[Economy] Why have some places suffered more covid-19 deaths than others?

[Mr.Talha]

https://www.economist.com/finance-and-economics/2021/07/31/why-have-some-places-suffered-more-covid-19-deaths-than-others

 

 

Seventeen months into the covid-19 pandemic, plenty of questions about the catastrophe remain unanswered. It is still unclear how sars-cov-2 originated, for instance. Another puzzle is why some areas have had less destructive epidemics than others. Why has Florida had fewer deaths per person from covid-19 than the American average, even though restrictions there have been looser for longer? But researchers are getting closer to the “magic” variable: the factor that does most to explain variance in deaths from the virus. It turns out that this has little to do with health measures, climate or geography. Instead it relates to economics.

The huge literature on the determinants of covid-19 infections and deaths finds that many widely assumed relationships do not always hold in the real world. Everyone knows that the old are most at risk; but Japan, where 28% of people are over the age of 65 compared with 9% globally, has seen remarkably few deaths so far. Some studies suggest that places that had bad flu seasons before the pandemic suffered less since; but other researchers have called that conclusion into question. There is no consistent correlation between the toughness of lockdowns and cases or deaths.

Faced with these surprising results, a hunt has begun that is as morbid as it is nerdy. Wonks are searching for less obvious variables that do more to explain variation in deaths from covid-19. And so far the most powerful of them all is inequality—usually measured as the Gini coefficient of income, where zero represents perfect equality and one represents perfect inequality.
In a recent exercise Youyang Gu, a data scientist, ran multiple versions of a model that seeks to find correlations between 41 different variables and American state-level deaths from covid-19. Only three variables “consistently have non-zero coefficients”, he finds: inequality, po[CENSORED]tion density and nursing-home residents per person. And of those three, inequality has the biggest effect.

Look around the world, and it seems that Mr Gu may be on to something. Deaths from covid-19 have been lower in egalitarian Scandinavia (even in Sweden, which imposed few restrictions) than for Europe as a whole. France, where the Gini is 0.29, has seen far fewer excess deaths than neighbouring Britain, where it is 0.34. New York state has both extremely high inequality and a huge covid-19 death toll; Florida is less exceptional on both counts.

Few other researchers rank the variables in the way that Mr Gu does. Yet our survey of the dozens of papers investigating the determinants of the toll from covid-19 finds that inequality has consistently high explanatory power. A recent study by Frank Elgar of McGill University and colleagues, looking at 84 countries, finds that a 1% increase in the Gini coefficient is associated with a 0.67% increase in the mortality rate from covid-19. Another, by Annabel Tan, Jessica Hinman and Hoda Abdel Magid of Stanford University, looks at American counties. They find that the association between income inequality and covid-19 cases and deaths varied over 2020 but was generally positive; higher inequality tends to lead to more suffering.

There is a lot less research on the potential reasons behind this intriguing relationship. Three sound plausible. The first relates to pre-existing health. A study in 2016 by Beth Truesdale and Christopher Jencks of Harvard University found “modest evidence” of a link between higher income inequality and lower life expectancy. This may be because of what economists call a “concave” relationship between health and income: giving a rich woman an extra dollar in income probably improves her health by less than removing a dollar from a poor man harms his. People in worse health tend to suffer more from covid-19 (and indeed some other research has drawn links between inequality and pre-existing conditions that may aggravate the disease, such as obesity).