The Economist magazine in London has used a machine-learning approach to produce an estimate of 12 million to 22 million excess deaths - or between 2 and 4 times the pandemic’s official toll so far (see go./3qjtyge and ‘Global toll’). And one of the highest-profile attempts to model a global estimate has come from the news media. These efforts, from both academics and journalists, use methods ranging from satellite images of cemeteries to door-to-door surveys and machine-learning computer models that try to extrapolate global estimates from available data.Īmong these models, the World Health Organization (WHO) is still working on its first global estimate, but the Institute for Health Metrics and Evaluation in Seattle, Washington, offers daily updates of its own modelled results, as well as projections of how quickly the global toll might rise. And more than 100 countries do not collect reliable statistics on expected or actual deaths at all, or do not release them in a timely manner.ĭemographers, data scientists and public-health experts are striving to narrow the uncertainties for a global estimate of pandemic deaths. Some official data in this regard are flawed, scientists have found.
It is not as simple as just counting up each country’s excess mortality figures. Working out how many more is a complex research challenge. Records of excess mortality - a metric that involves comparing all deaths recorded with those expected to occur - show many more people than this have died in the pandemic.
But that figure is a significant underestimate. On 1 November, the global death toll from the COVID-19 pandemic passed 5 million, official data suggested. Last year’s Day of the Dead marked a grim milestone.
0 kommentar(er)
