Assessing policy to address the medium-run impact of COVID-19 on income and health inequality with models informed by the history of disease outbreaks

本研究旨在评估2019冠状病毒病对收入和健康不平等的中期影响，以及旨在减轻这些影响的可能政策。中期很重要，因为预计2019冠状病毒病对不平等的影响将持续多年。了解不平等在中期如何变化，并评估短期以后的缓解政策，需要掌握疫情爆发几年后收入和健康不平等演变的信息。为实现这一目标，我们将把通常适用于现代数据集的模型与历史时期的定量数据结合起来，与当代数据不同，历史时期的定量数据涵盖了疫情爆发后的较长时期。我们将使用格拉斯哥自19世纪末以来的记录，涵盖了一段紧张而动荡的经济活动时期，以及多次疾病爆发。我们之所以选择格拉斯哥，是因为它是一个大城市，表现出与今天类似的不平等现象，而且格拉斯哥的行政记录提供了详细的相关信息。我们的做法如下。我们将使用一个建模框架，该框架已被证明在捕捉收入不平等和经济衰退对这种不平等的影响方面是有效的。我们将扩展建模方法，将健康不平等也包括在内，并确保使用最新数据集准确地表示收入和健康不平等。为了建立模型，以便捕捉疾病暴发对不平等的影响，我们将使用包括大规模疾病暴发在内的早期历史数据。然后，该模型将允许我们检查不同政策干预对具有不同社会经济特征的家庭的影响。

This research aims to assess the medium-run implications of COVID-19 on income and health inequality, and possible policies that aim to mitigate these effects. The medium run is important because the impacts of COVID-19 on inequality are expected to persist for many years. Understanding how inequality changes over the medium run, and assessing mitigation policies beyond the short term, requires information on the evolution of income and health inequalities several years after an outbreak. To achieve this, we will combine models typically applied to modern datasets with quantitative data from historical periods that, unlike contemporary data, cover extended post-outbreak periods. We will use records from Glasgow since the end of the 19th century, covering a period of intense and volatile economic activity, as well as multiple disease outbreaks. We choose Glasgow because it is a large city demonstrating similar inequalities to those seen today, and because administrative records for Glasgow provide detailed relevant information.Our approach is the following. We will use a modelling framework that has been shown to be effective in capturing income inequality and the effects of recessions on this inequality. We will extend the modelling approach to also include health inequalities and ensure that both income and health inequalities are represented accurately using recent datasets. To set up the model so that it captures the effects of outbreaks on inequalities, we will use historical data from earlier times that include large disease outbreaks. The model will then allow us to examine the effects of different policy interventions for households with different socioeconomic characteristics.