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Article Dans Une Revue Journal of Data Science, Statistics, and Visualisation Année : 2022

Using hospital data for monitoring the dynamics of COVID 19 in France

Marc Lavielle

Résumé

The aim of this article is to show how daily hospital data can be used to track the evolution of the COVID-19 epidemic in France. A piecewise defined dynamic model allows a very good fit of the available data on hospital admissions, deaths and discharges. The change-points detected correspond to moments when the dynamics of the epidemic changed abruptly. Although the proposed model is relatively simple, it can serve several purposes: It is an analytical tool to better understand what has happened so far by relating observed changes to changes in health policy or the evolution of the virus. It is also a surveillance tool that can be used effectively to warn of a resurgence of epidemic activity, and finally a short-term forecasting tool if conditions remain unchanged. The model, data and fits are implemented in an interactive web application.
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Dates et versions

hal-03321804 , version 1 (18-08-2021)
hal-03321804 , version 2 (05-01-2022)

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Marc Lavielle. Using hospital data for monitoring the dynamics of COVID 19 in France. Journal of Data Science, Statistics, and Visualisation, 2022, ⟨10.52933/jdssv.v2i7.48⟩. ⟨hal-03321804v2⟩
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