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Corona in Belgium

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I lost a couple of hours this afternoon when digging into the Corona virus data primarily triggered by reading this post at this site which offers a nice view on how to be aware of possible problems which can arise when collecting information and to be familiar with covert aspects and it likewise shows Belgium.

As a Belgian, I was interested to see how Corona may affect our lives in the next weeks and out of curiosity I was interested to see how we are doing compared to other countries regarding containment of the Corona virus outspread– specifically given that we still do not have a government in Belgium after elections 1 year ago. In what follows, I’ll be showing some charts utilizing information offered at https://github.com/CSSEGISandData/COVID-19( it supplies current stats on Corona cases). If you want to recreate this, pull the repository and just execute the following R code shown.

Data

Let’s see first if the information is exactly what is shown at our National Tv.

 library( data.table)
library( lattice)
x
x
x
x
x
x$ date
x
old=c(" date", "Country/Region", "Province/State", "Validated", "Deaths", "Recuperated"),
brand-new=c(" date", "region", "subregion", "validated", "death", "recovered"))
x region %in%c(" Belgium", "France", "Netherlands", "Spain", "Singapore", "Germany", "Switzerland", "Italy"))
x$ area
x
x subset( x, location %in%"Belgium" & validated> 1)

Yes, the information from https://github.com/CSSEGISandData/COVID-19 looks correct certainly. Same numbers as reported on the Belgian Tv.

date location verified death recovered
2020-03-01 Belgium 2 0 1
2020-03-02 Belgium 8 0 1
2020-03-03 Belgium13 0 1
2020-03-04 Belgium23 0 1
2020-03-05 Belgium50 0 1
2020-03-06 Belgium109 0 1
2020-03-07 Belgium169 0 1
2020-03-08 Belgium200 0 1
2020-03-09 Belgium239 0 1
2020-03-10 Belgium267 0 1
2020-03-11 Belgium314 3 1

Exponential variety of cases of Corona

Now is the outbreak really rapid. Let’s make some graphs.

What is clear when looking at the plots is that undoubtedly infections happen at an exponential scale except in Singapore where the federal government handled to entirely separate the Corona cases, while in Belgium and other European nations the federal government did not have the chance to isolate the Corona cases and we are now in a stage of trying to slow down to minimize the impact.

corona1

You can replicate the plot as follows

 trellis.par.set( strip.background=list( col="lightgrey"))
xyplot( validated ~ date|area, information=x, type="b", pch=20,
scales=list( y=list( relation="complimentary", rot=0), x=list( rot=45, format="%A %d/%m")),
design=c( 5, 2), main=sprintf(" Confirmed cases of Corona n( last date in this chart is %s)", max( x$ date)))

Compare to other nations– start

It is clear that the onset of Corona is various in each nation. Let’s define the day 0 as the day where 75 individuals had Corona in the country. That will permit us to compare different nations. In Belgium we started to have more than 75 clients with Corona on Friday 2020-03-06 In the Netherlands that was one day previously.

date area confirmed
2020-01-22 Hubei444
2020-02-17 Singapore77
2020-02-23 Italy155
2020-02-29 Germany79
2020-02-29 France100
2020-03-01 Spain84
2020-03-04 Switzerland90
2020-03-05 Netherlands82
2020-03-06 Belgium109

Reproduce as follows:

 x 75]), by=list( location)] 
x beginning beginning[order(onset$date), ]

Compare to other countries– what can we anticipate?

Now are we doing better than other nations in the EU. Following plot reveals the log of the number of individuals detected as having Corona since the start date shown above. It appears like Belgium has learned from the issues in Italy but it still hasn’t found out the method to More Here with the infection break out the like e.g. Singapore has actually done.

Based upon the blue line, we can expect Belgium to have next week between roughly 1100 validated cases (log(1100)=7) or if we follow the pattern of France that would be approximately 3000 ( log(3000)=8) patients with Corona. We hope that it is only the.

corona2

Reproduce as follows:

 xyplot( log( validated) ~ days_since_case_onset|"Log( verified cases) of Corona because start of ill individual nr 75", 
groups=location,
data=subset( x, days_since_case_onset>=0 &
location %in%c(" Hubei", "France", "Belgium", "Singapore", "Netherlands", "Italy")),
xlab="Days considering that Corona start (verified case 75)", ylab="Log of number of validated cases",
auto.key=list( space="right", lines=REAL),
type="b", pch=20, lwd=2)

Compared to the Netherlands

Now, are we doing better than The Netherlands? Offer the above pattern shown above, I can only hope everybody in Belgium follows the federal government standards as rigorous as possible.

corona3

Reproduce as follows:

 xyplot( newly_confirmed ~ date|"Recently confirmed cases of Corona", groups=location,
information=subset( x, location %in%c(" Belgium", "Netherlands") & date> as.Date("2020-03-01")),
xlab="Date", ylab="Variety of new Corona cases",
scales=list( x=list( rot=45, format="%A %d/%m", at=seq( as.Date("2020-03-01"), Sys.Date(), by="day"))),
auto.key=list( space="right", lines=REAL),
type="b", pch=20, lwd=2)


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