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2ND WAVE OF THE PANDEMIC (SEP TO NOV 2020)

Some additional statistical data presented in the table below, will help us explain why the Balkan countries appear to have some of the highest deaths per million from COVID-19, while the Scandinavian countries appear to have some of the lowest deaths per million.

Phases by Regions

Sub - RegionsRegionsAverage household size1 member2-3 members4-5 members6 or more membersAged 65 years or over
Western EuropeWestern Europe2,430,3%47,8%19,7%2,2%
Ex East Block (Central Europe)Eastern Europe2,628,5%45,8%21,6%4,2%
BalkansEastern Europe2,923,4%45,2%25,5%6,0%38,8%
GreeceWestern Europe2,625,7%49,2%22,6%2,5%36,8%
BalticEastern Europe2,431,5%48,3%17,9%2,3%37,4%
ScandinavianWestern Europe2,140,3%42,6%15,5%1,6%
Sub - RegionsRegionsGDP per CapitaInformal EmploymentLiving Conditions Index 2019Health Index 2019Care Home Beds per 1000Diabetes PrevalenceCardiovascular Disease deaths %Obesity Rate %
Western EuropeWestern Europe51.875 94,381,77,76,2%33,7%22,8%
Ex East Block (Central Europe)Eastern Europe18.50989,477,56,06,9%46,0%23,9%
BalkansEastern Europe9.89827,4%83,073,32,08,5%52,9%21,8%
GreeceWestern Europe20.33087,779,10,24,6%43,0%24,9%
BalticEastern Europe13.905 85,871,04,25,0%56,8%23,3%
ScandinavianWestern Europe61.814 96,3829,85,6%34,9%21,4%

Some of factors that can explain the high death per million scores of the Balkan countries are the following:

  • The high average household size (2,9), which may lead to domestic spread of the virus. 30% of households has 4+ members.
  • The significantly lower GDP combined with a high Informal Employment percentage, factors that may indicate that people in these countries cannot respect the government lockdown rules, as they need to go out to seek a job, let alone that they cannot benefit of the state financial help, as the government has no way to identify them.
  • Finally, the poor quality of the health system in the Balkan countries combined with high diabetes and cardiovascular disease prevalence, could also be responsible for the significantly higher deaths per million in this region.

Scandinavian countries, where deaths per million are much lower, can attribute this success to the low density of the population as well as the small household size (40% of the household are single households). Also, even though they have the highest number of elderly care home facilities, they seem to have protected them much more successfully, with the exception of Sweden, who had a very different approach during the first wave of the pandemic.

Mobility in November

0-10-20-30-40-60-50ItalySpainGermanyAustriaRomaniaBelgiumLithuaniaPortugalSwedenGreeceFinlandSloveniaNetherlandsIrelandUnited KingdomPolandSlovakiaLatviaSwitzerlandCzechiaFranceBulgariaHungaryEstoniaCroatiaLuxembourgUkraineMoldovaBosnia and HerzegovinaBelarusSerbiaNorth MacedoniaNorway

Another reason for the aggressive second wave from October onwards is the significantly lower mobility reduction rates compared to first wave. The maximum reduction of mobility in the second wave is that of Greece (57%), while in the first wave many countries had reached 70%. This is probably the result of less strict measures during second wave, without general lockdown measures.

Mobility vs Death per 1M November

Mobility vs Death per 1M November

The above graph presenting the relation between Death per 1M and Mobility, demonstrates a positive correlation that is: the higher the deaths per 1M Pop, the higher the mobility reduction. As strict measures such as lockdowns usually follow the pandemic rage. There is again a group of Central European and Balkan Countries which do not follow their trend, most probably for reason already discussed at the beginning of the section.