The initial motivation of this work was to provide a near-real time visualization tool of the COVID-19 related mortality in Europe, highlighting the features of COVID-19 transmission dynamic, particular to help knowing whether a peak in daily mortality rate was reached, and whether mortality started decreasing.
The motivation of this work was to provide a near-real time
visualization tool of the COVID-19 related mortality in Europe,
highlighting the features of COVID-19 transmission dynamic, particular
to help knowing whether a peak in daily mortality rate was reached,
and whether mortality started decreasing.
In addition, we defined and estimated a set of indicators of the country-level daily mortality pattern, to enable further studies on the effect of lockdown measures, and their implementation (e.g., consequences of human mobility), on the course of this epidemic.
In addition, we defined and estimated a set of indicators of the
country-level daily mortality pattern, to enable further studies on
the effect of lockdown measures, and their implementation (e.g.,
consequences of human mobility), on the course of this epidemic.
These indicators were then used to identify clusters of countries sharing similar mortality patterns.
These indicators were then used to identify clusters of countries
sharing similar mortality patterns.
## Main results {-}
As per `r data_update_date`, in the `r length(european_countries)` countries
accounted for, the total number of deaths is now `r sttnd` for an
overall population size of `r sttpop`, representing a
As per `r data_update_date`, in the `r length(europe)` countries
accounted for, the total number of deaths is `r sttnd` for an overall
population size of `r round(ttpop/1e6)` millions representing a
cumulative death rate of `r sttcdr` deaths $10^{-5}$ inhabitants.
**The most affected countries are located in south-western Europe, at
the exception of Sweden**. Indeed, the cumulative death rate is
contrasted between these south-western European countries and the
others.
the exception of Sweden, Switzerland, and North Macedonia**. Indeed,
the cumulative death rate is contrasted between these south-western
European countries and the rest od Europe.
Low death rates are reported in Finland, the Baltic countries, Central
Europe, and south-eastern Europe. These countries are heterogeneous in
terms of socio-economic features. These differences are known to be
risk factors for the emergence of infectious diseases, e.g.,
tick-borne encephalitis. However, the effect seems to be reversed for
COVID-19, with higher risks in southwestern Europe. Other factors
related to sub-population connectiveness and vulnerability - with
respect to COVID-19, might be involved.
The highest values of mortality growth rate were met at the early
stage of the exponential growth of daily mortality rate. In Europe,
this coincided with the implementation of lockdown measures, with some
fluctuations around the lockdown date - probably depending on the
progressiveness of the preventive measures decided by the governments,
and their actual implementation by the populations.
terms of socio-economic features. For COVID-19, factors related to
sub-population connectiveness and vulnerability, might explain these
differences in disease incidence.
The lockdown dates represented pivotal times for the national daily
mortality trends, with the mortality growth rate decreasing
The highest mortality growth rates were met before the implementation
of lockdown measures, with some fluctuations around the lockdown
date - probably depending on the progressiveness of the preventive
measures decided by the governments, and their actual appropriation by
the populations. The mortality growth rate decreased
thereafter. Different situations were encountered after the first
mortality peak:
* **a continuous decrease in the mortality growth rate** after the
peak (Belgium, Italy, France, the Netherlands, Ireland,
Switzerland...): the daily mortality rate is continuously
decreasing, and now stands at a low level.
Switzerland...): the daily mortality rate continuously decreased,
and now stands at a low or very low level.
* the mortality growth rate increased again after the peak, and
eventually resulted in an increasing mortality rate before a rather
steep decrease. Spain and the UK met this situation, as well as
Portugal, Austria, and North Macedonia. A secondary peak was
observed in Bosnia and Herzegovina, where the daily mortality is now
low.
* the mortality growth rate increased again after the peak, possibly
resulting in secondary and further peaks: Spain, North Macedonia,
Portugal, Austria, Bosnia and Herzegovina, Turkey, Serbia, Kosovo,
Montenegro, Albania, Czech Republic, and Croatia.
Daily mortality rate has now reached a low level in most countries
(fig. \@ref(fig:decay)). However, it is sill at least 50% of the
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@@ -472,7 +452,6 @@ The geographical scope of the study is:
Liechtenstein was excluded from the study because of its small population size.
## Approach{-}
* Publicly available data sets (see section \@ref(data)) are used to
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@@ -486,7 +465,7 @@ Liechtenstein was excluded from the study because of its small population size.
## Cumulative death rate
In the `r length(european_countries)` countries accounted for^[List of countries (number of deaths in braces): `r collapse(nam = levels(Dfr$name), cnt = sond)`.],
In the `r length(europe)` countries accounted for^[List (number of deaths in braces): `r collapse(nam = levels(Dfr$name), cnt = sond)`.],
the total reported deaths is now `r sttnd` for an overall population size of
`r round(sum(country_data$pop)/1e3,0)` millions, thus representing a cumulative death rate of
