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 - Regions||Regions||Average household size||1 member||2-3 members||4-5 members||6 or more members||Aged 65 years or over|
|Western Europe||Western Europe||2,4||30,3%||47,8%||19,7%||2,2%|
|Ex East Block (Central Europe)||Eastern Europe||2,6||28,5%||45,8%||21,6%||4,2%|
|Sub - Regions||Regions||GDP per Capita||Informal Employment||Living Conditions Index 2019||Health Index 2019||Care Home Beds per 1000||Diabetes Prevalence||Cardiovascular Disease deaths %||Obesity Rate %|
|Western Europe||Western Europe||51.875||94,3||81,7||7,7||6,2%||33,7%||22,8%|
|Ex East Block (Central Europe)||Eastern Europe||18.509||89,4||77,5||6,0||6,9%||46,0%||23,9%|
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
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
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.