Estimating the impact of the COVID-19 pandemic using granular mortality data

TL;DR

This paper extends a mortality model to quantify COVID-19's impact across five European countries using granular weekly data, enabling scenario-based mortality forecasts during the pandemic.

Contribution

It introduces a third layer to the Li and Lee model specifically capturing COVID-19's excess mortality, utilizing granular weekly data for improved accuracy.

Findings

Model effectively quantifies COVID-19 impact on mortality.

Granular data enhances the model's precision.

Framework supports scenario-based mortality forecasting.

Abstract

We present an extension of the Li and Lee model to quantify mortality in five European countries during the COVID-19 pandemic. The first two factors are used to model the pre-COVID mortality, with the first layer modelling the common trend and the second layer the country-specific deviation from the common trend. We add a third layer to capture the country-specific impact of COVID-19 in 2020 and 2021 in excess of the pre-COVID trend. We use weekly mortality data from the Short Term Mortality Fluctuations Database to calibrate this third factor, and we use a more granular dataset for deaths in the Netherlands to assess the added value of more detailed data. We use our framework to define mortality forecasts based on different possible scenarios for the future course the pandemic.