Honigsbaum Mark
Department of Journalism, City University of London, London, UK.
Interface Focus. 2021 Oct 12;11(6):20210029. doi: 10.1098/rsfs.2021.0029. eCollection 2021 Dec 6.
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.
自1918 - 1919年那场毁灭性的流感大流行以来，政策制定者们一直运用数学模型来预测流行病和大流行的发展进程，以减轻其最严重的影响。然而，尽管英国长期以来一直是预测性流行病学的先驱，疾病建模者在为政府应对新冠疫情提供建议的关键委员会中占据着有影响力的职位，但与1918年一样，英国对新冠疫情的应对是世界上最无效的之一。本文认为这种“专业知识的失败”是医学和政治自满以及过度依赖基于流感的疾病模型的结果，它运用医学史的视角来展示医学对新冠疫情的态度如何反映了1918年英国医学界的态度。我认为，我们不应寄希望于预防医学和统计技术来预测流行病的发展进程并在未来规定抑制措施，而是需要培养更深刻的形式来富有想象力地应对传染病爆发，要考虑到隔离的悠久历史以及大流行的实际经历。一个有用的出发点是认识到，虽然诸如R°等指标可能有助于计算病毒的繁殖率，但它们永远无法涵盖大流行的全部风险或其社会复杂性。
