On the interplay between mobility and hospitalization capacity during the COVID-19 pandemic: The SEIRHUD model

TL;DR

This paper introduces the SEIRHUD model to analyze how mobility restrictions and hospitalization capacity interact during COVID-19, aiding understanding of policy impacts on disease spread and healthcare resources.

Contribution

The paper develops a novel compartmental model that integrates mobility reduction and hospitalization dynamics, enabling detailed analysis of their interplay during the pandemic.

Findings

Model calibrates mobility reduction effects on infection spread

Highlights importance of hospitalization capacity limits

Provides insights for policy optimization

Abstract

Measures to reduce the impact of the COVID-19 pandemic require a mix of logistic, political and social capacity. Depending on the country, different approaches to increase hospitalization capacity or to properly apply lock-downs are observed. In order to better understand the impact of these measures we have developed a compartmental model which, on the one hand allows to calibrate the reduction of movement of people within and among different areas, and on the other hand it incorporates a hospitalization dynamics that differentiates the available kinds of treatment that infected people can receive. By bounding the hospitalization capacity, we are able to study in detail the interplay between mobility and hospitalization capacity.