The overarching goal of the PReViX project is to develop an integrative modeling framework that provides public health authorities with early and reliable information from the first signs of a new respiratory virus threat. The project brings together a multidisciplinary consortium of leading French research institutions to tackle this challenge from various angles, including virology, genomics, epidemiology, and social sciences. PReViX is structured into six interconnected work packages, each addressing a critical aspect of pandemic preparedness, from early risk assessment to understanding non-pharmaceutical interventions.

Focus on Enhancing Hospital Resilience

Our team in Rennes, in collaboration with the IPLESP unit in Paris and PCCEI in Montpellier, will specifically investigate the French hospital system’s ability to adapt to the massive influx of patients during a health crisis. During the COVID-19 pandemic, hospitals in most European countries, the US, and Australia have been able to absorb a surge of hospitalizations beyond their theoretical capacity. In France, while only 5,000 ICU beds were registered in the country in 2019, it has been shown that this number could increase to over 20,000, mostly by converting acute and post-anesthetic care units into ICU beds. To match hospital capacity to the demand for care, hospitals may reallocate resources by reducing their quality of care (reducing patients’ length of stay, staff per patient), and reducing (postponing non-priority care) or diverting part of their activity to other healthcare institutions. The extent and nature of these adjustments will also strongly depend on the intensity and profile of the demand for hospitalization, which itself varies with several factors: the characteristics of the pandemic pathogen, mitigation measures that may decrease other hospitalization needs (curfew, lockdowns), but also on the demographic characteristics of the hospital catchment area, and the local density of healthcare offer. This PhD project aims to evaluate and model the flexibility of hospital capacity and its multidimensional determinants.

This PhD project seeks to address the question: How can hospital systems adapt to a sudden surge in demand caused by a pandemic, and how can decision-makers be reliably informed, before and during the crisis, of the risk of hospital overload? As observed during the COVID-19 pandemic, hospital resources may become scarce and turn into a trigger for local or national mitigation measures (social distancing, curfews, lockdown, …). Yet, hospitals also demonstrated a certain degree of flexibility, notably through the reallocation of resources. This project will aim to quantify that flexibility, identify key adjustment levers, and develop a healthcare capacity model capable of simulating the system’s potential for adaptation and informing strategies to strengthen it efficiently.

We will retrospectively analyze the French hospital discharge database from 2019 to 2021 to document effective surge capacity by hospital and ward type, as well as the decrease in non-COVID-19 activities, and how these activities were postponed or diverted. This approach will enable the assessment of how hospitals adapted their medical technology to perform supplementary COVID-19 treatments, contingent upon the type of medical equipment available. This analysis will also provide information on how and where hospital activities have been diverted during COVID-19 pandemic surge events at hospitals. We have demonstrated in previous works our ability to harness hospital discharge databases to build healthcare networks of patient transfers and analyze such objects. For this project, we will build on tools already developed within the team to identify structural changes in the healthcare network under various contexts of infectious disease epidemics. These elements will serve as the foundation to build a dynamic model of healthcare capacity for pandemic preparedness.