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From Nature – lengthy article:
Demographers, data scientists and public-health experts are striving to narrow the uncertainties for a global estimate of pandemic deaths. 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.
Among 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 one of the highest-profile attempts to model a global estimate has come from the news media. 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.nature.com/3qjtyge and ‘Global toll’).
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the true death toll of COVID-19 might always be disputed. “We still don’t know how many people died in the 1918 [flu] pandemic, but I always figured we would know pretty well how many people would die in the next one, because we live in the modern world,” Noymer says. “But we don’t actually, and that’s kind of sad for me as a demographer.”
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