Configurations for low YLL rate.

Why was there considerable variation in initial COVID-19 mortality impact across countries? Through a configurational lens, this paper examines which configurations of five conditions—a delayed public-health response, past epidemic experience, proportion of elderly in population, population density, and national income per capita—influence early COVID-19 mortality impact measured by years of life lost (YLL). A fuzzy-set qualitative comparative analysis (fsQCA) of 80 countries identifies four distinctive pathways associated with high YLL rate and four other different pathways leading to low YLL rate. Results suggest that there is no singular “playbook”—a set of policies that countries can follow. Some countries failed differently, whereas others succeeded differently. Countries should take into account their situational contexts to adopt a holistic response strategy to combat any future public-health crisis. Regardless of the country’s past epidemic experience and national income levels, a speedy public-health response always works well. For high-income countries with high population density or past epidemic experience, they need to take extra care to protect elderly populations who may otherwise overstretch healthcare capacity.为什么各国在新型冠状病毒肺炎（COVID-19）疫情初期的死亡影响存在显著差异？本文基于组态视角，探讨五项条件的组态——公共卫生响应延迟、既往流行病应对经验、人口老龄化比例、人口密度以及人均国民收入——如何影响以寿命损失年（YLL，years of life lost）衡量的早期COVID-19疫情死亡影响。本研究对80个国家开展模糊集定性比较分析（fuzzy-set qualitative comparative analysis, fsQCA），识别出四类与高寿命损失年率相关的独特路径，以及另外四类可导致低寿命损失年率的不同路径。研究结果表明，并不存在单一的“通用方案”——即各国可遵循的一套统一政策。部分国家的防控失败各有其特殊缘由，而成功防控的国家也各有其独特路径。各国应结合自身情境采取整体性应对策略，以应对未来任何公共卫生危机。无论一国既往的流行病应对经验与国民收入水平如何，快速响应的公共卫生措施总能取得良好效果。对于人口密度较高或既往有流行病应对经验的高收入国家而言，需格外注重保护老年人群体，否则医疗资源承载能力将面临过度挤压的风险。