[Skip to second paragraph if you are not interested in the German context of the false positives issue.]
On June 5, 2020, OVALMedia’s Robert Cibis interviewed the Austrian microbiologist and infectious disease specialist Dr. Martin Haditsch about laboratory tests and specifically the PCR test that is used globally to detect the Sars-CoV-2 virus in a person. The interview [in German] broached the issue of false-positive test results in the context of a low-prevalence disease and imperfect tests. Two Youtube copies of the one-hour interview have a total of over 100,000 views at the time of writing. The next day, Swiss entrepreneur and Youtuber Samuel Eckert presented a 20-minute summary and explanation of the false-positive issue using an interactive Excel spreadsheet. His video currently boasts over 225,000 views with 15,000 likes. Possibly in response, the German Federal Minister of Health Jens Spahn, a banker by training, said in a brief interview contained in a tweet from public TV channel ARD on June 14 that if the COVID-19 prevalence continued to drop and testing was simultaneously expanded (as has been the case in many Western countries since mid-April) into the millions then you would eventually obtain more false-positive than correct-positive results.
Six weeks later, in a media briefing about the Province of Ontario’s safe reopening of schools, Associate Chief Medical Officer of Health Dr. Barbara Yaffe cautioned against seeing wide-spread COVID-19 testing as a solution. She went on to state that “in fact, if you’re testing in a population that doesn’t have very much COVID, you’ll get false positives almost half the time.”
In order to understand the impact of two test characteristics – sensitivity and specificity – we can use a confusion matrix to display true and false positive test results along with true and false negative test results. For example, in Geography we use confusion matrices to assess the accuracy of the classification of a remotely sensed image. The confusion matrix shows how many pixels of a certain land use class such as agricultural were correctly classified as agricultural or misclassified as another land use like forest. This is based on a ground-truthed image for comparison in a limited part of the study area. Similarly, the following spreadsheet estimates how often a positive or negative PCR test result is found in a true carrier of the virus vs an unaffected person.
The true proportions and counts of “infected” and not “infected” are based on the number of tests completed and the true prevalence of COVID-19 in the population, which is largely unknown. At the tail end of winter, coronaviruses are typically causing cold infections in some 5% to 10% of the population. As COVID-19 has tapered off over the summer, a value below 1% seems reasonable, here set to 0.5% as an example. In recent days, there were 40,000 or more tests completed in Ontario with some 400 new “cases” detected for a test-positivity rate of around 1%. Note that in conjunction with the PCR test, I like to put “cases” and “infected” in quotation marks since the test does not distinguish sick people carrying an infectious virus load from healthy, presymptomatic, or asymptomatic people carrying traces of inactive genetic material from the virus.
With a prevalence of e.g. 0.5%, we expect that 200 out of 40,000 tests are true positives. If we assume the sensitivity characteristic of the test at 99%, we get 198 correct positives out of the 200 true “infections” that should be detected, while two are missed. These two misses are false-negative results. False negatives are problematic, since potentially infectious persons are told that they don’t pose a risk to their environment. However, at a low prevalence of the disease, these misses are very small, even negligible, in comparison with the correctly identified negatives.
After subtracting 200 “infected” from the 40,000 tests completed, there are 39,800 left who should test as not “infected”. However, medical tests are usually imperfect in that they can both miss a condition present (false negatives, see above) as well as indicate the presence of a condition when it is not there (false positives). The characteristic that describes how accurate the test is in this latter respect is called specificity. It refers to how specific the test is geared towards its target, here the Sars-CoV-2 virus, rather than picking up other targets. The specificity of the PCR test for Sars-CoV-2 is a bit of a mystery and moving target, but before I discuss it, I will go through one example to explain the significance of false-positive results in the current phase of the pandemic.
With an assumed specificity of 99.5%, our test would determine 39,601 correct negatives out of 39,800 persons who are truly not “infected”. An issue arises with the remaining 199 false positives, which are wrongly detected by the test although they do not carry the virus. While the number is small in proportion to the correct negatives, we need to view it in relation to the 198 correct positives. From the perspective of each person testing positive, the chance that they are in fact falsely positive is 199 : 198, thus 50% of the 397 total positive test results are false positives, in line with the warnings by the officials cited above. The relationship is only this large due to the low prevalence of the disease. You can use the spreadsheet link above to examine the effect of increasing or decreasing the prevalence (try 0%!) and modifying the test characteristics.
Due to the significant restrictions imposed on test-positive persons’ lives, 50% false positives is a highly problematic proportion. In addition, a difference between 200 and 400 new “cases” may affect the assessment of the current public health threat, although the raw count of positive PCR tests is almost meaningless without considering who was tested and how many tests were completed, an issue which shall be discussed at another time.
Some critics of the pandemic response are using a lower specificity of 98.6% and come to the conclusion that all (!) positive test results in certain jurisdictions such as Germany are false positives and therefore the pandemic has ended. That values stems from a study of lab results (external PDF, see page 12) conducted by a German accreditation body in April, which found an average of 98.6% correct negative results across over 400 participating labs. Other experts however have noted that the actual proportions of positive test results has gone down to values as low as 0.6% in Germany, 0.3% in Canada, and even 0% in New Zealand, which – given the large numbers of tests completed – would not be possible if the false positives were any higher than these values. This can be explained by the fact that the quality assurance study reported the results for individual gene sequences but the testing protocols in some countries were modified to require testing of at least two gene sequences. In this case, the false positive rates of 0.5% for the E gene region (which I used in the above example) and e.g. around 2% for another characteristic gene would have to be multiplied, resulting in extremely low false-positives of 1 in 10,000 or so. However, Public Health Ontario’s in-house test methods target the E gene and clearly state that “Specimens with a single target detected … will be reported as COVID-19 virus detected, which is sufficient for laboratory confirmation of COVID-19 infection.” (emphasis added)
In summary, false-positive PCR test results likely are, or have been, an issue in some jurisdictions during some phases of the corona crisis, and politicians and health officials should be more transparent about this. Questions that the media should be asking include:
When did you become aware of the impact of false positives?
What is the magnitude of the problem currently?
Have lab testing procedures been modified to address the issue?
Is wide-spread testing still meaningful at this point in the pandemic?
In fact, just yesterday, the Ontario government changed course by discouraging asymptomatic people from getting tested. Yet this reversal seems more related to preserving lab capacity for symptomatic persons and those with suspected exposure, who need faster test results, than to the fundamental issues with over-testing.
Karina Reiß, Sucharit Bhakdi: Corona Fehlalarm? Zahlen, Daten und Hintergründe [Corona False Alarm? Numbers, Data and Background]. Goldegg, Vienna Austria. Published 1 June 2020 (eBook, EAN 9783990601907) and 23 June 2020 (paperback, 160 pages, ISBN: 978-3-99060-191-4)
Published in the midst of the SARS-CoV-2 pandemic, „Corona Fehlalarm?“ (German for “Corona False Alarm?”) gives reason for deep reflection on where humanity stands with respect to rational decision-making, public health, and the social contract. In fact, the authors would argue that we are in a panic rather than a pandemic, and that we are not in the midst but at the end of the COVID-19 curve, though we may only be at the beginning of much worse collateral damage inflicted by the global overreaction to the appearance of the novel coronavirus in December 2019.
Professor Karina Reiß, whose natural sciences doctorate is in cell biology, is a faculty member in the Department of Dermatology and Allergology at the University Hospital of the northern German province of Schleswig-Holstein in Kiel. Her co-author and husband, retired professor Sucharit Bhakdi, holds a medical doctorate and spent his career as a faculty member in institutes for Medical Microbiology at the universities of Gießen and Mainz in Germany. Dr. Bhakdi has been one of the early critics of the lockdown measures in Germany. On March 26, he publicly asked German Chancellor Dr. Angela Merkel five questions around the threat assessment of COVID-19, which remained unanswered. In a June 3 video interview with alternative news magazine Rubikon, Dr. Bhakdi explained the genesis of the book “Corona False Alarm?” out of his and his wife’s frustration with the repeated extension of many emergency measures by the German governments.
The book consists of ten chapters framed by an introduction and conclusion. The introduction, subtitled “Start of a Nightmare?”, outlines the first half of 2020 that most of us have experienced as an onslaught of bad news and terrifying images from Wuhan’s hospitals to northern Italy’s morgues, supermarket lineups and empty shelves, isolated seniors trapped in long-term care homes and police drones surveying deserted city streets and parks. The authors briefly outline the discovery of the novel coronavirus SARS-CoV-2 and the associated illness COVID-19. Subsequent chapters discuss the data and state of scientific knowledge concerning the public health threat from SARS-CoV-2; describe the pandemic situation in Germany; explain collateral damage from the lockdown measures; and compare the lockdown with Sweden’s light-handed response. Additional chapters suggest alternative emergency measures that could have been taken and analyze the role of the media in this crisis situation. The book ends with a short chapter asking where we will go from here, a concluding note, and an appendix with 208 numbered online references.
The first substantial chapter analyses the threat level of the so-called “killer virus” based on the relation of fatalities to infections. The authors explain three tremendous challenges with counting infections: (1) use of the non-validated PCR test with unknown false-positive and false-negative rates, which becomes problematic when the (true) prevalence of the infection decreases towards the end of an epidemic; (2) testing being limited to symptomatic patients instead of sampling across the entire population from an early stage; and (3) lack of attention to the fact that the number of tests completed directly influences the number of infections found, potentially resulting in a “lab pandemic”. The authors only present a hypothetical example here; I believe they could have easily used the example of Germany or any other country, in which the number of tests conducted were increased significantly as lab capacities became available in the early stages of the corona crisis, resulting in an apparent exponential growth of cases while the percent of positive test results quickly started to decline.
With respect to COVID-19 fatalities, Drs. Reiß and Bhakdi emphasize that the official guidelines in Germany, the UK, Sweden, the US, and probably most other countries are known to count anyone as a “corona death” who has tested positive for the virus, regardless of the ultimate cause of death. In some countries, a suspected infection was enough to be included in the death count. In addition, the agencies discouraged or prohibited autopsies for fear of endangering the pathologist. Nevertheless, a dissenting pathologist in Hamburg conducted autopsies on over 100 corona-related fatalities and found that all of them had at least one co-morbidity, most frequently cardio-vascular diseases. Similar observations are reported from Switzerland and Italy, casting doubt on the degree to which the SARS-CoV-2 virus caused the patients’ death. In this context, the authors place the “corona deaths” in context with Germany’s regular mortality of 2,500 to 3,000 deaths per day, and specifically with the death rate among people over 80 years. The text and graphic are a bit confusing here, but they nevertheless illustrate the minimal impact of COVID-19 even on elderly mortality compared to the big killers: heart disease and cancer.
Still in the same chapter, Drs. Reiβ and Bhakdi summarize different ways to compare the risks from COVID-19 and influenza. The infection-fatality rate (IFR) of a normal flu season in Germany is 0.1% to 0.2% with a few hundred deaths. However, in 2017/18, 25,000 patients died from the flu with 330,000 reported cases, resulting in a stunning 8% lethality. Even the original WHO estimate of 3% to 4% IFR for COVID-19 was lower, while current estimates were revised to 0.4% or less, taking into account a large number of undetected infections. For example, the CDC’s best estimate is now 0.26%, identical to the estimate from a comprehensive population-wide study by Prof. Streeck and team of the corona hotspot Heinsberg county in western Germany. Our book authors emphasize that this makes COVID-19 comparable to a moderate flu season and dispels the myth of the “killer virus”. They also note that while elderly are at much higher risk than the young, it is the co-morbidities that cause death and that many healthy elderly have survived the infection.
This chapter ends with a selective review of local factors that may have influenced the higher death counts and rates in COVID-19 hotspots in Italy, Spain, Britain, and the US. These factors include different testing regimes, historic underfunding of the hospital and healthcare system, hospital infections, antibiotics resistance, ad-hoc guidelines for medical treatment of COVID-19, classification of fatalities, local funeral logistics, fear and panic generated by media images, age structure, and regional air pollution.
Chapter 3 of “Corona False Alarm?” is a sharp critique of the prevailing expert advice and political decisions in Germany, yet it provides many lessons for other countries. The authors denounce the ever-changing goalposts for the pandemic threat assessment, from the case-doubling rate to the effective reproduction number R, the calculation of which changed several times, to thresholds on regional counts of new infections per 100,000 population currently in place. An extensive quote by Stanford Professor John Ioannidis is presented in contrast to the seemingly erratic government communications and decisions around mid-March 2020. Fear-mongering with spurious models, best known from the Imperial College group around Prof. Ferguson, and individual narratives by Germany’s “top” virologist Prof. Drosten about exploding cases and triage decisions in an overburdened healthcase system inevitably led to the lockdown decision effective March 23. Among other evidence that the lockdown was ill-advised, the authors present a copy of the infectious disease agency RKI’s estimated R curve, published mid-April, that shows that the peak of the pandemic was passed in early March before any measures were taken.
Readers with a critical disposition will already know many of these and the following details, but seeing them organized and summarized in book form gives them additional logic and credibility. The RKI’s R curve was extensively scrutinized by Prof. Homburg of the University of Hannover. Another early warning that the pandemic was “over” in late March came from Dr. Wittkowski, whose testimonials could be added to the book. Despite the evidence, the German lockdown was extended and makeshift face-coverings required in some indoor settings such as stores, a move the authors decry as capricious at best. Brainwashing through the mainstream media and the stoking of fear of a “second wave” by Prof. Drosten and others resulted in broad compliance with the lockdown, distancing, and mask regulations. This contrasts with the known seasonality of coronaviruses, illustrated in the book with reference to a 1998 study from Finland. The authors’ frustration is tangible when they report the slow pace of re-opening throughout May and the further extension of many measures until the end of June, and Chancellor Merkel’s recent statements that “we are still at the beginning of the pandemic” …
In Chapter 4, the German healthcare system and the occupancy of intensive-care beds and respirators throughout the pandemic are discussed. With reference to official data and a model from the “Corona Initiative of German SMEs”, the authors show that the system was nowhere near capacity at any point in time. In addition, they criticize the practice of bringing frail elderly patients, who would have gone into palliative care during normal times, into ICU and expose them to futile respirator treatment. The chapter ends with a summative assessment of the COVID-19 situation in Germany, including that there has never been an exponential growth of infections to begin with, that government decision-makers declared a pandemic emergency without justification and enforced nonsensical measures instead of living up to their oath of office: to work towards the wellbeing of Germans and protect them from harm. A section on “what the government did right” is left demonstratively empty.
Chapter 5 deals with the collateral damage from the lockdown measures. Reference is made to a leaked crisis management analysis from the German Ministry of the Interior, which suggests that the pandemic may have been a global false alarm and its “cure” comes with a disproportionate cost of lives (e.g. from deferred surgeries and stroke sufferers avoiding hospitals), wellbeing (e.g. loneliness, depression, violence, abuse), and prosperity (e.g. unemployment, bankruptcies). A particularly cruel side effect of the social distancing requirements was the isolation of seniors. The authors also highlight the impact on children and on the poorest regions in the world, before turning their sights in Chapter 6 to a handful of countries that averted general lockdowns. Given that more specific and proven infectious disease control measures existed, it is not surprising that high-density Japan (with little testing), South Korea (with extensive testing and tracing), Hong Kong, Iceland, and even the (in)famous Sweden have similar (or better) epidemic curves and death rates as the countries with the strictest and longest lockdowns, including France, Italy, and Spain. The authors call out German politicians and media for putting illicit pressure on Swedish decision-makers to follow suit with the Europe-wide lockdowns. Since Sweden has now reached one of the higher death rates in the world, it would be helpful to add details that may explain the – in today’s perspective – mixed results of the Swedish approach. Conversely, an interesting example included in the book is the Czech Republic where due to a court decision some restrictions were eased much earlier (late April) than elsewhere, without noticeable impact on COVID-19 cases.
According to Drs. Reiβ and Bhakdi, consistent protection of the at-risk population, in particular the residents of long-term care homes, would have been the right approach to addressing SARS-CoV-2. Chapter 7 also deconstructs politicians’ claims that the pandemic continues and normality will not return “until a vaccine is found”. Lockdown sceptics were particularly dismayed when Bill Gates got to make a 9-minute statement on public TV’s 15-minute prime time news show, decreeing that all 7 billion humans will be immunized with a vaccine developed in a time span compacted from five years to 18 months by skipping some of the required safety checks. Our authors explain immunity to coronaviruses on the basis of two natural mechanisms involving anti-bodies and t-cells, noting that t-cell immunity against coronaviruses has been largely ignored in public discourse. The much cited “herd immunity” for corona and flu viruses is described as a relative concept, which also relies on cross-immunity from earlier virus variants. Existing cross-immunity may very well explain the high percentage of asymptomatic and mild infections with SARS-CoV-2. Importantly, the same virus can never cause a catastrophic second wave, although a new, significantly different variant could. Given these factors, the authors call the aspiration to develop a SARS-CoV-2 vaccine foolish. They note parallels to the 2009 swine flu outbreak and the role of the WHO in determining what constitutes a pandemic. The same government advisors of today warned of a deadly disease then, and recommended the purchase of millions of doses of a quickly developed vaccine, which later had to be destroyed. And some of the same critics raised their voice, including physician and health politician Dr. Wodarg and one of our authors, Prof. Bhakdi, competent voices of reason that again today are ignored by decision-makers.
Chapter 8 turns to one of the most disturbing developments in the corona crisis of 2020: the role of the mainstream media, their journalists, and the censorship of social media and the web. The public broadcasters in Germany and many other European countries are considered the fourth branch of societal power, with a mandate to control the legislative, executive, and judiciary branches. They are legally required to be politically independent and contribute to the formation of public opinion – supposedly by reporting on opposing views regarding major questions and events. The book illustrates the complete failure of Germany’s public broadcasters along with private mainstream media (and parliamentary opposition) to critically monitor government action. The authors outline the fear-mongering on national and regional TV, the uncritical reporting on a limited subset of science and modeling, and the discrediting and silencing of dissenting viewpoints. What should be added here is the emergence of a grassroots democratic resistance movement, whose goal to restore and protect the constitution was equally ignored, if not ridiculed, by the mainstream media.
In addition, internal and external “fact checkers” produced inaccurate ratings that flagged alternative perspectives as conspiracy theories and led to shadow banning or complete removal of YouTube videos and Facebook posts as well as temporary web site closures. Meanwhile, the often changing and contradictory messages from governments and WHO were taken as the only permissible narrative. In interviews, Prof. Bhakdi repeatedly stated that it should not be considered “courageous” in a democracy to state one’s dissenting opinion. Yet, disturbingly, we have indeed reached this point, both with respect to personal opinions vis-à-vis family members, friends, and neighbours as well as regarding expert opinions. The authors of “Corona False Alarm?” take government, opposition, the media, and those in the know – here doctors and scientists – to task and accuse those, who remain silent, of complicity with regards to the collateral damage done.
The book ends with an even darker concluding Chapter 9 and a brief and faintly hopeful summary. The suspension of constitutional freedoms of opinion, speech, movement, assembly, exercise of religion, and choice of profession was not proportional to the public health threat from SARS-CoV-2. Germans should have been particularly vigilant when critical journalism went missing, mass hysteria was stoked, and public opinion constrained to a single narrative. The invitation to snitch on fellow citizens for violations of lockdown regulations is another sign of totalitarian practices established within a few months in what many of us considered a healthy democracy. I concur with Drs. Reiβ and Bhakdi that there will be extensive research and inquiry needed to learn from the corona crisis. The authors express their hope that the book will help prevent that (this!) history ever repeats itself.
Although it must have been put together with a red-hot needle (or keyboard?), the book reads well with a stringent storyline and fitting transitions between chapters. A few inaccuracies, duplications, and omissions are excused by the urgency to publish this important perspective on the ongoing corona crisis. While the information is often specific to German events and actors, some additions could be made to cover the development of the crisis in German-speaking Austria and Switzerland, which had their own distinct experiences. Translations into other languages would likely require some clarifications, if not the addition of regionally relevant contents. Owing to the subject, reading “Corona False Alarm?” could be quite upsetting for the unsuspecting reader, yet it is a must-read for anyone who wants to understand what on earth just happened!
Summary of a Leaked Report from the Crisis Management Unit KM4 of the German Ministry of the Interior (BMI)
Mainstream and alternative media in Germany are brewing with news of a leaked report assessing the German government’s crisis management with respect to COVID-19. The liberal-conservative magazine Tichys Einblickfirst published extracts of the report that was circulated by its author, a civil servant who has since been suspended. Another alternative media platform, Die Achse des Guten, documents that a draft of the “corona paper” had been presented internally as early as March 23 and the minister’s office was approached by the report’s author on April 25, but as the report continued to be shut down, the author decided to circulate it more widely and it was eventually leaked. The Ministry responded with an unusual Sunday press release dismissing the report as a personal opinion. Interestingly, nine eminent medical experts who were consulted in preparing the report issued a press release of their own on Monday, stating their surprise that the Ministry seems determined to continue ignoring expert analyses of the collateral damage of the COVID-19 response and fail to substantiate its claims that the protective measures taken were effective and are continuously being reassessed.
So what’s in the leaked report? The 187-page PDF document that I downloaded from Achgut.com consists of an anonymized 1-page cover letter, an 8-page summary, an 82-page full report, and a 96-page appendix (pages 3-5 of the appendix are missing). The subject line of the cover letter – “Results of internal assessment of corona crisis management” – is supplemented with three brutally honest bullet points:
Grave errors of judgement in crisis management
Deficits in the regulatory framework for pandemics
Corona crisis likely proves to be a false alarm
The report’s summary starts with the definition of the goal of crisis management: to detect and combat threats until the “normal” state is re-established (p. 2). The author further notes: “Therefore, a normal state cannot be a crisis.” This reads like a personal statement against the idea of a “new normal”, which has recently been promoted by many politicians and experts globally.
The remainder of the summary document outlines results of the author’s analysis (pp. 2-3, points 1-8) and conclusions (p. 2, points a) to c)). These sweeping points, which I will paraphrase below, are followed by an explanation of interdependencies during a crisis, including the declaration of an eminent threat (the pandemic) and the impact of protective measures and resulting collateral damage (pp. 3-4). The author then professes his perspective with respect to available courses of action (pp. 4-5) – also outlined below. What follows on pp. 5-8 is a section titled “Overview of health impacts (damages) of the government measures and limitations during the 2020 corona crisis”. This section is given a separate date of May 7 and is also attached to the press release of the nine medical experts mentioned above.
The report’s summary concludes with the author’s reasons to proceed with circulating the report without further consultation (p. 8). The stated reasons include the ongoing threat of collateral damage of the lockdown measures including avoidable deaths and the inability to have his analysis acknowledged through the ministerial hierarchy. The main report, which is double-dated to April 25 and May 7, 2020, is titled “Corona Crisis from the Perspective of Critical Infrastructure Protection”. In this blog post, I focus on summarizing, paraphrasing, and commenting on the 8-page summary.
Results of the Analysis
The author, who speaks alternatively in singular (“I”) or plural (“we”), summarizes his analysis in eight results:
Despite better knowledge, crisis management [in Germany] has not developed adequate tools for threat analysis and assessment. Status reports in the current crisis include only a fraction of information on the range of threats. Incomplete and unsuitable information does not allow for a proper threat assessment and thus does not support appropriate and effective emergency response. This methodological deficit translates upwards through levels of public administration; politics has had a much reduced ability to make evidence-based decisions.
The observed health impacts of COVID-19 on the general population suggest that we are dealing with a global false alarm. In relation to general mortality, there has likely never been an unusual threat to the population and the danger of COVID-19 was over-estimated. The author of the report adds a special note that these results were scientifically vetted and do not contradict the data and risk assessments presented by the German centre for disease control, the Robert Koch Institute (RKI).
The fact that the false alarm remained undetected to this point is owed to the lack of instruments that would trigger a warning in case of an unwarranted pandemic declaration or a situation in which the collateral damage of the response measures exceeds the disease’s impacts on public health, and specifically on fatalities.
At this point, it is plausible to assume that the direct loss of lives owed to the emergency response measures [i.e. lockdown, distancing, hospital procedures] is already greater than the COVID-19 death count [in Germany].
The collateral damage of the corona crisis is gigantic and pointless, will primarily manifest itself in the future, and can only be limited, not prevented any more.
As a consequence of the protective measures, the security and resilience of critical infrastructure has declined. Our society is subject to increased vulnerability and risk of failure of survival systems that could be fatal if a truly dangerous pandemic or another threat, such a bioterrorism attack, would occur.
Emergency orders and other protective measures that lost any meaning and are now causing collateral damage are still in place for the most part. It is urgently recommended to lift these measure immediately to avert harm to the population – in particular additional unnecessary deaths – and stabilize the possibly precarious state of critical infrastructure.
Deficits and errors in crisis management have led to the distribution of misinformation to the population. It could be said that the state has become one of the greatest producers of fake news in the corona crisis.
Three broad conclusions are drawn by the author:
a) The proportionality of restrictions of civil liberties is not evident, since governments have not properly assessed the consequences, as required by the German constitutional court on May 5.
b) Status reports from the ministries of the Interior and Health as well as federal communications to the provinces should immediately:
undertake an adequate risk analysis and assessment,
include a section with meaningful data on collateral damage,
be cleared of superfluous data and information that are unhelpful for risk assessment, and
develop and emphasize metrics [this point remains oddly vague].
c) An adequate risk analysis and assessment is to be completed immediately; otherwise, the state may become liable for damages.
Available Courses of Action
The report’s author sees the German government and administration in a precarious position, since in his assessment there is no reasonable doubt that the corona warning was a false alarm and that crisis management failed with respect to danger prevention and instead caused harm, including fatalities that continue to occur every day that the emergency response measures are kept in place.
The author further notes, which is not without humour, that technically a new crisis situation should be declared and the out-of-control pandemic crisis management itself be battled. In case the executive arm is not be able to regroup, the following options for a correction are proposed:
a) The legislative arm, i.e. the federal and provincial parliaments, could change the crisis management framework to force a change in the direction of the executive.
b) The judiciary has so far supported restrictions of constitutional rights with reference to the eminent threat but without in-depth test of plausibility of the government’s threat assessment. This could change as demonstrated in the author’s report.
c) The online and mainstream media could also serve as a corrective. However, at present the leading media not least the public broadcasters seem to view themselves as messengers of the dominant political orientation. This lack of plurality of opinions tends to stabilize the executive even when their actions threaten the existential interests of the nation, e.g. in case of a factual error of judgement.
Collateral Health Impacts
The following information was obtained from 10 eminent experts who were randomly selected (not representative) by the report’s author.
Fatalities: a) Due to limited availability of hospital beds and services, it is estimated that 2.5 million surgeries were delayed or cancelled that would have taken place in March or April. This could result in between 5,000 and 125,000 premature deaths. b) For the same reason, follow-up treatment for cancer, stroke, or heart attack patients, which number in the order of million(s) annually, were delayed or cancelled, resulting in the possibility of avoidable death of up to several thousand patients. c) The quality of long-term care homes and services with 3.5 million recipients has declined; a concrete estimate of fatalities is not feasible, yet even a tenth of a percent impact would result in 3,500 premature deaths. d) The current annual average of 9,000 suicides will increase due to long-term impact on living conditions that could become critical for psychologically unstable persons. Additional suicides also have to be expected due to personal bankruptcies and destroyed livelihoods, as well as emotional pressures for specific professional groups that are most affected by ongoing change. e) An unspecified number of acute heart attack and stroke sufferers will not receive timely treatment resulting in death or reduced life expectancy in the short- or long-term.
Other health and psychological damage from: a) isolation experienced by elderly long-term care patients; b) persons with psychoses and neuroses requiring treatment; c) domestic violence and child abuse; d) broad-based communication disorders, e.g. due to mandatory wearing of face masks.
A long-term reduction in life expectancy is likely to become the greatest harm from this crisis. The decline arises from reduced general prosperity and wellbeing.
As you can tell, the leaked BMI report convincingly argues for a comprehensive risk assessment and holistic crisis management rather than the current tunnel vision focused on virology and acute medical concerns around COVID-19. The report’s summary does not engage with the actual threat of the novel coronavirus, which I hasten to add is a serious illness that has caused deaths and individual hardship around the world. However, viewed at the population level, the report’s assessment is in line with a growing number of international experts who demonstrate that the threat of COVID-19 is no worse than a severe influenza cycle.
Our political decision-makers and public health officials would be well advised to conduct continuous (re)assessments of the lockdowns and other emergency response measures in comparison to their collateral damage, and inform the public of the outcome of these assessments. As a geographer, I am particularly interested in the fact that there is strong spatial clustering of confirmed COVID-19 cases and attributed fatalities, which suggests geographically specific responses. As a data scientist, I am puzzled by the high degree of uncertainty in all coronavirus-related datasets and the multitude of interpretations that each time series generates. In addition to the ongoing medical and epidemiological research there will be many more topics to study if and when we are able to leave this crisis behind us.
The COVID-19 lockdown has brought with it an abundance of online professional development opportunities – a welcome escape from the terrors caused by the novel coronavirus (or by the house arrest and social distancing regime itself, if you concur with my view ;). On April 29, cartographer Daniel P. Huffman of Madison, Wisconsin, organized “How to do Map Stuff: A Live Community Sharing Event” with virtual workshops offered by volunteers from around the world, see https://somethingaboutmaps.wordpress.com/2020/03/19/how-to-do-map-stuff/.
Along with several interesting presentations, I listened in to Minnesota-based cartographer Ross Thorn, who went through the process of “Creating an Interactive Fantasy Map” using QGIS and MapBox. The recording is now posted on Youtube at https://www.youtube.com/watch?v=2nmLibB3lGs (starts around minute 9:30). Rather than create a set of islands from scratch, Ross “floods” a digital elevation model (DEM) so that mountains or hills turn into islands while lower elevations are transformed into the open seas… The remainder of that tutorial focused on vectorizing the island boundaries and adding land-use polygons as well as settlement locations with attached information.
During the April 29 live session, a chat participant asked whether the original elevations could be preserved as terrain on the islands. In this post, I would like to show how this can be done and how the result become an interactive 3D map within the QGIS and Web environment. I am using QGIS 3.4.12 and QGIS 3.10 with the Qgis2threejs plugin. The plugin does not correctly install on my Windows 8.1 office computer, thus the second part of this post is completed using the newer Windows and QGIS versions on my laptop. Also, this is certainly not the first time someone has created a 3D fantasy map, nor the only way in which it can be done; it just happens to be the first time I was motivated to try this myself using one of the GIS tools I am familiar with.
The above screenshots show the PDEM displayed in QGIS using the default black-to-white gradient for increasing elevations. The Niagara Escarpment is visible in the south adjacent to the Greater Toronto Area, while the remaining high altitudes are all part of the Canadian Shield. I zoomed in to an area west of Lake Temiskaming near the eastern border of Ontario with Quebec.
A further zoom yielded an area with several distinct peaks above 500m in elevation. Also shown above is the symbology dialog to distinguish pixels by elevation above and below 500m and the resulting “islands”. Using the menu sequence Raster | Extraction | Clip Raster by Extent | Use Canvas Extent | Save to File “PDEM_Escape.tif”, I clipped the province-wide DEM to the area shown. I renamed the new layer and used copy & paste to apply the same blue-red style from PDEM_South.
Under layer properties, you can view a histogram of raster grid values. The above screenshot is zoomed in to values above 500m to get a sense of their frequency distribution; I didn’t know what to expect, but the fast decline of higher elevation certainly makes sense.
We now use Raster | Raster Calculator for what is the key “contribution” of this post. In his tutorial, Ross used the following formula to set cells with elevation below the threshold (here: 500m) to zero (= water) and cells above threshold to one (= land):
Here, we do not want to condense the higher elevations to a categorical value representing land, but keep them as land elevations above the new “sea level” of 0. We achieve this by multiplying the values selected in the second term of the sum by the original elevation value, from which we subtract the threshold. Thus, while values up to 500m will be converted to 0m, the value of 501m will be converted to 1m (= 501m – 500m) and so on:
After completing the remainder of the tutorial, I realized that the configuration of my area’s elevations did not yield sufficient terrain variation. I went back to the current step to introduce a vertical exaggeration factor of 5. Therefore, the final raster calculation is as follows:
The following screenshot shows a colour scheme I created for the symbology property of the new LDEM_Escape5 layer, to allude to the different land cover classes that may be associated with increasing elevations, i.e. water, coastal sand, grasslands, forests, and bare rock. Another important change I made here is under Project | Properties | CRS tab, where you want to find and set “WGS 84 / Pseudo-Mercator” (EPSG:3857) to set the map units to metres instead of degrees (if that’s what it was before).
For the 3D version of our fantasy world, we will primarily use the raster dataset. However, we will also complete the instructions from Ross Thorn’s tutorial to create a vector dataset with the coastlines of our islands. The command sequence Raster | Conversion | Polygonize (Raster to Vector) turns the grid cells of the raster layer into square polygons. Unfortunately, cells with different elevation values on the islands will result in separate polygons, as shown in the first of the following screenshots (I clicked to select and highlight the large water polygon as well as a few small in-land squares for illustration). Ross did not have this issue, since all of his land pixels had the same value of 1 and formed contiguous polygons for each island. We will achieve this with the command sequence Vector | Geoprocessing Tools | Dissolve. This generates the situation shown in the second screenshot, with all land pixels combined and the water polygon removed. However, different islands are now all combined into one, multi-part polygon (I clicked to select only one island, which results in the highlighting of all land areas, since they are part of this multi-part feature). We now use Vector | Geometry Tools | Multipart to Singleparts in order to separate the land mass into independent entities, as shown in the third screenshot where a small island in the northwest is highlighted without also selecting the remaining islands. After adapting the symbology and project background colour, and adding a text field with a few island names for labelling, we achieve the status shown in the fourth screenshot below.
Our last steps in QGIS include making the island polygon fill transparent and give its borders a sand colour. For island labelling, I selected the three islands that actually had a name assigned and used right-click on the layer name | Export | Save Selected Features to create a new Shapefile layer with only these three islands; otherwise, there would be a lot of NULL labels down the road (not in QGIS but in the 3D export). I also created two new point layers according to Ross’ video: one for named cities and another for a mountain peak. Labels are activated under each layer’s properties and I am using “buffers” in the label options to make the label text better visible. The end result is shown in the following screenshot.
At this point we are starting to work with the Qgis2threejs plugin, which will convert our 2D map into an interactive 3D scene that is exportable to the Web. As noted above, I had to migrate the project to my Windows 10 laptop using QGIS 3.10. To find the Qgis2threejs plugin, go to Plugins | Manage and Install Plugins and let the system fetch the latest plugins. In the search field, type “threejs” to find the plugin and install it. If all goes well, you should have a new item in the “Web” menu and be able to run the “Exporter” from there. The tool opens with all project layers available for display and customization.
Check to activate the (vertically exaggerated) island terrain layer (LDEM_Escape5) and right-click for properties. I enabled “Surrounding blocks” to extend the seas beyond the map canvas and deactivated “Build sides” so that the water level is a plane rather than a block. The default material setting to display “Map canvas image” drapes the 2D map from QGIS over the elevation model. While this is what we want for the topographic colour scheme, it does not work for the points of interest and labels, which we’d rather turn into 3D objects. The QGIS window underneath the plugin window is still actionable and we thus uncheck the visibility of the places, mountain, and island names layers (see background/left side of the following screenshot).
So for example, we see the places layer unchecked in the QGIS project/map canvas but checked in the Qgis2threejs Explorer. In the corresponding 3D layer properties, we set the object for cities to a box sized 400m x 400m x 100m (assuming you set a coordinate reference system with metres as the map unit, as outlined above). Under “Features”, I should have checked “All features” to ensure that points that aren’t included in the current QGIS map extent are still exported. Lastly, activating “Export attributes” creates the 3D “airborne” labels at a set height that you can see in the scene. All this is done for the cities, island labels (only names are visible, coastlines of this layer remain invisible but come from the other island polygon layer), and the mountain peak (also no object symbol, just the name/label).
Under File | Export Settings, you have the option to save the Qgsi2threejs settings if you need to close your session and load them to restore it.
I did not play with the other Explorer settings but proceeded straight to File | Export to Web, using a temporary directory, the “3D Viewer” template, and “Enable the Viewer to Run Locally”. The template “3D Viewer with dat-gui panel” may be of interest in other applications where controlling layer visibility and opacity is useful (try it!). The above screenshot of the 3D Web map shows our fantasy world from the northwest. A live version can be accessed in my Github repository at https://crinner.github.io/escape5/.
It is heartening to hear Ontario’s Premier Doug Ford explain that “we must listen to what the data tells us” about the threat of the novel coronavirus. Commitments from politicians to evidence-based decision-making are refreshing, even though it is well understood that the data (a plural word) do not actually speak to us, unless we ask the right questions of them. In the case of COVID-19, numerous analysts – myself included – have been playing with ways to visualize, interpret, and even predict the curves of confirmed infections, tests conducted, deaths, and cases resolved. Unfortunately, it is becoming increasingly clear that the underlying data are fundamentally flawed and should not be used for public information nor for executive decisions that drastically interfere with our freedoms to live a healthy life, move around, assemble, or conduct business.
number of fatalities case-fatality rate = ——————————— number of cases
The release of Ontario’s COVID-19 prediction models on April 3rd based on data collected up to the previous day, reported a high case-fatality rate of 2.1%, as 67 deaths were counted against 3,255 confirmed cases of the disease. In Italy, the same metric is pegged at a staggering 10% as of late March, i.e. one in ten infected are dying. This would explain Premier Ford’s characterization of SARS-CoV2 as “this terrible, terrible virus” and the widespread fear, as seen e.g. in my Facebook feed, of getting infected by the “deadly virus”. Media attention has recently turned to the “German exception” (New York Times, April 4th), where the case-fatality rate had been a low 0.2% in mid-March, although it has now risen to 1.6%. The key factor influencing the rate was identified as the extensive testing regime in Germany, which resulted in the detection of more mild cases of COVID-19 than elsewhere, and thus a lower ratio of fatalities to confirmed cases. In other words, if other countries conducted more tests they would also find more infected people with moderate, mild, or no symptoms at all, thereby reducing the ratio of fatalities to cases.
Our governments’ and epidemiologists’ main concern is the exponential growth of infections and the resulting need for hospitalizations and intensive-care beds. Like everybody else, I have been looking out for daily updates of confirmed infections and death tolls. Both have been growing exponentially in most countries worldwide and the proportion of people who know what a logarithmic scale is must have multiplied too. But there is a catch: infections are confirmed only among those who are tested, and the scarce testing resources in most countries are focused on health-care workers, hospitalized patients, and those with symptoms. Despite this focus, it was noted that confirmed cases are stabilizing at around 10% of those tested. In other words, the growth of COVID-19 cases could be due entirely, or in part, to the increasing number of tests conducted. And more speculatively, it is currently possible that the disease does not actually grow but that it is only the confirmation of cases among an already infected population that grows.
In addition to the case-fatality rate’s denominator being under-estimated, there are now increasing questions about the accuracy of its numerator, the death count. The April 6 report by the Italian COVID-19 Surveillance Group notes that 96.7% among 1,290 hospitalized “COVID-19 positive deceased patients” had one, two, three or more diagnosed comorbidities, including cardio-vascular diseases, diabetes, kidney failure, chronic lung disease, and/or several other severe illnesses. This raises the question of the causal effect of SARS-CoV2 on the “corona deaths”, or how many people actually die from COVID-19 as opposed to dying with COVID-19. The German infectious disease agency Robert Koch-Institut acknowledged that anyone who dies with a confirmed SARS-CoV2 infection is considered a corona death, irrespective of the cause of death. This would obviously result in a vast over-estimation of the COVID-19 mortality count and thus the virus’ deadliness. On the other hand, the case-fatality rate may also be under-estimated since we tend to relate the death count to the current case count instead of the lower case count from the earlier time when the deceased got infected.
All these issues suggest benchmarking the alarming COVID-related death counts against expected mortality. The web site “COVID-19 in Proportion?” does this for the UK, stating (as of April 7th) that “COVID-19 will be linked to around 3% of total deaths which number 172,384” for the year 2020. According to the latest cause-of-death data from Statistics Canada that I could find, about 8,500 people died of influenza and pneumonia in 2018, and another 13,000 died of chronic lower respiratory diseases. The total number of all-cause deaths in Canada was 283,706 in 2018, including 106,991 Ontarians. At the time of writing, Canada has 381 “corona deaths”, with 153 of those in Ontario. The fatalities therefore are in the order 0.1% of the expected annual mortality. A number of public health experts quoted by OffGuardian suggest that the impact of COVID-19 is no different from the annual flu. Reporting COVID-19 counts in context with a country’s overall mortality or the death counts of recent influenza cycles could go a long way in reducing the general sense of panic and distress caused by current news reports.
I admire lawyers for their ability to think through complex societal problems and succinctly outline a written argument. Numerous constitutional lawyers in Germany have now publicly argued that the extent of the COVID-19 response and the process by which it was instated, are out of proportion and therefore illegal. Quotes reported by the Swiss Propaganda Research project include the assessments that the German infectious disease law “cannot serve as a basis for such far-reaching restrictions of citizens‘ rights of freedom” and that “emergency measures do not justify the suspension of civil liberties in favour of an authoritarian and surveillance state”. The most pointed warning comes from a professor of public and ecclesiastical law in the context of the cancelled Easter masses and suggests that our “democratic constitutional state could turn into a fascist-hysterical hygiene state in no time”. At least one German lawyer, Beate Bahner of Heidelberg, is preparing a constitutional challenge of the federal and provincial corona bylaws passed on March 28. Her 18-page explanation (in German) of why the corona bylaws constitute the greatest legal scandal of post-war Germany is compelling.
Another lawyer, Viviane Fischer of Berlin, started an open petition with currently 69,000 signatures calling for a baseline study to generate a reliable database for public health decision-making in the coronavirus pandemic. The ongoing COVID-19 data issues noted in the petition include:
The inclusion of all corona-positive deceased in the official COVID-19 statistics, irrespective of their cause of death. The vast majority of fatalities had comorbidities and are not tested for other pathogens such as influenza viruses.
Tests are mostly limited to patients with COVID-19 symptoms, resulting in an inflated mortality rate. Conversely, untested asymptomatic infections have resulted in an unknown number of people who are now immune to the virus.
Duration of infectiousness and mechanics of transmission are yet to be confirmed.
To summarize this post, the COVID-19 crisis presents a learning opportunity for science and social science students regarding the benefits and pitfalls of statistical data analysis and modelling. But unfortunately, hasty data collection and analysis in the context of this pandemic is having serious implications on our livelihood. The issues at hand concern data classification (what is a “corona death”?), data normalization (how to benchmark the death count or confirmed infections?), and data modelling (how to predict a disease when the underlying data are inaccurate, possibly by orders of magnitude?). In Canada, the National Post is the only major newspaper, in which I have so far found two critical articles: “The mystery behind the true COVID-19 death rate” (March 31, reprinted from the Financial Times) and “COVID-19 modelling numbers are scary. Have we mortgaged our future on an inexact science?” (April 8). In addition, an opinion piece in the Hill Times posits that “It’s time to talk about a COVID-19 exit strategy” (April 2). We need more critical journalism and a broader range of perspectives – from health sciences and statistics to social studies, economy, politics, and philosophy – to scrutinize and guide our governments’ COVID-19 response. In other words, calling STEAM* superheroes to the rescue!
*STEAM = the integration of Arts with Science Technology Engineering and Math (STEM)
Do not use choropleths for your COVID-19 counts, ever!
In a hilarious contribution to Medium, Dr. Noah Haber et al. issued a call to “Flatten the Curve of Armchair Epidemiology“. They analyze the transmission of “well-intended partial truths” about COVID-19 and caution of hidden “viral reservoirs throughout the internet”. To flatten this curve, they recommend fact-checking before posting and go as far as endorsing social-media distancing measures. As with general COVID-19 tips based on armchair epidemiology, misinformation can also be spread through the numerous COVID-19 maps that are widely circulating through the Web. In this article I want to focus on one particular instance of armchair cartography: wrongly mapping COVID-19 count data using choropleth symbology.
Choropleths are great-looking maps, my favourite thematic map type! They use graduated colour schemes to fill areas (the spatial units of analysis) to represent the magnitude (usually in ranges) of data collected for, or aggregated to, these units. But they can be deceptive in many ways, one of which arises from using raw-count data without adjusting for the different sizes of the spatial units. The above gallery of cartographic failures shows a small selection of misleading choropleth maps of COVID-19 cases published by major government and news media Web sites as of March 26, 2020.
Representing raw-count variables using choropleth mapping is a mistake that is notoriously difficult to explain. In “Mapping coronavirus, responsibly“, Dr. Kenneth Field notes the need to normalize raw COVID-19 totals to account for different underlying population sizes of China’s provinces. But in a related debate on Twitter, Dr. Stephanie Tuerk, a Senior Data Visualization Engineer at Mathematica, pointedly asks: “Can you further articulate the problem with using a choropleth to display counts? What precisely will people misunderstand?” She also questions the recommendation to transform count data into normalized rates, if the goal is to map the original counts. Indeed, I tell my cartography students that normalizing their data (by area, total population, or another reference total) will create a new variable and they need to think about whether that’s what they actually want to visualize.
The best explanation that I have seen as to the actual reason for the misrepresentation of raw-count data through choropleth maps was written by GIS Consultant and former Harvard Lecturer Paul Cote under the heading “Effective Cartography – Mapping with Aggregated Statistics“. Using the schematic figures shown above, Paul underlines our cognitive ability to understand quantity from graphics that vary in one dimension (size), such as in proportional symbols, in contrast to how we read intensity from colour (lightness, value), such as on choropleth maps. It appears that we are wired to understand a choropleth map as a representation of an intensity (e.g. population density per sqkm, infection rate per one million people), not as a count, and therefore this map type does not fit with raw-count data.
The cartography textbook by Dr. Terry Slocum et al. (2009) proposes an additional explanation. They note that we read information from a choropleth map as the probability of encountering a phenomenon. For example, if we look at Google’s world map of COVID-19 cases, China’s 80,000 cases put it in the highest class (dark blue). We’d therefore expect to be exposed to many infected people if we were to travel around that country. Conversely, we’d expect to find fewer cases in Canada, since this country’s 4,000 cases are mapped two classes lower (medium blue). Assuming we run into comparable numbers of people given space-time constraints (but ignoring current travel restrictions!), this is a wrong conclusion since Canada’s COVID-19 infection rate of 103 cases per one million population is roughly twice as high as China’s 53 (March 26 data from https://www.worldometers.info/coronavirus/#countries).
It is important to note that this issue does not automatically occur on every choropleth map or between any two spatial units on a given map. In fact, I had a hard time finding a suitable pair of provinces or countries, in which the relationship between raw counts was inverted compared to that between normalized data. Yet, the possibility of this issue is what makes the choropleth map a no-go for visualizing total counts.
The above example also highlights another serious issue of the choropleth technique: It maps each value homogenously across its entire spatial unit, while in reality many phenomena are unevenly distributed within the units. Infectious disease is a good example of a phenomenon that produces highly localized clusters (China’s city of Wuhan, Italy’s Lombardy region, Germany’s Heinsberg district), which are poorly represented on any choropleth map that uses data aggregated to larger spatial units. The coronavirus pandemic demonstrates that improper cartography is not just an academic concern but can have serious real life implications – on public attitudes and even on policy decisions!
Why Germans are more concerned than most about a COVID-19 lockdown
I have never been a supporter of Germany’s conservative parties but their leader, Chancellor Dr. Angela Merkel, is making German politics great again, at least seen from across the Atlantic. In a rare, televised address to the nation on 18 March 2020, Dr. Merkel urges her “dear fellow citizens” to voluntarily practice the hygiene and distancing measures recommended by public health authorities. At the time, there were some 12,000 confirmed COVID-19 cases and 28 deaths in Germany.
Dr. Merkel’s speech can be seen as a last attempt to avoid enforcing stricter isolation rules. There is a unison of voices from politicians, epidemiologists, and the public calling for the “total shutdown” of society to stop the coronavirus spread, both in Germany and over here in Canada. Merkel however conveys a deeper understanding of the risks of social isolation. She characterizes COVID-19 as the greatest challenge faced by Germany since WWII – not in general terms, as was wrongly reported, but in terms of a challenge that requires every single person’s solidarity and commitment to flattening the curve. Merkel acknowledges the degree to which limitations on non-essential activities are already invading not just our personal lives but our understanding of a democratic society. She refers to her upbringing in totalitarian East Germany and the struggle to fight for the freedom of movement that is now effectively being withdrawn. She established that “such restrictions can only be justified if they are absolutely imperative” and “these should never be put in place lightly in a democracy and should only be temporary.”
Fast forward five days to March 22nd and approaching 25,000 COVID-19 infections and 100 deaths, Germany’s federal and provincial governments agreed on a contact ban, but still did not impose a general curfew. Citizens are free to leave their homes for any purpose as long as they keep among their co-habitants or stick around with no more than one other person. In a commentary entitled “The Other Danger“, Die Zeit journalist Christian Bangel acknowledges that Merkel did not take the easy route. He views her speech as a reminder of what is at stake, reminder to those who call for more drastic measures. Bangel, also born in East Germany, notes how many people who usually lament Germany’s culture-of-prohibitions (“Verbotskultur”), e.g. when it comes to taking climate change action, now call for lockdowns and celebrate the Bavarian premier for jumping the gun with a province-wide curfew. Bangel cautions against the collective-conformist effect of the coronavirus panic, when we forget the difficult balance of freedom and safety in our democracies. He asks what restrictions on civil liberties will be acceptable in the next crisis situation? Accepting such restrictions out of ease and convenience reminds me of how we willingly trade privacy for the convenience of digital services. Bangel concludes that in addition to fighting the virus we also need to fight against complacency and an attitude that views civil rights as a burden for public health and wellbeing.
Germany has learned from two totalitarian regimes in its not too distant past, and Dr. Angela Merkel, the Leader of the Free World according to some, set the tone for a thoughtful, measured pandemic response. Maybe that’s what you get with a conservative, female leader who boasts a doctoral degree in physical chemistry. Merkel shows great empathy when she thanks supermarket cashiers and warehouse employees for keeping things going (“den Laden am Laufen halten”, akin to the expression “the show must go on”) and is cited with the frustration over keeping families from enjoying the sunny spring weather if confined to their homes. In addition to the political dimension of the crisis, I expect that we will also see broader public health issues from a wide-spread sedentary life style under coronavirus lockdowns. Our mental health will be challenged to say the least. And the expected increase in domestic violence is a real danger, too. I therefore hope that other leaders will take a page from Dr. Merkel’s book and avoid full lockdowns or clearly limit them in duration, plus justify them in the context of democratic standards and civil liberties.
To be clear, I am not suggesting to take the coronavirus pandemic lightly or disregard public health guidelines, rules, and laws. I do argue to take a step back and not call for hasty political decisions in a panic. Some experts even recommend “social-media distancing” to “Flatten the Curve of Armchair Epidemiology“! Let’s consider the possible longterm impacts of our response and ensure that we as individual citizens can continue to monitor our authorities’ actions rather than be locked out of decision-making. But ultimately, a slowing of economic and social life under COVID-19 may not be such a bad thing, for nature and humans alike.
Why studying Applied Geography is more important than ever
Today was going to be Ryerson University’s Open House for prospective students, those already admitted for Fall 2020 as well as those considering a late application to our programs. The event was cancelled as a consequence of the distancing measures taken to slow the spread of the novel coronavirus. As undergraduate program director for the BA Honours in Geographic Analysis and past graduate program director for the MSA in Spatial Analysis, I would like to share some thoughts about why it is now particularly important to recruit bright students into Geography programs.
As you monitor the #COVID-19 news coverage, you can’t help but notice an abundance of maps and graphs. Many politicians and administrators refer to the importance of “the data” to make evidence-based decisions. The data in question are public health data – confirmed and suspected cases, recovered and deceased, tests completed, etc. – and as always, location information is a key component of these data. Geographic concepts such as distance, connectivity, clustering, and scale are at the very core of the issue, since the nature of an infectious disease such as COVID-19 is inherently spatial. But Geography is a meta discipline, its concepts apply across almost all areas of human activity. In addition to public health, it determines retail location decisions, financial transaction monitoring, environmental pollution and conservation efforts, crime pattern analysis, and transportation planning, to name only a very few examples.
Geography programs across North America are struggling to recruit students because it is notoriously difficult to explain our subject matter compared to seemingly clear disciplines such as psychology, outline career opportunities compared to say business or law degrees, and show its visible impact compared to e.g. urban planning. Therefore please pardon me for using the coronavirus crisis to explain the importance of recruiting some of our best high school students into Geography programs. Canada needs these graduates to take on some of the most important analyst, planner, and decision-maker roles in our society!
Geography at Ryerson is deeply committed to offering programs of study and courses that are directly relevant to today’s community needs. In the BA in Geographic Analysis and, at an advanced level, the MSA in Spatial Analysis, we teach technical skills and critical thinking for data analysis, visualization, and interpretation. This winter 2020, students in my course GEO641 “GIS and Decision Support” first used professional geographic information systems (GIS) software to identify areas for possible urban expansion in the Toronto region within the constraints of the Ontario Growth Plan. We then moved on to create indices of neighbourhood wellbeing in Toronto and visualize them in Esri’s Operations Dashboard product, the tool used by Johns Hopkins University’s Center for Systems Science and Engineering for their now-famous coronavirus map. The final lab assignment in my course is a web map to explore the United Nations Human Development Index, another real-world example of using GIS to address some of humanity’s greatest challenges.
Along the way, students learn about integrating disparate datasets, handling missing values, properly normalizing indicators, applying sound cartographic styles, and correctly interpreting the results. These are issues encountered in many of the “viral” visualizations of COVID-19, as discussed by Kenneth Field in “Mapping coronavirus, responsibly“. For example, my favourite Toronto newspaper, along with other news outlets and social media influencers, are still mapping global COVID counts using graduated colours (choropleth technique), which conveys false information about the spread of the virus and must not be used for decision-making. The world needs more geographers who are ideally positioned to tell stories behind the data and turn valid insights into proportionate action.
Some of the information collected for Esri Canada’s COVID-19 resource hub is sourced from another industry partner of Geography at Ryerson: Environics Analytics, a “leading data, analytics and marketing services company specializing in geo-demographic segmentation, site evaluation modeling and custom analytics” (https://environicsanalytics.com/). Environics Analytics provides $10,000 per year in scholarships to our students, attesting to the immense importance of geospatial technology training for their business and growing workforce.
Another example of the connection between Geography and Public Health is BlueDot, a research and consulting firm founded at Toronto’s St. Michael’s Hospital, just down the street from Ryerson. BlueDot was widely credited in the media for being one of the first organizations to warn of the novel coronavirus epidemic in China and the threat of its global spread. BlueDot conducts infectious disease modeling and monitoring using big geospatial data, geographic information systems, and artificial intelligence. About 20% of BlueDot’s staff as of early 2020 are Ryerson Geography graduates, primarily working in data engineering and software development, and BlueDot is currently seeking to expand these teams.
A university education in Geography goes well beyond the conceptual and technical competencies needed to analyze and interpret geospatial data in the workplace. Geographers are also equipped with critical thinking skills required to solve complex problems and understand the limitations of analytics. In the context of COVID-19, I notice concerning reports about the extent to which individuals are tracked using cellphone data (e.g. Germany, Israel), the use of drones for policing curfews (e.g. Spain), and general calls for drastic social isolation measures that could become politically dangerous and detrimental to our mental and physical health. Geographers know what is technically possible but also what is at stake, and are therefore among the few professionals that I would trust to balance decisive crisis response with concerns about its long-term implications. We need many more geographers to make the world a better place!
This past fall semester of 2019 marked my 15th time teaching our graduate cartography course. When I joined Ryerson University in August 2006, I had already taught MSA 9050 Digital Cartography at the University of Toronto for three years, in Fall 2003, 2004, and 2005. The course was part of the joint Master of Spatial Analysis (MSA) program between UofT’s and Ryerson’s Geography departments, and was also cross-listed with UofT’s graduate course GGR 1913H of the same title. The course had been taught by Byron Moldofsky, who retired as Manager of UofT’s GIS and Cartography Office in 2017, after 37 years of service as a staff member, and continues to be active as an executive member of the Canadian Cartographic Association and a free-lance cartographer.
Then, and now as SA8905 Cartography and Geovisualization, the course “introduces [traditional] cartographic principles and their application to the design of thematic maps with [modern] GIS software” – the words “traditional” and “modern” were removed from the Ryerson calendar course description at some point, without altering the core message. While the lecture portion has remained consistent over the years, heavily relying on three subsequent editions of Terry Slocum’s comprehensive textbook “[Thematic] Cartography and [Geographic] Visualization”, the approach to the hands-on lab component has changed significantly. Expanding on Byron’s design, the earlier iterations of the course saw students select a mid-sized Census Metropolitan Area (CMA), complete a series of weekly lab exercises using socio-economic data from the Canadian Census, submit one or two intermediate lab assignments and one or two reading summaries (later replaced by a map critique), and prepare a final lab project. One lab assignment let the student select, present, and analyze an issue of data normalization, classification, or colour choice. In 2004 in conjunction with a teaching technology grant, students chose their “good” map from the first assignment to turn into a web mapping application as the second assignment. The final project was a thematic atlas plate containing three or more maps portraying the student’s choice of Census data for the selected CMA. The final assignment also required a sketch map or editorial plan for instructor feedback during the term.
Through a series of annual changes to the evaluation scheme, the current set of assignments emerged, consisting of a map poster with two or three maps and a geovisualization project. The map poster is a logical extension of the atlas plate assignment, though students are now free to use any data for any geographic extent, making the assignment more suitable for students across all fields of study in the MSA program (business/retail, social/community, and environmental/physical). The range of topics and data sets being mapped has been impressive; these are the most recent poster topics from Fall 2019:
The map poster assignment includes an early proposal, students’ in-class presentation and discussion of a draft map poster, and final submission. Students are free to use the GIS software of their choice, and many also use graphics tools to finalize their posters. To ensure the student’s preparation for the map poster proposal, the lecture component of the course is now compressed into the first half of the term. This was also possible because most MSA students now enter the program with solid GIS and mapping skills, so that the lecture and textbook material usually serves as review rather than new information. Nevertheless, practice in examining data distribution, selecting adequate cartographic options, and creating “correct” and meaningful thematic maps is still sorely needed by most students who take the course!
Before we move on to examine the second major assignment, the geovis project, I would like to highlight some outstanding student work with respect to the map poster. To my knowledge, three SA8905 students have received external awards for their map posters:
Brad Carter, Broken Windows and Violent Crime in Philadelphia: 2nd place winner of the 2012 National Geographic Award in Mapping. Brad’s map poster also won Honorable Mention in the Student Maps Category of the Cartography and Geographic Information Society’s 39th Annual Map Design Competition.
Yishi Zhao, Earthquake Intensity and Population at Risk – California, USA (2006-2014): 2nd place winner of the 2015 National Geographic Award in Mapping.
Nebojsa Stulic, East Asians in USA – Demographic Trends of Diverse Population: winner of the Canadian Cartographic Association’s 2019 President’s Prize for excellence in student map design at the university level. Nebojsa’s map poster also won Honorable Mention for the Arthur Robinson Award for Best Printed Map in the Cartography and Geographic Information Society’s 46th Annual CaGIS Map Design Competition.
Several MSA graduates and “SA8905 alumni” have become part of what I call the Toronto School of Mapping, a loosely defined group of part-time mappers who use open data to create thematic maps for issues of public interest and distribute them via social media, whether as individual map images or as illustrations within write-ups such as blog posts. The blog by Jonathan Critchley at http://jonathancritchley.ca/ includes the three dot density maps from his Fall 2011 map poster, along with examples of his later work. Of note, Jonathan teaches our department’s Web Mapping course since he graduated!
Another former student, William Davis, became Data Analyst and Online Cartographer with the Toronto Star, Visual Journalist for Dow Jones Media, and finally Infographic Designer for Sun Life Financial. His personal blog, http://www.formerspatial.com/, contains numerous examples of his work, primarily interactive maps published in support of Toronto Star articles or on his own initiative. William also collaborates with another MSA graduate, Tom Weatherburn, on the award-winning mapping collective mapTO at http://www.mapto.ca/.
William Davis and yet another former SA8905 student, Michael Markieta, were the first exhibitors in the Student Gallery of the Ryerson Image Centre, who were neither photographers nor Image Arts students. Their three-week show “Geographies of Urban Form” in October/November 2015 abstracted the structure of global cities through skeletal maps of their road networks using OpenStreetMap data.
Some of the interactive maps by William Davis and others, as well as the pursuit of cartography as an art form by Davis+Markieta, are echoed in a second major course assignment introduced to SA8905 in Fall 2013 as a “Mini Research Paper” and then in Fall 2015 reconfigured as the “Geovisualization Project”. While the idea behind the research paper was to improve the students’ writing skills through a 2,000-3,000 word description of a web mapping or GIS automation project, the focus of the assignment quickly shifted from the write-up to a more in-depth technical experience. The geovis project expectations are to “develop a professional-quality geographic visualization product that uses novel mapping technology to present a topic of your interest”. This product, which can e.g. take the form of an online and/or animated map, digital or physical 3D model, or a story map, is accompanied by a tutorial published on https://spatial.blog.ryerson.ca/, in which the students provide enough information for others to be able to replicate the projects. The three grading criteria reflect whether the project is “cool, comprehensive, and compelling”.
The MSA curriculum structure has been consistent since the start of the program in Fall 2000 and due to resource constraints, our objective to add courses in topics such as programming and web mapping as well as the inclusion of advanced analytical software such as R and Tableau has been difficult to achieve. The SA8905 geovis project however provides each student with an opportunity to test their interest in, and develop or expand their skills with, one or more tools that are not formally taught in any MSA course. The following list of Fall 2019 geovis project topics states the technology in the project title or in parentheses; tools included Python, R, Tableau, CARTO, Mapbox, Esri Operations Dashboard, Esri Story Maps, ArcGIS Pro, and QGIS. This year, only one student created a physical (in contrast to digital) project; in other recent years, several students would select 3D printing, wood cutting, Raspberry Pi, or other “maker technologies” to create their final product. In addition to the geovis technology, students are also exposed to writing concise technical reports in the form of the tutorials created within Ryerson’s WordPress site.
The most noteworthy external recognition of an SA8905 geovis project assignment was for Melanie MacDonald’s “Geovisualizing ‘Informality’ – Using OpenStreetMap & Story Maps to tell the story of infrastructure in Kibera (Nairobi, Kenya)” (Fall 2017). As part of the project, Melanie led a one-week mapathon to add building footprints for an informal settlement in Nairobi, Kenya, to OpenStreetMap. She then created a story map (shown below and still available at https://ryerson.maps.arcgis.com/apps/MapTour/index.html?appid=a3bf9a5e2bd14fae85f07bf096cf25ae) to explain the background and mapping process. In addition, Melanie also created a line art print as a tangible project outcome “formalizing the informal”. At the 2018 meeting of the Canadian Cartographic Association (CCA), Melanie received the best student paper award for her presentation on this outstanding course project.
The final submission of the geovis projects also includes a departmental or public presentation event. In 2015, the Department of Geography and Environmental Studies together with the Ryerson Library’s Geospatial Map and Data Centre organized a GIS Day event that included speakers and an exhibit with SA8905 geovis project displays. In 2016 and 2018, students presented their geovis projects at the user conferences of our industry partner Environics Analytics with an audience of some 500 data analysts and marketing professionals. In 2017 and 2019, projects were presented in the GIS lab to a departmental audience, including undergraduate students as prospective MSA applicants. Photos and tweets from four events are shown below.
For other awesome geovis project examples, I recommend searching the tutorials at https://spatial.blog.ryerson.ca/ for keywords such as: acrylic, hologram, Lego, Minecraft, table-top AR, translucent maps; food aid, parking, polar ice cap, street art, and street grid. Without prejudice, these were some of the most “cool” (unusual, innovative) and/or “compelling” (high-quality) projects that I remember ad-hoc. The “comprehensive” grading criterion, which represents the scope of the project and the student’s level of investment has been very high for all students. In other words, I have been amazed by the results of this assignment year after year. They have become a display of graduate student engagement, hands-on learning, and professional development for the MSA program well beyond the cartography and geovisualization course.
Much like many economic, social, health, crime, and environmental data sets, election results have an important geospatial component. For the 2019 federal election, Canada was divided into 338 electoral districts, each of which is represented by a member of parliament. Consequently, thematic maps – usually representing the “first-past-the-post” winning party – are a typical part of news media coverage of the 43rd election. The following examples were found in select Canadian media outlets on the morning after the election.
Canada’s vast geographic expanse makes it difficult to show the entire country in a map that preserves its internal shapes and sizes as much as possible. Kudos to the Toronto Star for publishing #elxn43 results on a map with a suitable, appealing projection.
If you zoom to your local riding results, you may notice that this projection is not ideal for local areas. In the case of Toronto, the city is presented at an awkward angle due to the projection centre being located in the east-west centre of Canada, far to the west of Toronto. Since maps are primarily useful to examine general spatial patterns, not specific data points, I find that the properly presented overview map outweighs the issue with local zooming.
All other outlets that I checked do not live up to the Star’s standard. According to the copyright statement on the map, the Globe and Mail used the Leaflet interactive mapping library with an OpenStreetMap base layer. The provincial breakdown of riding results is helpful to illustrate the increasing divisiveness of Canadian politics, yet the use of a Mercator map projection is not just unappealing but further emphasizes the size differences between small left-leaning city ridings and large right-leaning rural ridings.
The Canadian Broadcasting Corporation (CBC) uses the US-based Mapbox “location data platform” with the same projection issue. A difference is that the Globe uses the actual riding boundaries including water bodies, while the CBC clipped the ridings at the shores – both approaches have their advantages and disadvantages.
Maybe it’s just the way it is integrated in the National Post’s, Toronto Sun’s, and Huffington Post’s web sites that makes the Canadian Press’s #elxn43 results map “ugly”. When I loaded these newspaper pages, the map defaulted to full extent including all of Ellesmere Island in the most northern reaches of Nunavut. While we normally don’t want to cut off relevant geographic areas from a map, in this case it makes the entirety of the map all the more … ugly.
Maps can be a “centre piece” not only during election time but for many important political discussions and decisions. The following tweet by Jean Tong and the Ontario Association of Geographic and Environmental Education sums it up nicely.
As I am teaching two cartography courses this semester, I was compelled to take a critical look at published #elxn43 maps. Nevertheless, I appreciate the media’s efforts to visualize geospatial data and make them navigable for their readers. In interactive mapping, some cartographic guidelines become blurred. Maybe this critique will further stimulate improved map-making and underline the value of higher education and applied skills in the field of Geography.