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Imagining pandemics now, and then: a century of medical failure

Ever since the devastating 1918–1919 influenza pandemic, policy makers have employed mathematical models to predict the course of epidemics and pandemics in an effort to mitigate their worst impacts. But while Britain has long been a pioneer of predictive epidemiology and disease modellers occupied...

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Detalles Bibliográficos
Autor principal: Honigsbaum, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504896/
https://www.ncbi.nlm.nih.gov/pubmed/34956597
http://dx.doi.org/10.1098/rsfs.2021.0029
Descripción
Sumario:Ever since the devastating 1918–1919 influenza pandemic, policy makers have employed mathematical models to predict the course of epidemics and pandemics in an effort to mitigate their worst impacts. But while Britain has long been a pioneer of predictive epidemiology and disease modellers occupied influential positions on key committees that advised the government on its response to the coronavirus pandemic, as in 1918 Britain mounted one of the least effective responses to Covid-19 of any country in the world. Arguing that this ‘failure of expertise’ was the result of medical and political complacency and over-reliance on disease models predicated on influenza, this paper uses the lens of medical history to show how medical attitudes to Covid-19 mirrored those of the English medical profession in 1918. Rather than putting our faith in preventive medicine and statistical technologies to predict the course of epidemics and dictate suppressive measures in future, I argue we need to cultivate more profound forms of imaginative engagement with infectious disease outbreaks that take account of the long history of quarantines and the lived experiences of pandemics. A useful starting point would be to recognize that while measures such as the R° may be useful for calculating the reproductive rate of a virus, they can never capture the full risks of pandemics or their social complexity.