While organizations such as the WHO, the CDC or Worldometers are releasing statistics on a daily basis regarding the COVID-19 pandemic, the data is not efficiently analyzed to provide useful information (let alone the media that are dedicated to comparing absolute figures instead of relative between countries, as if it were a horse race or a soccer match).
A new analysis that considers a good number of factors offers a much clearer map of the situation (with the precarious data that we have), placing Spain as one of the worst places in the world to experience this crisis .
Interrelated causes
Although simplistic analyzes indicate that in one country there are more deaths than in another because there is more aging population, the truth is that there are countless factors that can be taken into account and, above all, it is important to know how they interact with each other.
For example, in Spain there is an older population than in the United States, but in the United States there is more obese or diabetic population, which is also a handicap; or in Spain there are fewer inhabitants than in the United States, but in the United States its demography is distributed more in the form of a cluster, which reduces the probability of massive contagion, and so on indefinitely.
Not counting that in Spain there is a large aging population, but the same happens in many other countries where there are hardly any deaths from coronavirus, so we have to deduce that an aging population is only a negative factor in the abstract, but it is more or less negative in the concrete . A piece of data only makes sense if we know how it interacts with other data.
Currently, Spain is the country with the most deaths from the coronavirus pandemic in the world , in proportional figures taking into account its population.
If we do not know the causes, or they are far from being fully clarified, it is because the COVID-19 pandemic is a complex system that involves biology, human behavior, companies and governments, and is powerfully influenced by the health of its inhabitants, the economy , administration and geopolitics.
This is why Deep Knowledge Group (DKV), a Hong Kong-based think tank with European offices in London, has developed advanced analytical frameworks to analyze this data . Big Data analysis is applied to quantified and relevant parameters . These mathematical classification frameworks have been developed over the past five years for use in highly complex and multidimensional industries and domains, including artificial intelligence for the new drug discovery industry.
The results have been presented in the form of open source country rankings to help people and governments make informed decisions.
To conduct their analysis, a team of experts collected and analyzed data generated for 200 countries around the world. To communicate ideas in a practical way, the analysts developed a ranking system.
DKV establishes a score for each country out of a total of 1,000 points, and indicates the 40 safest states to live in the health crisis . Israel, Germany (both above 630 points) and South Korea are in the top three, while Spain is not even listed. Nor is Spain reflected in the list of the 10 countries with the most effective treatments against Covid-19, in a ranking led by Germany. Regarding European countries, DKV places Spain in the last place (33rd) of the safest countries.
Spain only has one appearance that could be considered flattering in the rankings prepared by DKV: it places it as the fourteenth place in the list of governments that are providing the most support during the crisis .
Let’s look at it in more detail.
Ranking of safest countries
The countries were evaluated using 24 specific parameters in 4 different categories :
- Quarantine efficiency
- Government management efficiency
- Monitoring and detection,
- Preparation for emergency treatment.
Risk ranking
Countries were benchmarked according to their risk levels according to a variety of medical and non-medical factors, including the risk of infection, hospitalization, death, and lasting health conditions, as well as the negative risk of country in economic, quality of life and geopolitical issues resulting from the pandemic.
It uses 24 specific parameters grouped into 4 different categories :
- Risk of spreading infection
- Government management
- Sanitary efficiency
- Regional specific risks
Treatment efficiency ranking
Countries were benchmarked according to how well they are monitoring the spread of infections, providing citizens with the tools and information necessary to manage non-critical cases at home without overloading the health infrastructure. The framework presents 24 parameters grouped into 4 main categories :
- Disease monitoring
- Disease management
- Emergency treatment
- New approaches to R&D treatment
To analyze Europe, the analysis was designed specifically for the unique circumstances present on the continent, including highly interconnected economies, high levels of the supply chain, tourist flow and the incidence of hotspots. In this ranking, Spain is in last place .
Government support ranking
Countries were benchmarked according to the scale, diversity, efficiency and effectiveness of their government’s efforts and measures to provide financial support (e.g. supplemental income, tax exemptions, subsidies, emergency loans, etc. .) to its citizens, companies (especially SMEs), freelancers and other interested parties.
The analysis revealed that some countries proved to be very effective in fighting COVID-19 early on. These countries focused on early prevention by implementing quarantine measures before the number of confirmed cases exceeded 50,000, and using efficient methods for treating hospitalized patients.
Naturally, this is a concrete data analysis, not the truth. As the months go by, better quality data will become available and more comprehensive analyzes will also be possible . DKV, wrong or wrong, has tried to make an approach based on many different factors, and therein lies its value: if we have to learn something from it, it is that we are facing a complex problem in which simple answers must be avoided and, above all, Manichean, political or partisan.