Covid-19 update now also reports coronavirus cases and deaths as rates per million population. I’ve done some updated plots for confirmed case rates, reported death rates, and apparent case fatality rates (CFR). The latter are calculated simply as reported deaths per 100 confirmed cases using numbers on at 13.11 GMT on March 24. This may overestimate CFR for countries testing few people, or only people with symptoms (as in Switzerland), or may underestimate it when most cases are recent and deaths for those cases have not yet occurred.

The first graph shows leading countries for cases per million population. Switzerland is in second place with almost as many confirmed cases per million as Italy. I’ve excluded small countries and territories with populations of less than one million.  Otherwise, several small populations such as Iceland, Andorra and Faeroe Islands dominate the graph with rates 2- 5 times higher than Italy.

The second graph shows reported mortality per million population for the thirty leading countries. Italy and Spain have the highest rates, Switzerland is in 5th position. The third graph shows apparent case fatality rates. These may overestimate case fatality (if a lower proportion of cases are being identified through testing) or underestimate case fatality (in the early stages of the epidemic when most cases are very recent). Also, the worldometer dataset does not yet include today’s new cases and deaths for all countries.

The cross-sectional comparison at one point in time does not give any sort of correct comparison of the overall final impact of the epidemics across countries, since countries are all at different points on the epidemic curve. A number of websites are tracking trends with the time axis defined in terms of time since 10th or 100th case.

Now in 9th day of social distancing here in Switzerland. Schools and all shops apart from food, pharmacies and petrol stations are closed, gatherings of more the 5 people banned. Borders are largely closed, with only cross-border workers and others with urgent reasons allowed to cross. Papers are being checked for all except health workers (who have a fast lane) and delays of hours are being encountered. Streets are eerily quiet with little traffic.

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Looking at the COVID-19 statistics on day 3

I live just a couple of kilometres from the border of Switzerland with France, and last Monday evening the border was closed except for frontaliers (who live across the border from work) and those with urgent reasons.  We are now in day 3 of social isolation. All shops, social and fitness venues and schools are closed except for groceries, pharmacies and petrol. Gatherings of 5 or more people inside or outside are banned and everyone who can is asked to work from home. The regime in France is even more extreme, and you are required to fill out an online form to get permission for venturing outside, ie. to walk the dog.

I was looking at the Johns Hopkins website that tracks confirmed cases and reported deaths from COVID-19. It lists countries in descending order and I realized I had not seen plots of cases or deaths per capita, so I made some using the numbers there today. (i’ve not  shown San Marino separately to Italy, as it would dwarf Italy’s rates). Switzerland is the 4th highest country in terms of cases per 100,000 and 5th for deaths per 100,000 (after Italy, Spain, Iran and Netherlands).

Of course these rates are seriously influenced by rates of testing and diagnosis, and identification and reporting of deaths, and clearly some countries and regions are doing much more testing and case/death identification than others. The cross-sectional comparison at one point in time will also not give any sort of correct comparison of the overall final impact of the epidemics across countries, since countries are all at different points on the epidemic curve.

These numbers are all fast moving and the JHU website is not always as updated as the latest figures appearing in some media and government sites. But they are generally not far behind. Its interesting that the rates are much higher for Switzerland than France, but the social distancing regime in France is more draconian than here.

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Declining freedom in the world

Last week, Freedom House released its 2020 annual report on global freedom. The report documents trends in every region of the world of declining political and civil freedom: “In every region of the world, democracy is under attack by populist leaders and groups that reject pluralism and demand unchecked power to advance the particular interests of their supporters, usually at the expense of minorities and other perceived foes.”

The report compiles a freedom index for countries based on an average of two indices for political rights and civil liberties, composed of numerical ratings and descriptive texts for each country. The 2020 index adds to a time series for countries that extends back to 1972. I’ve used this time series in the past as a potential covariate for modelling or projecting causes of death such as organized conflict (see earlier post on projections). I’m also interested to see to what extent the time series upholds the view of Stephen Pinker that there has been sustained long-term improvement in both political rights and human rights globally and this will continue (Enlightenment Now, Chapters 13 and 14).

The graph below shows time trends for the number of countries falling into three broad categories of the freedom index, labelled as Free (green shades), Partly free (orange shades) and Not free (purple shades). The graph includes 185 countries. 11 very small countries with populations less than 90,000 in 2015 are not included.

Trends in numbers of countries by broad freedom category

The report’s methodology is derived in large measure from the Universal Declaration of Human Rights, adopted by the UN General Assembly in 1948. The index is based on the premise that these standards apply to all countries and territories, and operates from the assumption that freedom for all people is best achieved in liberal democratic societies. I list the components of the index below in this post.

The Political Rights index:

  • Electoral process (free and fair elections)
  • Political pluralism and participation
  • Functioning of government (policy determination, lack of corruption, openness and transparency)

Civil liberties:

  • Freedom of expression and belief
  • Freedom of association and organization
  • Freedom for trade unions and other professional or labour organizations
  • Rule of law
  • Personal autonomy and individual rights
  • Equality of opportunity and freedom from economic exploitation

Recent reports use numerical indices with range 0-40 for political rights and 0-60 for civil liberties. I’ve used the mapping of these to seven point rating scales (1-7) for consistency with indices for earlier years.  The categories Free, Partly Free and Not Free are based on the combined average of the PR and CL  ratings as follows:

     Freedom Index       Category                Upper subgroup     Lower subgroup

            1.0 to 2.5            Free                         1.0                              1.5 – 2.5

            3.0 to 5.0            Partly Free            3.0 – 3.5                   4.0  – 5.0

            5.5 to 7.0            Not Free                 5.5 – 6.0                  6.5 – 7.0

The graph above shows numbers of countries by these three categories (and also distinguishing two levels within each category defined as show in the third column above. The following graph shows the proportion of the global population in each category, by weighting each country score by its total population.

Trends in proportions of global population by freedom category

Over the last 14 years, 25 of the 41 established democracies have experienced declines in their freedom indices. This can be see in the diminishing width of the green zone from around 2006. Though there is a long-term trend of increasing global freedom until around 2005-2010, this trend has ceased and there are declining levels of freedom in the last decade. Comparing changes in the freedom index between 2015 and 2020, the gap between setbacks and gains widened compared with 2018, as individuals in 44 countries experienced deterioration in their political rights and civil liberties while those in just 24 experienced improvements. The negative pattern affected all regime types, but the impact was more visible near the top and the bottom of the freedom scale.

At the bottom of the scale, large countries like Russia and China are intensifying their suppression of domestic dissent and at the top of the scale many freely elected leaders are also taking steps to reduce existing human or political rughts. The Global Freedom Report notes that “such leaders—including the chief executives of the United States and India, the world’s two largest democracies—are increasingly willing to break down institutional safeguards and disregard the rights of critics and minorities as they pursue their populist agendas.”- The Freedom House Report goes into more detail about the trends and changes for individual countries in each region.

In the following graphs, I have plotted trends in the proportions of regional populations falling into each of the freedom categories. Because large populations dominate, and crossing one of the freedom thresholds will shift that entire population to another area, these graphs are more spikey than if I had plotted numbers of countries rather than people. For example, the large discontinuity in the purple sub-areas for East Asia and Pacific from 1977 to 1988 reflects the freedom score for China decreasing from 6.5 to 6 in that period. Similarly, the graph for North America shows the decrease in freedom from 2016 onwards in the USA with the index increasing one step from 1 to 1.5.

Finally, I also calculated a population-weighted average freedom score for regions and the world, shown in the following graph.  This also highlights the recent declines in freedom in most regions in recent years, but perhaps in a more comparative way than the regional plots above (where the population proportions relate only to the categories relevant to each region).

Is Pinker right that freedom is increasing and will continue to increase?  Maybe, he is taking a longer view than the last decade, and in the big picture there has been an overall increase in global freedom. But the reversal is worrying and may continue if populist responses continue to attack political and human rights, and humans increasingly turn away from evidence-based approaches to global issues such as pandemics, refugees, overpopulation, and the climate crisis.

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Climate change and the denial of reality

Greta Thunberg and Extinction Rebellion have been raising awareness of the urgent need to stop talking and start acting on global warming. The evidence that global warming is real and that it is human-caused is now overwhelming, but the public debate is regularly swamped by science deniers who in most cases clearly simply ignore or are ignorant of the evidence, and often are clearly clueless about how to assess evidence, or even what constitutes evidence.

The first illustration below, from a recent Economist issue, summarises the rise in average temperature across the earth’s surface in 2018 compared to the average for 1951-1980.

Many deniers claim that the current rising temperature is natural, resulting from ice age cycles or orbital variations of the earth. The graph below shows how current CO2 levels are dramatically higher and rising faster than in any interglacial period over the last half million years.

And our best climate models predict temperature rises associated with CO2 levels which match measured temperatures over the last 40 years. If the impact of CO2 is excluded from the models, it is not possible to explain the observed rise in temperature (see graph below).

Three recent studies published in Nature and Nature Geoscience use extensive historical data to show there has never been a period in the last 2,000 years when temperature changes have been as fast and extensive as in recent decades (1-3).

It had earlier been thought that similarly dramatic peaks and troughs might have occurred in the past, including in periods dubbed the Little Ice Age and the Medieval Climate Anomaly. But the three studies use reconstructions based on 700 proxy records of temperature change, such as trees, ice and sediment, from all continents that indicate none of these shifts took place in more than half the globe at any one time.

The Little Ice Age, for example, reached its extreme point in the 15th century in the Pacific Ocean, the 17th century in Europe and the 19th century elsewhere, says one of the studies. This localisation is markedly different from the trend since the late 20th century when records are being broken year after year over almost the entire globe, including this summer’s European heatwave. Major temperature shifts in the distant past are also most likely to have been primarily caused by volcanic eruptions, according to one of the three studies.

The oft-quoted 97% figure

In the last few days I have seen several articles quoting the claim that 97% of climate scientists accept that humans are causing global warming.  This figure actually comes from a 2013 article in Environmental Research Letters by Cook et al. titled “Quantifying the Consensus on Anthropogenic Global Warming in the Scientific Literature” (4). It actually estimated that among abstracts expressing a position on global warming, 97.1% endorsed the consensus position that humans are causing global warming”.  Not a per cent of scientists but a per cent of papers whose abstracts expressed a position. But the misquote has achieved the status of a universal factoid trotted out by those arguing that humans are causing global warming as well as climate sceptics, who point to 3% thinking it is not real means there is uncertainty.

A more recent review of abstracts from 2013 and 2014 (the_consensus_on_anthropogenic_global_warming) found that of 24,210 abstracts of papers on climate change, only five explicitly rejected human role in global warming. As two of these papers were by the same author, the final figure for scientists who publish on global warming and reject a human causative role is 1 in 17,352 or 0.006%. Almost certainly this percentage is even lower now as more evidence floods in every year. This is probably as close to unanimity as humans are capable of in areas of science that involve such massive amounts of data of different kinds.  Its probably approaching the level of unanimity among physicists and geologists about the shape of the earth. In that case, the evidence is also overwhelming but quite straightforward and accessible to anyone. I suspect the number of scientists publishing papers arguing the earth is flat is actually a real zero per cent.

The obfuscation and undermining of science

I recently commented elsewhere that the climate change denial is being fuelled by deliberate obfuscation and funding of deniers, politicians and right-wing think tanks, that is reminiscent of the way that tobacco companies set out to confuse and obfuscate the very clear scientific consensus. And I went even further to say that in both cases, the relevant industries knew the truth from quite early on but hid that.  After I posted it, I had some qualms. While I thought I was right, perhaps I was just remembering second hand comments and I should check my facts. So I did.

Cummings et al (6) have documented the evidence that the tobacco companies knew and for most part accepted the very strong evidence that cigarette smoking was a cause of cancer by the late 1950s. They and Brandt (7) also document how the tobacco companies’ response was to deliberately undermine the acceptance of the facts by funding research intended to obfuscate the debate about smoking and health and to manufacture controversy about the facts.

In the immediate post-war years – the dawn of the nuclear age – science was in high esteem. Scientific advances (the bomb, radar, computing) had played a major role in winning the war, and continued to transform everyday life with radio, TV, electronics and electrical labour-saving devices. The tobacco industry launched an unprecedented strategy to undermine acceptance of scientific results through funding research intended to undo and obfuscate what was known. In doing so it provided substantial funding to researchers and doctors who would work to confuse the public and more or less invented the modern conflicts of interest that are now such a source of contention in science, medicine, media and public policy. This strategy of producing apparent uncertainty in the science (which actually largely did not really exist) undercut public health efforts and regulatory responses designed to reduce the harms of smoking.

Following the publication by Sir Richard Doll and Austin Bradford Hill in 1952 of a definitive review American, German and British studies which showed smoking was an important cause of lung cancer, the major tobacco companies of the time commissioned a public relations company, Hill and Knowlton, to regain public confidence in the tobacco industry.

In 1954 the British Medical Journal published the first prospective results from the British Doctors Study set up by Doll, confirming that lung cancer rates were much higher in smokers, and increased with the amount smoked. Doll and Hill reported that smokers also had higher death rates from heart disease, chronic lung disease, and many other conditions and, in 1957, the British and Dutch were the first governments to accept officially that smoking caused lung cancer.

John W. Hill, Hill and Knowlton’s president at the time, said that denying the facts would not be enough as this would clearly be borne from self-interest. Instead, demanding more science was a better tactic. He suggested that the goal of the tobacco industry should be to build and broadcast a major scientific controversy which would convey the message that the health effects of smoking were not conclusively known. One way to achieve this end was to commission more research into the causes of illness. Hill proposed the creation of a research group which would serve a public relations purpose demonstrating the tobacco industry’s collective concern for the public. The Tobacco Industry Research Committee was founded. In an advert published in more than 400 newspapers across the United States, tobacco companies promised to explore the science of tobacco and to ensure consumer well-being.

A wide range of other industries have subsequently adopted similar strategies to invent scientific controversy to undermine public action to address known harms. While the tobacco industries have now conceded and accept that tobacco smoking causes cancer, respiratory and cardiovascular diseases, the fossil fuel industries and their supporters are doing their utmost to undermine acceptance of the evidence and consensus on global warming.

The Guardian recently documented the evidence that the fossil fuel industries’ own scientists were advising them in the 1970s that there was an “overwhelming” consensus that fossil fuels were responsible for atmospheric carbon dioxide increases (8). And a confidential report prepared for Shell found that CO2 could raise temperatures by 1C to 2C over the next 40 years with changes that may be “the greatest in recorded history”.  In 1990 Exxon funded two researchers, Dr Fred Seitz and Dr Fred Singer to dispute the mainstream consensus on climate science. Seitz and Singer were previously paid by the tobacco industry and questioned the hazards of smoking. Singer, who has denied being on the payroll of the tobacco or energy industry, has said his financial relationships do not influence his research (8).


  1. Neikom R. et al. No evidence for globally coherent warm and cold periods over the pre-industrial Common Era. Nature 2019, Vol 571, pp550-554
  2. Neikom R. et al. Consistent multidecadal variability in global temperature reconstructions and simulations over the Common Era. Nature Geoscience 2019, Vol 12, pp643-649
  3. Brönnimann S, et al. Last phase of the Little Ice Age forced by volcanic eruptions. Nature Geoscience 2019, Vol 12, pp650-656
  4. Cook J. et al. Quantifying the consensus on anthropogenic global warming in the scientific literature. Environmental Research Letters 213, Vol 8 (2), 023024
  5. Powell JR. The Consensus on Anthropogenic Global Warming. 2015, Vol 39(6). Available at
  6. Cummings KM, Brown A, O’Connor R. The Cigarette Controversy. Cance Epidemiol Biomarkers Prev 2007, Vol 16(6), June 2007.
  7. Brandt AM. Inventing conflicts of interest: a history of tobacco industry tactics. American Journal of Public Health 2012, Vol 102(1), pp63-71.
  8. Watts J, Blight G and Gutierrez. Half a century of dither and denial – a climate crisis timeline. Guardian Wed 9 Oct 2019.


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Gun ownership and gun deaths

Given recent events, I took a look at the data relating to gun deaths overall and the  extraordinarily high rates of mass shootings in the USA compared to the rest of the world. Despite President Trump blaming video games and mental disorders, the data show that the US has similar levels of mental disorders and usage of video games as other high income countries. What does stand out is the difference in levels of gun ownership.

Based on results from the Small Arms Survey 2018(see smallarmssurvey), there are 150 guns per 100 adults in the USA, compared to 8.7 per 100 adults 15+ for the rest of the world combined.

According to the Small Arms Survey 2018 results, there are one billion firearms in global circulation as of 2017, 857 million (85 per cent) are in civilian hands, 133 million (13 per cent) are in military arsenals, and 23 million (2 per cent) are owned by law enforcement agencies. Of the 875 million guns in civilian hands, 393 million of them are in the USA. In other words, 46% of all guns in civilian hands in the world are in the hands of US civilians.

A 2017 US survey (pewsocialtrends) found that 30% of American adults currently own a gun, 4 in 10 US adults say they live in a gun-owning household and 72% of US adults have shot a gun. Among gun owners, 66% own more than one gun, with an average of 6 guns per multiple gun owner. However this statistic is skewed by the 3% of gun owners who own half of all guns in the USA, with an average of 17 each. 38% of gun owners say there is a gun loaded and easily accessible at all times in their home. 26% say they carry their gun with them outside the home all or most of the time.

44% of US adults personally know someone who has been shot, and 23% say they or someone in their family have been threated by someone using a gun.

I was interested to contrast these figures with those for Australia, where gun laws were somewhat tightened after the Port Arthur Massacre. In 2017 there were 18 guns per 100 adults aged 15 and over. Around 6% of households have a gun, down from 25% in 1988 before the Port Arthur Massacre. Apart from banning semi-automatic and automatic weapons, a key part of the Australian gun regime is the requirement to register weapons. Registered owners are responsible for the use of weapons registered to them, and for example, must report loss or theft to the police. An estimated 88% of weapons in Australia are registered, compared with 0.3% in the USA.

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Latest data show accelerating rise in atmospheric carbon dioxide

Back in January, I posted on climate change (are-humans-heating-up-the-world) and included a graph of the Keeling curve showing the increase in atmospheric carbon dioxide concentration. The Mauna Loa Observatory in Hawaii has just released its latest results showing that atmospheric carbon dioxide concentration hit 415 ppm on June 3rd (two days ago). This is the second highest annual rise in the past six decades.

May is the most significant month for global carbon dioxide concentrations because it is the peak value for the year, before the growth of vegetation in the northern hemisphere starts to absorb the gas from the air. The seasonal peak and fall can be seen in the Keeling curve, named after Charles Keeling, who started the observations on Mauna Loa in 1958 because of its isolation in the Pacific Ocean.

As recently as the 1990s, the average annual growth rate was about 1.5ppm, but in the past decade that has accelerated to 2.2ppm, and is now even higher. This brings the threshold of 450ppm closer sooner than had been anticipated. Concentrations of the gas have increased every year, reflecting our burning of fossil fuels.

Scientists have warned for more than a decade that concentrations of more than 450ppm risk triggering extreme weather events and temperature rises as high as 2C, beyond which the effects of global heating are likely to become catastrophic and essentially irreversible on a human time scale.

The Scripps Institute of Oceanography has a video animation showing the dramatic rise in carbon dioxide concentration from the mid-20th century. The screenshot below from the video shows that the carbon dioxide concentration was below 300 ppm for most of the last three centuries but started to rise dramatically after World War II.

The video then zooms out to show the Keeling curve for the last 800,000 years putting the accelerating rise in atmospheric carbon dioxide this century in stark perspective. For the evidence linking carbon dioxide rise to global warming refer to my previous post.


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State-level trends and levels of child mortality in India 2000-2015

I’ve been involved for nearly 20 years in the estimation of global, regional and national causes of child death under the age of 5, in collaboration with academic researchers and a number of WHO technical departments (new-estimates-of-the-causes-of-child-death-under-age-5).  This collaboration has just published a paper in the Lancet extending this work to state level for India:

Li Liu et al. National, regional, and state-level all-cause and cause-specific under-5
mortality in India in 2000–15: a systematic analysis with implications for the
Sustainable Development Goals.

India had a population 1.35 billion in 2018 and the larger states are bigger than most of the world’s countries. If Indian states were countries, five of them would be among the 20 largest countries in the world. Uttar Pradesh is similar in size to Brazil or Indonesia, and Maharashra and Bihar are similar in size to Japan or Mexico. The map below graphically illustrates the size of Indian states by labelling them with the names of countries with similar population sizes.

The paper presents estimates and trends for causes of death in children under 5 in India  for the 23 of the 29 states, together with smaller states grouped into two categories. In 2015, there were 25 million livebirths in India and 1·2 million under-5 deaths (under-5 mortality rate 48 per 1000 livebirths). 0·7 million (58%) of these deaths occurred in the first month of life (neonatal period). This quite a contrast to the rest of the world, for which 45% of under 5 deaths occurred in the neonatal period, and India is characterized by a substantially higher proportion of deaths associated with preterm birth (25% of all under 5 deaths, see figure below).  Low birthweight deaths, as reported by the Million Deaths Study, were even higher, due to high numbers of deaths in full-term low birthweight babies.

The paper is the result of a collaboration between the Maternal and Child Epidemiology Estimation (MCEE) group, WHO staff, and the Million Death Study (MDS). The MCEE group, lead by Professor Bob Black and researchers at Johns Hopkins University, is funded by the Bill and Melinda Gates Foundation (MCEE).

India had the largest number of under-5 deaths of all countries in 2015, with substantial subnational disparities. The child mortality rates in 2015 ranged from 9.7 deaths under age 5 per 1,000 livebirths in Goa to 73.1 deaths per 1,000 livebirths in Assam. Overall, child mortality rates were lowest in the south and highest in the northeast of India. In 2015, India was ranked 158th out of 194 countries for child mortality. The graph below shows the rankings against countries of the Indian States, if they were treated as countries. Goa would have ranked 66th out of 218 “countries” and Assam 194th (or 25th worst).

Overall, the leading causes of under-5 deaths were preterm birth complications (0·330 million [95% uncertainty range 0·279–0·367]; 27·5% of under-5 deaths), pneumonia (0·191 million [0·168–0·219]; 15·9%), and intrapartum-related events (0·139 million [0·116–0·165]; 11·6%), with cause-of-death distributions varying across states and regions. In states with very high under-5 mortality, infectious-disease-related causes (pneumonia and diarrhoea) were among the three leading causes, whereas the three leading causes were all non-communicable in states with very low mortality.

India has made a sustained effort in recent years to increase vaccination coverage for children.  The national coverage for the first dose of vaccine against measles has risen from around 56% in 2000 to 88 % and that for the second dose of vaccine against measles from under 25% t0 77%.  Measles deaths in India have declined from around 90,000 in 2000 to 20,000 in 2017.

The number of child deaths under 5 reduced from 2·5 million in 2000 to 1.2 million in 2015,  yet despite this progress, India did not meet target 4 of the Millennium Development Goals (MDG 4) of a two-thirds reduction in under-5 mortality rate between 1990 and 2015.  In the post-MDG period the UN Sustainable Development Goals (SDG) target for child mortality is to achieve ≤25 under-5 deaths per 1000 livebirths and ≤12 neonatal deaths per 1000 livebirths by 2030. The paper concluded that ten major states must accelerate progress to achieve the SDG under-5 mortality target, while 17 are not on track to meet the neonatal mortality target. Efforts to reduce vaccine-preventable deaths and to reduce geographical disparities should continue to maintain progress achieved in 2000–15. Enhanced policies and programmes are needed to accelerate mortality reduction in high-burden states and among neonates to achieve the SDG child survival targets in India by 2030.

Annual rate of reduction (ARR) of U5MR, NMR, mortality rate among 1-59 month olds (PNMR) by state in India in 2000-2015 (Webappendix 11 of Liu et al, Lancet 2019).

If the average rate of decline in child mortality from 2000-2015 is sustained unchanged until 2030, how would the Indian States compare with the countries of the world in 2030?  The tables below show the change in global ranking (Indian States and other countries) for the five best and worst Indian States in 2015 and 2030.  The paper provides more detailed analysis of State-level trends in specific causes of child death to help identify areas where more efforts are needed to achieve the SDG target for child mortality for India.

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