Using input-output analysis to model the impact of pandemic mitigation and suppression measures on the workforce.
Using input-output analysis to model the impact of pandemic mitigation and suppression measures on the workforce.
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DOI：
10.1016/j.spc.2020.06.001
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发表时间：
2020-07
影响因子：
12.1
通讯作者：
Santos J
中科院分区：
文献类型：
--
作者：
Santos J
“拉平曲线”图最近已成为一种常用工具，用于直观显示大流行抑制和缓解措施可能在多大程度上减少和延迟大流行造成的每日感染人数。COVID-19疫情对许多医疗系统的能力构成挑战，并对全球社会相互依存的部门造成连锁经济影响。本文专门探讨了流行病对劳动力的影响。本文提出的模型包括三个主要步骤。首先，确定流行病曲线的来源，以生成发病率，发病率是相对于受影响地区人口标准化的每日感染人数。其次，该模型假设，一般攻击率可以专门反映部门特定的劳动力分类，注意到每个经济部门对劳动力的依赖程度不同。第三，使用美国经济分析局的经济投入产出（IO）数据，本文分析了几种缓解和抑制措施相对于基线大流行情景的表现。IO模拟的结果表明了缓解和抑制措施可以使曲线变平的程度。本文最后反思了流行病的其他后果，如与社会隔离相关的心理健康影响以及对不同社会经济群体的不成比例的影响。
The “flatten the curve” graphic has recently become a common tool to visualize the extent to which pandemic suppression and mitigation measures could potentially reduce and delay the number of daily infections due to a pandemic. The COVID-19 pandemic has challenged the capacity of the many healthcare systems and created cascading economic impacts on interdependent sectors of the global society. This paper specifically explores the impact of pandemics on the workforce. The model proposed in this paper comprises of three major steps. First, sources for epidemic curves are identified to generate the attack rate, which is the daily number of infections normalized with respect to the population of the affected region. Second, the model assumes that the general attack rate can be specialized to reflect sector-specific workforce classifications, noting that each economic sector has varying dependence on the workforce. Third, using economic input-output (IO) data from the US Bureau of Economic Analysis, this paper analyzes the performance of several mitigation and suppression measures relative to a baseline pandemic scenario. Results from the IO simulations demonstrate the extent to which mitigation and suppression measures can flatten the curve. This paper concludes with reflections on other consequences of pandemics such as the mental health impacts associated with social isolation and the disproportionate effects on different socioeconomic groups.
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影响因子：
28.2
作者：
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通讯作者：
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影响因子：
2.3
作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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DOI：
10.1073/pnas.0601266103
发表时间：
2006-04-11
影响因子：
11.1
作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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