Data needs for integrated economic-epidemiological models of pandemic mitigation policies

Abstract

The COVID-19 pandemic and the mitigation policies implemented in response to it have resulted in economic losses worldwide. Attempts to understand the relationship between economics and epidemiology has led to a new generation of integrated mathematical models. The data needs for these models transcend those of the individual fields, especially where human interaction patterns are closely linked with economic activity. In this article, we reflect upon modelling efforts to date, discussing the data needs that they have identified, both for understanding the consequences of the pandemic and policy responses to it through analysis of historic data and for the further development of this new and exciting interdisciplinary field.

Keywords: Economics; Modelling; Transmission.

Fig. 1

Schematic of integrated epi/econ models: epidemiological variables are grouped at the bottom (yellow), economic variables displayed in the centre of the figure (red), and current economic data at the top (green). For simplicity we exclude core epidemiological data (e.g. hospitalisations and deaths) from this diagram. The letter $\tau$ indexes time intervals, typically of one month in duration. GVA in period $\tau$ is reported in period $\tau +1$. In the epidemiological model, $H\left(\tau \right)$ denotes total hospital occupancy in period $\tau$, and $\lambda \left(t\right)$ the (continuously varying) Force Of Infection (FOI). Solid arrows denote dependencies between variables. Bold arrows show the causal relationships between economic and epidemiological phenomena. Dashed arrows show the manifestation of economic variables in current data sources, and indicate the progression of time periods in the epidemiological part of the model.