https://www.economist.com/briefing/2021/05/15/there-have-been-7m-13m-excess-deaths-worldwide-during-the-pandemic

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[                    ]
Modelling covid-19's death toll
There have been 7m-13m excess deaths worldwide during the pandemic

The rich world suffered relatively badly, but most of the dying has
been elsewhere

BriefingMay 15th 2021 edition
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May 15th 2021

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OFFICIAL FIGURES say there have been 55,000 covid deaths in South
Africa since March 27th last year. That puts the country's death rate
at 92.7 per 100,000 people, the highest in sub-Saharan Africa. It is
also a significant underestimate--as, it seems safe to infer, are all
the other African data on the disease.

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Over the year to May 8th the country recorded 158,499 excess
deaths--that is, deaths above the number that would be expected on
past trends, given demographic changes. Public-health officials feel
confident that 85-95% of those deaths were caused by SARS-CoV-2, the
covid-19 virus, almost three times the official number. The
discrepancy is the result of the fact that, for a death to be
registered as caused by covid-19, the deceased needs to have had a
covid test and been recorded as having died from the disease.
Although South Africa does a lot of testing compared with
neighbouring countries, its overall rate is still low. And the cause
of death is unevenly recorded for those who die at home.

South Africa is not particularly unusual in its levels of testing or
in missing deaths outside the medical system. Excess mortality has
outstripped deaths officially reported as due to covid-19, at least
at some points in the course of the epidemic, in most if not all of
the world. According to the most recent data, America's excess deaths
were 7.1% higher than its official covid-19 deaths between early
March 2020 and mid-April 2021.

Studies of such mismatches have proved illuminating in some
countries. For example, Britain saw excess deaths higher than
official covid-19 deaths during its first wave, but lower than the
official covid death rates in the second--an effect taken to show that
measures to stop the spread of covid had saved lives which in another
year would have been lost to other diseases, such as seasonal flu,
perhaps. Something similar was seen in France.

But the excess-mortality method has failed to provide useful or
robust global figures for the simple reason that most countries, and
in particular most poor countries, do not provide excess-mortality
statistics in a timely fashion. Global estimates have used the
official numbers, despite knowing that the figure--currently
3.3m--surely falls well short of the true total.

To try to put numbers on how much of an underestimate it is--and thus
on how great the true burden has been--The Economist has attempted to
model the level of excess mortality over the course of the pandemic
in countries that do not report it. This work gives a 95% probability
that the death toll to date is between 7.1m and 12.7m, with a central
estimate of 10.2m. The official numbers represent, at best, a bit
less than half the true toll, and at worst only about a quarter of
it.

As well as providing a new estimate of the overall size of the
pandemic, the modelling sheds light on the distribution of its
effects and on its overall course.

Unsurprisingly, most of the deaths caused by covid-19 but not
attributed to it are found in low- and middle-income countries. Our
figures give a death rate for the mostly rich countries which belong
to the OECD of 1.17 times the official number. The estimated death
rate for sub-Saharan Africa is 14 times the official number. And the
first-and-second-wave structure seen in Europe and the United States
is much less visible in the model's figures for the world as a whole.
Overall, the pandemic is increasingly concentrated in developing
economies and continuing to grow.

To create these global estimates of total excess deaths during the
pandemic, we drew on a wide range of data. Official counts of
covid-19 deaths, however imperfect they may be, are available for
most countries; they are shown in the top map on this page. So,
frequently, are data on the number of covid cases and the share of
covid tests that are positive. In general, if lots of tests are
coming back positive, it is a fair bet that many more infections are
being missed by a testing regime that is looking only at those
seeking medical treatment and those near them.

Boosting the gradient

In some places there have been seroprevalence surveys which show how
many people have detectable SARS-CoV-2 antibodies, a sign of earlier
infection. Other factors we thought might matter included the steps
governments have taken to curb the spread of disease--such as closing
schools--and the extent to which people moved around.

Demography matters a lot: more younger people typically means lower
death rates. So, we inferred, do less obvious factors such as systems
of government and the degree of media freedom. To take a specific
example, excess deaths in Russia are 5.1 times greater than official
covid deaths.

All told we collected data on 121 indicators for more than 200
countries and territories. We next trained a machine-learning model
which used a process called gradient boosting to find relationships
between these indicators and data on excess deaths in places where
they were available. The finished model used those relationships to
provide estimates of excess deaths in times and places for which
there were no data available. A description of our methodology and
the ways in which we tested it, as well as links to replication code
and data, are here.

We estimate that, by May 10th, there was a 95% probability that the
pandemic had brought about between 2.4m and 7.1m excess deaths in
Asia (official covid-19 deaths: 0.6m), 1.5m-1.8m deaths in Latin
America and the Caribbean (v 0.6m), 0-2.1m deaths in Africa (v 0.1m),
1.5m-1.6m deaths in Europe (v 1.0m) and 0.6m-0.7m deaths in America
and Canada (v 0.6m). In Oceania, with only 1,218 official deaths, the
model predicted somewhere between -12,000 and 13,000, the lower bound
reflecting the possibility that precautions against covid-19 had
reduced deaths from other causes.

The ranges for Africa and Asia are spectacularly wide. So they should
be. The data from which to make strong predictions are not available,
and in some places do not exist. Yet, wide as they are, they provide
a more reliable picture than official tallies. The 50% probability
ranges narrow considerably: 3.3m-5.2m for Asia, 0.8m-1.6m for Africa,
8.2m-10.5m for the world.

During 2020 deaths per day rose for 33 of 52 weeks. After a brief
lull at the beginning of 2021, they shot up to new highs, driven in
large part by the tragedy currently unfolding in India. Our model
suggests the country is seeing between 6,000 and 31,000 excess deaths
a day, well in excess of official figures around the 4,000 mark. This
fits with independent epidemiological estimates of between 8,000 and
32,000 a day. On the basis of the model it would appear that around
1m people may have died of covid-19 in India so far this year. Again,
this does not seem out of line with other estimates.

The Indian catastrophe will eventually abate, as lesser spikes have
elsewhere. But that does not mean that the global picture will
improve. Though the disease rises and falls in waves in any given
place--a first wave takes some of the most vulnerable and leads to
responses that lower spread, a second wave builds up when those
responses are loosened--the waves are not all in sync. That is why, to
date, the number of daily deaths worldwide has increased in ten out
of 15 months, including some, such as June and July last year, when
much of the rich world was between waves.

It is worth noting, though, that despite hitting the poorer parts of
the world harder than indicated by data on covid-related deaths, on a
per-person basis covid-19 really has been worse in richer countries.
For Asia and Africa, the average estimated deaths per million people
are about half those of Europe (including Russia). India is
comparable to Britain, at least for now.

This might sound surprising to Europeans, who have been in lockdown
for the better part of a year. How did people in these mostly poor
countries see less death despite frequently lacking interventions to
curb the spread of the virus and having less well-funded health care?
It seems likely that much of the answer comes down to age. If two
populations have the same level of health care, the one with more
elderly people will see more deaths. If demography were the only
difference, estimates of the way that the risk of dying from covid-19
infection varies with age suggest the disease would be 13 times more
deadly in Japan (median age 48) than Uganda (median age 17). Reliable
excess-mortality data tend to come from countries with older, more
vulnerable populations (see chart).

Low as they are in absolute terms, though, the death rates among poor
young populations are much higher than they would be for populations
in the rich world with similar age profiles. And for the elderly in
poor countries the outlook is clearly grim. South Africa has seen
120,000 excess deaths among those over 60.

The fact that a relative lack of deaths in developing countries seems
to be due to age, rather than anything else, has various
implications. One is that the virus is spreading easily among younger
people--a finding backed by seroprevalence surveys, which find far
higher rates of past infection in Afghanistan, India and elsewhere
than they do in Europe or America. This suggests lots of non-fatal
cases of disease, something which suggests that the problem of "long
covid" will be worse in these countries. It also means that the virus
is getting plenty of opportunities to mutate.

There is an exception to this story. In some countries in South-East
Asia, deaths seem remarkably low, at least so far. This is not an
artefact of the model: excess-death data for Malaysia and Thailand
have hardly risen at all. It is possible that people there benefit
from "cross-immunities"--a level of protection against SARS-CoV-2
conferred by past infection by other viruses circulating in the
region. Unfortunately, though, there are signs that the figures are
now mounting (see Asia section).

The Economist's global excess-death-toll estimates are, as far as we
know, the first of their kind. They are not the only way to infer the
total number of deaths due to covid-19. On May 6th the Institute for
Health Metrics and Evaluation (IHME) at the University of Washington
published the results of a simpler model which applies fixed
multipliers, mostly based on test-positivity rates, to official
covid-19 death tolls in different countries and territories. This
methodology often provides numbers which fail to match reported
excess deaths. For example, IHME estimates that there have been
100,000 covid-19 deaths in Japan, far more than have been reported,
but the excess-death figure for the year to March 2021 was -11,000.

However they are made, estimates are no substitute for data, notes
Ariel Karlinsky, a statistician at the Kohelet Economic Forum, an
Israeli think-tank, who as leader of the World Mortality Dataset
project has collected many of the excess-mortality data on which The
Economist's model relies. Only by better tracking of mortality in
poor countries can estimates of the death rate be improved. Resources
should be put into such measures not just to honour the dead and the
truth, but also because, without such basic numbers, estimates of
other impacts--economic, educational, cultural or in the health of
survivors--are hard to understand, or to compare. #

Dig deeper

All our stories relating to the pandemic and the vaccines can be
found on our coronavirus hub. You can also listen to The Jab, our
podcast on the race between injections and infections, and find
trackers showing the global roll-out of vaccines, excess deaths by
country and the virus's spread across Europe and America.

This article appeared in the Briefing section of the print edition
under the headline "Counting the dead"

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