A growing number of Swedish doctors and scientists are raising alarm over the Swedish government’s approach to COVID-19. Unlike its Nordic neighbours, Sweden has adopted a relatively relaxed strategy, seemingly assuming that overreaction is more harmful than under-reaction.
Although the government has now banned gatherings of more than 50 people, this excludes places like schools, restaurants and gyms, which remain open. That’s despite the fact that 3,046 people have tested positive. Although Norway has the most confirmed cases (3,066) in Scandinavia, COVID-19 fatalities in Sweden are highest by far (92), compared with Norway (15) and Denmark (41).
People now are taking sides, with some arguing that publicly criticising the authorities only serves to undermine public trust at a time when this is so badly needed. Others are convinced that Sweden is hurtling toward a disaster of biblical proportions and that the direction of travel must change. The truth is that of all these opinions, none is derived from direct experience of a global pandemic. No one knows for sure what lies ahead.
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In epidemics, prediction models help guide the choice of interventions, assess likely social and economic impacts, and estimate hospital surge capacity requirements.
All prediction models require input data, ideally derived from past experience in comparable scenarios. And we know the quality of such input data is poor.
Most current COVID-19 prediction models use data gathered from the COVID-19 epidemics in China and Italy and from past outbreaks of other infectious diseases such as Ebola, influenza and other coronaviruses (Sars and Mers).
But demographics and patterns of social interactions differ from country to country. Sweden has a small population and only one real metropolitan area.
Ideally, we’d need data from Sweden on the community spread of COVID-19, but this requires screening programmes that do not currently exist.
The little reliable data on COVID-19 in Sweden concerns hospital admissions and fatalities. This latter can be used to get a “poor man’s estimate” of community transmission, providing approximately how many fatalities occur among those infected.
But with a two-week lag between diagnosis and death, this a very blunt instrument with which to guide decision-making.