感染致死率与社会接触矩阵对疫苗优先级排序策略的影响
Effects of infection fatality ratio and social contact matrices on vaccine prioritization strategies
AI总结：
该研究通过基于真实数据的仓室流行病模型，分析感染致死率与社会接触矩阵对疫苗优先级策略的影响，明确了不同流行病学场景下的策略有效性规律及相关影响因素。
摘要：
有效的疫苗优先级排序策略对于减轻烈性传染病的影响至关重要。我们利用基于不同疾病和国家真实数据构建的仓室流行病模型，研究了感染致死率（IFR）与社会接触矩阵在疫苗优先级排序中的作用。研究证实，若传染病传播得到控制，大规模早期接种疫苗在降低疾病死亡率方面效果极佳；但在疫情不受控的场景下，随着疫苗接种启动时间推迟，其有效性会不断下降。最优与效果最差的优先级排序策略与流行病学变量呈非线性相关。在流行病学参数空间中，优先保护最脆弱人群比优先针对最具传染性个体更有效的区域，很大程度上取决于IFR的年龄分布——例如，与季节性流感相比，COVID-19对应的该区域范围要宽得多。人口结构与社会接触矩阵会改变相图的形态，但不会改变其定性特征。
英文摘要：
Effective strategies of vaccine prioritization are essential to mitigate the impacts of severe infectious diseases. We investigate the role of infection fatality ratio (IFR) and social contact matrices on vaccination prioritization using a compartmental epidemic model fueled by real-world data of different diseases and countries. Our study confirms that massive and early vaccination is extremely effective to reduce the disease fatality if the contagion is mitigated, but the effectiveness is increasingly reduced as vaccination beginning delays in an uncontrolled epidemiological scenario. The optimal and least effective prioritization strategies depend non-linearly on epidemiological variables. Regions of the epidemiological parameter space, in which prioritizing the most vulnerable population is more effective than the most contagious individuals, depend strongly on the IFR age profile being, for example, substantially broader for COVID-19 in comparison with seasonal influenza. Demographics and social contact matrices deform the phase diagrams but do not alter their qualitative shapes.
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