Karin Bojs: Reality data shows how covid-19 spreads



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Today, there is reality data and a much clearer picture, compared to this spring, of how covid-19 really spreads.

A couple of weeks ago, information came from 98 million US cell phones about how the pandemic has spread in North America.

On Thursday, the journal Science published a study from Hunan in China, based on infection tracking chains of 1,178 covid-infected people and their 15,648 closest contacts.

Traces of infection in many countries, not least in Sweden, have emerged similar chains since the covid outbreak began, but this week’s study from Hunan is the most comprehensive ever published.

Today there are many studies which is based on reality: in the community, in hospitals, in laboratories … And of course there are the theoretical models.

Models are an important tool for decision makers. But they can never be better than your input data. Because the sars-cov2 coronavirus is a new and untested virus, models have often shown complete error.

For lack of better knowledge, model builders have included all kinds of prerequisites. For example, they have assumed that covid-19 works in the same way as the flu virus. But covid-19 differs from influenza in several crucial ways: Children are affected to a lesser extent and generally milder, and they don’t seem to drive infection in the same way. And the covid infection does not spread as evenly in society as the flu virus usually does.

This week’s big study from Hunan, previous findings confirm that a small group, only 15 percent of those infected, accounts for almost all transmission (80 percent of patients are infected with these “super-spreaders”).

Of course, both the US mobile phone study and the Chinese infection chain study have their limitations.

The mobile phone study could not include homes and workplaces, which are known access points, or public transportation (which appears to drive infection to a lesser extent).

However, what Jure Leskovec and his co-authors in the US were able to show is that restaurants with table service and alcohol spread infections four times more often than gyms, which in turn is slightly worse than gyms. hotels and simpler food service, which is worse than religious establishments, which is worse. than grocery stores …

And grocery stores in poor areas are spreading more infections than in wealthier areas, in line with the fact that COVID-19 affects socially disadvantaged people much more.

The Chinese study It takes place in Hunan between January 16 and April 3, and a large part of the period was dominated by the confinement. Most of the patients contracted the infection at home, from relatives with whom they lived. That risk quadrupled when the lockdown was introduced on January 25.

Both before and after the closure, people living together infected significantly more than they infected family members with homes elsewhere. Friends, or “social contacts,” as they are called in the study, were even more harmless (not even half the risk compared to living together before confinement, then a tenth the risk). Even a lower risk of infection meant random contacts in the city and meetings in the health sector.

An important insight from the Hunan study is that Covid-19 appears to be most contagious only in relation to the outbreak of the disease. Even before symptoms appear!

Today, the media and the internet are flooding of more or less qualified statements about how we should behave to avoid infections.

Among the most qualified votes is, of course, the Swedish Public Health Agency. And what Prime Minister Stefan Löfven has said about the gym and socializing in recent days at a press conference and in his speech to the nation is quite well founded, given the knowledge that exists.

Crowded taverns are probably more dangerous than airy gyms with few visitors. But myself, right now I avoid both sides, like most of my friends, no matter how sad and poor I feel.

Read more:

Karin Bojs: Do we have to sacrifice alcohol, dancing or cat?

Models show how difficult it is to have a pandemic

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