to slow down to a steady speed such that active infections (total reported cases less recoveries and deaths) reach a steady count that does not exceed the capacity of the health care system. This happens when that steady number of active infections does not exceed health care system capacity at the time stability is attained, or with a period of deceleration, where the speed decreases until the capacity of the health care system is no longer exceeded by the number of active infections. 

Deceleration can be fast or slow. When deceleration happens in a region, the count of new cases every day begins to decrease, finally coming to near zero new cases every day. That is the goal – zero new cases each day, but the curve can be considered “flattened” when the number of active infections is stable and does not exceed the capacity of the health care system. This analysis reports the number of active infections (see Recovery charts), but does not attempt to assess if the capacity of the health care system has been exceeded.

To describe the state of some of the regions as of the end of March:

  • The Chinese car was slowing down and nearly stopped.
  • The Italian car was nearly at its top speed, but still gaining speed.
  • The USA car was accelerating rapidly, not yet at its top speed.
  • The BC car was at a relatively constant speed.
  • The Costa Rican car had just left the starting line.

Fairly simple to understand right?

To further this analogy, imagine that the car from each region has a different size engine (horsepower). This is like the population density of each region (people per square kilometer). And we want to see the race between each region’s car and China’s car. This seems useful because China was first region to be impacted by COVID-19 and we all saw the response and its impact on the news. By comparing a region with China we can measure how that region is doing, and what might yet happen in that region. In order to make a meaningful comparison I did two things:

  • I put each car on the starting line at the same time. This is done by moving the data from China forward in time to match up to the case 1 date with the particular region.
  • I adjusted the horsepower of the Chinese car to match the horsepower of the regional car. This is done by scaling the reported case counts from China proportionally to the population density of the region. That is to say that China’s case counts are scaled to match the population density of each region.

OK, that was a bit more complicated, but the idea is to make the cars start at the same time, with the same size engine, then see how the regional car does against what we know already happened with the Chinese car. Its a simple idea. Not perfect, but simple.

OK, one more extension of this “car” analogy…

Imagine that there are people on the race track and each driver is trying to avoid them, but inevitably hits and injures some people. Only some people are actually injured, and those people who are injured may recover, or they may succumb to their injuries. A better driver will hit less people and will also leave behind more people that are able to recover. This is like the percentage of recoveries in those reported cases that have a known outcome, ignoring active infections (because the outcome is not known yet). A better driver (who is careful driving, and has a good health care system) will result in a higher percentage of recoveries in those cases that have a known outcome, and this provides a view as to how well the population is recovering based on known outcomes only. Only when all reported cases have a known outcome will the mortality rate for the region will line up with this.

The comments found below the graph for each region provide the speed (new cases each day), and acceleration or deceleration (change in the number of new cases each day), and rating of the driver of the car (recovery percentage of reported cases with known outcomes) and reference this “car” analogy to make it easier to understand what the numbers mean.

These are the major assumptions and formulas used in these graphs and analysis

  • Formula: Adjusted_Case_1_Regional_Date = Date_of_Case_In_Region – (Case_1_Date_In_Region – Case_1_Date_In_China)
    The number of days from case 1 in China to case 1 in other regions was measured. This is used to slide the China data forwards in time to align with case 1 in the region. It ranges between 19 and 65 days difference in the date of case 1.
  • Formula: Adjusted_China_Case_Count = ( China_Case_Count ) / ( (China_Population / China_Land_Mass) / (Regional_Population / Regional_Land_Mass) ).
    Given that different regions have different population densities, which would likely impact the infection rate, The populations and land mass areas were looked up to create population density numbers (people per square km). Population density ratios between China and other regions are calculated and used that to scale the Chinese data down in a linear fashion. This is a major simplifying assumption which undoubtedly introduces error, but I believe it brings the analysis closer to the truth than simply ignoring population density.Google was used to find populations and land masses.
  • Different data sets are reported in different time zones so the data may be off by a day or so in some cases.

I chose a particular set of regions to analyze:

  • China – as the starting point for this virus and the first worldwide experience of this outbreak. China seemed like a good region to compare to.
  • Canada and BC – because I live in BC, which is a province of Canada
  • Netherlands – because I have family there
  • Costa Rica – because I have family there too
  • Italy – because of the tremendous impact this is having there
  • USA – because anything of this scale happening in the USA will undoubtedly impact the rest of the world
  • Sweden – because they are less strict about locking down, depending on their people to take the right measures without needing the enforcement.
  • World – because its the whole world!

Only reputable data sources are used as listed below.

  • World Health Organization – for Case and Death counts in China and the world. Updated with a situation report once per day. I note that the Canada numbers reported here are a day or two behind Canada CDC and are likely a day or two behind most areas of the world because it takes time to collect and report. There was a jump in reported cases mid February which reflects a change in the way the WHO collected and reported data.
  • Canadian Public Health – for Case and Death counts in Canada. Updated several times per day.
  • CTV News – for verification against Canada Public Health and for Canadian recovery data.
  • USA Center for Disease Control – for Case and Death counts in USA. This site is updated every weekday, but not always on weekends, which seems strange to me.
  • British Columbia Center for Disease Control – for Case, Death, and Recovery counts in BC. Updated several times a day.
  • RIVM Netherlands for Case and Death counts in the Netherlands.
  • Johns Hopkins GIS App for recovery counts if I cannot find them on region specific CDC sites

Since some of these sites do not publish their own historical data, and since I only started collecting systematically in early March, I used the Way Back web site to collect some of the historical data. Not every day was captured by Way Back so there are some gaps in the data which make some of the graphs a bit “choppy” in January and February, but I did get historical data at least weekly using that approach. 

The following data has been used to display or adjust the regional data in order to compare it to China.

The following charts and analysis are created on this basis. They are updated once a day (usually in the evening Pacific Daylight Time) and should be normally one day behind today’s date.

Quick Links

Fri 25-Sep-20 *New Today*

  1. The focus is changing from a comparison to China (not so relevant now), to a comparison to world numbers and references to prior peaks for each analyzed region. There are additional comparisons in the text below each regional graph.
  2. It has been very interesting to watch the numbers as different regions continue to re-open their economies. 
  3. It will be interesting to see what happens as the school systems open their doors in various regions in September.
  4. Top 5 countries by case count: USA, India, Brazil, Russia, Columbia.
  5. USA continues to grow. The USA is showing signs of slowing its growth (but the daily rate of new cases is still quite high). 
  6. Costa Rica continues to rapidly grow. There is no doubt that it is now growing at a substantial rate, and continues to accelerate.
  7. Netherlands is rising rapidly again. As the economy reopened in August, reported daily case counts have gone up again, but are no longer accelerating.
  8. BC had significant increases in cases in August, and then again over the last week, but it is slowing slightly. Stay vigilant!
  9. Italy is recovering well, but infections are on the rise again. The daily rate of new cases is climbing again while recoveries continue.
  10. Canada, Sweden are starting to show early signs of growth again.
  11. China continues to recover well. The daily rate of new cases is low, and the active infection line is low and nearly flat.

Today's Numbers

Comments on Today’s Numbers

  • There will be no publish on Saturdays and Sundays since several regions no longer report on the weekends.
  • Recovery Counts seem unusually low in some regions. Netherlands recovery numbers are very low per reported case compared to other regions, perhaps they use a different measurement to determine recovery. Therefore the active infection line for the Netherlands follows the case count line very closely. Swedish recovery numbers are now reported as unavailable on Johns Hopkins, so the active infection and recovery curves have been removed. However, Johns Hopkins case counts and mortality data are well aligned to regional CDCs. BC CDC and Canada Public Health publishes BC and Canadian recovery respectively data so I have confidence in the Canadian recovery numbers.
  • Some metrics on the numbers I have collected: As of 25-Sep-20, over the period from 03-Jan-20 to 25-Sep-20 (267 days), there have been 6,348 individual numbers collected for 9 regions, which are used to form these graphs and analysis. The main Excel worksheet has 87 columns of calculations across 2,111 rows of data, making 183,657 individual calculations. There are twelve Visual Basic functions and fifteen worksheets in the spreadsheet. Each day thirty new numbers are collected and verified from seven independent web sites. It takes four CPUs and over two minutes for the spreadsheet to grind out the graphs and analysis. Some manual written analysis is created and entered. Then it takes about twenty minutes to copy and paste the results to my website. This is not a funded service and is free from any political interference. Just saying…

Cases in all Regions

25-Sep-20 Comment: The USA has the most cases per capita over analyzed regions, followed by Costa Rica. Costa Rica and Sweden are well below the USA, but Costa Rica is catching up. The Netherlands has passed Italy. Canada, BC, then China are below the World average. China’s case count, while high in actual numbers (90,000+), is very low per capita compared to other regions. Data Sources: WHO, Johns Hopkins, Canada Public Health, CTV News, BC CDC.

Deaths in all Regions

25-Sep-20 Comment: The USA has the most deaths per capita in analyzed regions, and is closely followed by both Italy and Sweden. USA, Italy, Sweden, Netherlands, Canada, Costa Rica are all above the World average. BC and China are below the World average. Mortality rate (deaths per reported cases) for analyzed regions ranges from 1.1% in Costa Rica to 11.7% in Italy. Recovery rate (recoveries per reported cases with known outcomes) for analyzed regions ranges from 34.9% in Netherlands to 97.1% in Costa Rica. Data Sources: WHO, Johns Hopkins, Canada Health, BC CDC, USA CDC.

Tests

25-Sep-20 Comment: BC has performed 506,520 tests (10.0% of the population). Canada has performed 6,979,242 tests (18.6% of the population). The USA has performed 99,483,712 tests (30.4% of the population). The USA has tested at a higher rate than both Canada and BC. BC is testing at about half the rate of Canada as a whole. Note that these numbers are tests performed, (not people tested) which could count more than one test for a single person. Data Sources: Johns Hopkins, Canada Public Health, BC CDC.

World Case Counts

Comment: In the early part of the graph its mostly happening in China. In mid March is where it hit the world

25-Sep-20 Comment: The World reported 315,626 new cases in the last day, (1% more than the prior day which had 311,724 new cases), for a total of 32,406,883 cases. The number of new cases is moderate over the last 7 days (an average of 288,710 new cases per day). In the last 7 days, the speed of the World’s car is moderate and it is very slowly decelerating. In the World the number of active infections is increasing very slowly over the last 7 days (an average increase of 44,125 active infections each day), with a current total of 9,089,179 active infections. The World reported 5,492 new deaths over the last day, for a total of 985,791 deaths. This is 6% more than the prior day, which had 5,199 new deaths. The mortality rate in the World is 3.0%. Based on recoveries vs deaths (96%) so far, the driver of this car is an excellent driver. The World reported the highest daily number of new cases (357,932) 2.1 months ago on 23-Jul-20, the highest active infection count (9,089,179) today on 25-Sep-20, and the highest daily deaths (29,882) 4.9 months ago on 02-May-20. Data Source: Johns Hopkins

China Case Counts

Comment: This shows the early exponential rise in cases in China in January and February, followed by the flattening out caused by the massive response.

25-Sep-20 Comment: China reported 15 new cases in the last day, (50% more than the prior day which had 10 new cases), for a total of 90,933 cases. The number of new cases is almost stopped over the last 7 days (an average of 20 new cases per day). In the last 7 days, the speed of China’s car is almost stopped and it is at a nearly constant speed. In China the number of active infections is constant over the last 7 days (an average increase of 1 active infections each day), with a current total of 858 active infections. China reported 0 new deaths over the last day, for a total of 4,745 deaths. This is less than the prior day, which had 1 new deaths. The mortality rate in China is 5.2%. Based on recoveries vs deaths (95%) so far, the driver of this car is a very good driver. China reports 0.02 times the world per capita case count, 0.03 times the world per capita death count, and 0.00 times the world per capita active infection count. China reported the highest daily number of new cases (352) 5.4 months ago on 17-Apr-20, the highest active infection count (2,687) 7.6 weeks ago on 03-Aug-20, and the highest daily deaths (1,290) 5.4 months ago on 17-Apr-20. There have been 6,433 new cases reported since 18-May, when two new outbreaks were reported in China by the media, then another outbreak reported 13-Jun. Overall China is recovering well. 注意安全 ! Data Sources: WHO / Johns Hopkins recoveries.

Netherlands Case Counts

25-Sep-20 Comment: Netherlands reported 2,852 new cases in the last day, (10% more than the prior day which had 2,593 new cases), for a total of 110,749 cases. The number of new cases is very high over the last 7 days (an average of 2,344 new cases per day). In the last 7 days, the speed of Netherlands’s car is very high and it is very rapidly accelerating. In Netherlands the number of active infections is increasing extremely rapidly over the last 7 days (an average increase of 2,246 active infections each day), with a current total of 100,957 active infections. Netherlands reported 39 new deaths over the last day, for a total of 6,377 deaths. This is more than the prior day. The mortality rate in Netherlands is 5.8%. Based on recoveries vs deaths (35%) so far, the driver of this car is a very poor driver. Netherlands reports 1.55 times the world per capita case count, 2.94 times the world per capita death count, and 5.04 times the world per capita active infection count. Netherlands reported the highest daily number of new cases (2,852) today on 25-Sep-20, the highest active infection count (100,957) today on 25-Sep-20, and the highest daily deaths (241) 5.7 months ago on 07-Apr-20. There was significant acceleration in late July as the economy began re-opening, and it is accelerating again. Recoveries seem unusually low compared to other regions. Blijf Veilig! Data Source: Johns Hopkins.

Italy Case Counts

25-Sep-20 Comment: Italy reported 1,912 new cases in the last day, (7% more than the prior day which had 1,786 new cases), for a total of 306,235 cases. The number of new cases is moderate over the last 7 days (an average of 1,576 new cases per day). In the last 7 days, the speed of Italy’s car is moderate and it is very, very slowly accelerating. In Italy the number of active infections is increasing slowly over the last 7 days (an average increase of 731 active infections each day), with a current total of 47,718 active infections. Italy reported 20 new deaths over the last day, for a total of 35,801 deaths. This is 13% less than the prior day, which had 23 new deaths. The mortality rate in Italy is 11.7%. Based on recoveries vs deaths (86%) so far, the driver of this car is a good driver. Italy reports 1.22 times the world per capita case count, 4.68 times the world per capita death count, and 0.68 times the world per capita active infection count. Italy reported the highest daily number of new cases (6,638) 5.7 months ago on 07-Apr-20, the highest active infection count (108,257) 5.3 months ago on 19-Apr-20, and the highest daily deaths (1,056) 5.7 months ago on 06-Apr-20. The curve had more than flattened for Italy, but is trending up again. Rimanga sicuro! Data Source: Johns Hopkins.

Sweden Case Counts

25-Sep-20 Comment: Sweden reported 634 new cases in the last day, (19% more than the prior day which had 533 new cases), for a total of 90,923 cases. The number of new cases is moderate over the last 7 days (an average of 365 new cases per day). In the last 7 days, the speed of Sweden’s car is moderate and it is very slowly accelerating. In Sweden the number of active infections is increasing over the last 7 days (an average increase of 362 active infections each day), with a current total of 80,072 active infections. Sweden reported 2 new deaths over the last day, for a total of 5,880 deaths. This is the same as the prior day, which had 2 new deaths. The mortality rate in Sweden is 6.5%. Sweden reports 2.16 times the world per capita case count, 4.60 times the world per capita death count. Sweden reported the highest daily number of new cases (2,889) 3.2 months ago on 22-Jun-20, and the highest daily deaths (190) 5.7 months ago on 07-Apr-20. Daily case counts jumped significantly beginning in June, and stabilized in July/Aug. Sweden’s response, with limited economic closures, is intended to result in little or no second wave of infections. It will be interesting to see if that happens and if and when the case counts completely flatten out. Var försiktig! Data Source: Johns Hopkins.

Costa Rica Case Counts

25-Sep-20 Comment: Costa Rica reported 1,357 new cases in the last day, (3% less than the prior day which had 1,400 new cases), for a total of 70,816 cases. The number of new cases is extremely high over the last 7 days (an average of 1,180 new cases per day). In the last 7 days, the speed of Costa Rica’s car is extremely high but it is slowly decelerating. In Costa Rica the number of active infections is increasing extremely rapidly over the last 7 days (an average increase of 590 active infections each day), with a current total of 42,981 active infections. Costa Rica reported 17 new deaths over the last day, for a total of 812 deaths. This is 21% more than the prior day, which had 14 new deaths. The mortality rate in Costa Rica is 1.1%. Based on recoveries vs deaths (97%) so far, the driver of this car is an excellent driver. Costa Rica reports 3.47 times the world per capita case count, 1.31 times the world per capita death count, and 7.52 times the world per capita active infection count. Costa Rica reported the highest daily number of new cases (1,556) 7 days ago on 18-Sep-20, the highest active infection count (42,981) today on 25-Sep-20, and the highest daily deaths (21) 2 days ago on 23-Sep-20. The very strict response (curfews, limited driving days) in Costa Rica seemed to be working well in May, but this second wave is significantly bigger than the first wave. ¡Mantenerse a salvo! Data Source: Johns Hopkins.

USA Case Counts

25-Sep-20 Comment: The USA reported 53,469 new cases in the last day, (30% more than the prior day which had 41,193 new cases), for a total of 7,027,910 cases. The number of new cases is very high over the last 7 days (an average of 43,765 new cases per day). In the last 7 days, the speed of the USA’s car is very high and it is slowly accelerating. In the USA the number of active infections is increasing rapidly over the last 7 days (an average increase of 17,684 active infections each day), with a current total of 4,097,004 active infections. The USA reported 843 new deaths over the last day, for a total of 203,571 deaths. This is 1% less than the prior day, which had 848 new deaths. The mortality rate in the USA is 2.9%. Based on recoveries vs deaths (93%) so far, the driver of this car is a very good driver. The USA reports 5.17 times the world per capita case count, 4.92 times the world per capita death count, and 10.75 times the world per capita active infection count. The USA reported the highest daily number of new cases (77,638) 2.3 months ago on 17-Jul-20, the highest active infection count (4,097,004) today on 25-Sep-20, and the highest daily deaths (4,553) 5.4 months ago on 16-Apr-20. After a period of explosive growth in July, daily case counts have slowed somewhat. Our thoughts and prayers are with our American brothers and sisters. Stay safe! Data Source: Johns Hopkins.

Canada Case Counts

25-Sep-20 Comment: Canada reported 1,362 new cases in the last day, (2% more than the prior day which had 1,341 new cases), for a total of 150,456 cases. The number of new cases is moderate over the last 7 days (an average of 1,210 new cases per day). In the last 7 days, the speed of Canada’s car is moderate and it is very slowly accelerating. In Canada the number of active infections is increasing very slowly over the last 7 days (an average increase of 337 active infections each day), with a current total of 11,627 active infections. Canada reported 7 new deaths over the last day, for a total of 9,256 deaths. This is 53% less than the prior day, which had 15 new deaths. The mortality rate in Canada is 6.2%. Based on recoveries vs deaths (93%) so far, the driver of this car is a very good driver. Canada reports 0.96 times the world per capita case count, 1.95 times the world per capita death count, and 0.27 times the world per capita active infection count. Canada reported the highest daily number of new cases (2,760) 4.8 months ago on 03-May-20, the highest active infection count (35,014) 3.9 months ago on 30-May-20, and the highest daily deaths (289) 4.7 months ago on 08-May-20. The growth in the active infection count is slowing. Stay safe! Data Source: Canada Public Health.

BC Case Counts

25-Sep-20 Comment: BC reported 98 new cases in the last day, (34% less than the prior day which had 148 new cases), for a total of 8,641 cases. The number of new cases is low over the last 7 days (an average of 114 new cases per day). In the last 7 days, the speed of BC’s car is low and it is very slowly decelerating. In BC the number of active infections is decreasing slowly over the last 7 days (an average decrease of 92 active infections each day), with a current total of 1,375 active infections. BC reported 1 new deaths over the last day, for a total of 230 deaths. This is 50% less than the prior day, which had 2 new deaths. The mortality rate in BC is 2.7%. Based on recoveries vs deaths (97%) so far, the driver of this car is an excellent driver. BC reports 0.41 times the world per capita case count, 0.36 times the world per capita death count, and 0.23 times the world per capita active infection count. BC reported the highest daily number of new cases (179) 7 days ago on 18-Sep-20, the highest active infection count (2,009) 4 days ago on 21-Sep-20, and the highest daily deaths (6) 2.7 months ago on 06-Jul-20. A sharp rise in recoveries has pushed the active infection count down, and new cases counts are slowing. We must stay vigilant or we will lose all our progress. Stay safe! Data Source: BC CDC.

This Post Has 234 Comments

  1. Mike Davenport

    hi Rob, LinkedIn just offered your site so here I am. I have similar interests in the data (rather than the hype) and am keenly aware how hard it is to find the correct data that cleanly reveals what is happening. Have you looked at Euro MoMo (Mortality Monitoring) ? It has been collecting and reporting data for many years, and focuses on the simple question: what are patterns of all-cause mortality in European nations? The focus on “all-cause” gets around issues when people have many compounding health issues. It reports: deaths/month this year, deaths/month previous years, standard deviations (i.e. expected variations in deaths/month), z-factors, etc. Thus it tends to compare each year, in each country, to previous years – which is a new and important perspective.

    1. Rob vanSpronssen

      Hi Mike. Thanks for your interest. I have not looked at Euro MoMo mortality monitoring. I rely on WHO, Johns Hopkins, and BC/Canada CDC for my numbers (you can see the links on my page). I simply don’t have time for a more exhaustive analysis, so I have to keep it simple.

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  161. Brian Stapleton

    Hi again Rob

    I read this article this morning and thought it might be of interest.

    Coronavirus: How ‘overreaction’ made Vietnam a virus success https://www.bbc.co.uk/news/world-asia-52628283

    Key points was a population who have had SARS, Avian flu and others and understand the impact, reacted quickly and decisively.

    1. Rob vanSpronssen

      Good article. I agree 100%. I heard a similar thing from a medical person (near the time of the start of it in China) whose expertise was in pandemics like SARS and Ebola. He said in a pandemic that “speed trumps perfection”, and that you were better to be judged as over-reacting. Days and hours make a difference in containing it.

  162. Guillermo Sancho

    Here in Costa Rica we are confident that soon we will have a plasma based treatment that could be of great help. The Clodomiro Picado Institute is working hard on this line. Have you hear of that possibility ?

    1. Rob vanSpronssen

      No I have not heard that, but sounds like good news. Costa Rica seems to have handled this pandemic very well. Good job!

  163. Brian Stapleton

    Hey Rob

    I am enjoying the presentation of the data. An added dimension that may be of interest if the culture differences play a part, such as individualism vs collectivism. You could base it on the hofstede data found here https://www.hofstede-insights.com/product/compare-countries/

    Costa Rica has low individualism compared to say Italy, USA, UK etc.

    Extending on above, you also could look at the current leadership of the countries you are monitoring and whether they are left or right leaning politically (some sort of scale) and whether there is a correlation with the effectiveness of the car driver.

    Thank you for sharing

    1. Rob vanSpronssen

      Great to hear from you Brian. Those are good ideas. I do believe that cultural collectivism vs individualism plays a big part in recovery.

  164. Mike D

    so, interesting thing to consider adding to your graphs. Best known mortality rate is 1%. For countries where there are enough cases, we can use the # of deaths (which are confirmed covid positives), to project the aprobable number of positives. This accounts for the lack of widespread testing in most countries (including ours). Just something to consider. Thanks for this page!

    1. Rob vanSpronssen

      Interesting idea, let me ponder that. Thanks for your feedback!

  165. Andrew

    Rob, can we have some graphs of fish? Or caddis fly hatch rates? Maybe a pic or two of a nice rainbow leaping over the Recoveries line… I am happy to see the BC infections curve looking much like the summer doldroms.

  166. Andy Symchych

    Excellent information Rob, keep up the good work. All my best too you and Sherry and the boys.

  167. Richard Nasr

    Thanks for all this great data! This is great Rob. Now we just need a chart that shows how many charts have been generated on COVID-19 by chart type, by country and how it correlates with the effectiveness of each country’s ability to flatten the curve. 😉

    1. Rob vanSpronssen

      Nothing beats good data, that’s for sure. Its very clear in the regions I am analyzing that the early, decisive, action works. My brother in law in Costa Rica says there is a 5pm curfew and you can only drive two days in a week. They are containing it better than any other region, but are 65 days behind China, so its still a bit early to be sure.

  168. Naadia Clayton

    Thanks Rob……very easy to comprehend 😀

  169. John Vanspronssen

    Very interesting Rob, glad to live in Canada not the USA

  170. Lisa Woudzia

    Thank you, Rob! Very informative and comprehensive!

  171. Paul

    Nice work Rob! Keep it updated!

    1. Rob vanSpronssen

      Thanks Paul. I’m trying to update it every morning (Pacific Time).

  172. Angela Termarsch

    Wow, now there is some interesting data! Thanks for the info and will check it to see how we are doing as the weeks go on..

  173. Wendy Laverock

    You really know your stuff Rob, this is interesting and well informing. Thanks and stay safe, love to you and Sherry and the boys💕💕

    1. Rob vanSpronssen

      Thanks Wendy. Our best to you and your family. Stay safe.

  174. John Ortynsky

    Thanks Rob,
    This helps put things in perspective.Im now working from home but Cherryl has to work with a much higher risk level so it’s very much top if mind for us.

  175. Tina van Koll

    Wow!! 😍 This is so interesting and detailed and well thought out. Thanks!!

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