Pandemic risk modeling is a recurring topic, particularly since the recent COVID-19 pandemic. Most often, classical epidemiological models are developed for this goal. This article proposes a modeling solution that offers a compromise between simplicity and adjustment of multiple results according to the population at risk. The modeling solution framework relies on an R Shiny application that can be used interactively for different use cases. In addition, we offer insights into how to model potential future pandemics.

Key discussion points:

• Past pandemics: Respiratory and non-respiratory events
• Pandemic modelling approach: Baseline mortality and excess pandemic models
• Implementation of the pandemic model: The R Shiny dashboard applied to real population data
• Emerging pandemic threats: Implications of climate change and zoonotic pathogens