Medwave · 2026
Mechanistic analysis of COVID-19 cases in Chile during the second half of 2020: an SIR model with dynamic transmission rate.
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Córdova Lepe Fernando, Hernández Castañeda Ranghely, Gutiérrez Rodrigo, Gutiérrez Jara Juan Pablo
Аннотация
INTRODUCTION: This article analyzes the prolonged trough phase in the epidemic curve associated with COVID-19 dynamics in Chile during the period July-December 2020, characterized by a relatively stable daily record of 1 000-2500 cases.
METHODS: Unlike traditional (, )-SIR models, with constant parameters and associated respectively with the transmission and removal rates in the infectious process, which predict unimodal behavior, we propose an approach based on Contagion Mechanics that incorporates a dynamic law for the transmission rate .
RESULTS: Using official data from the Department of Health Statistics and Information, we demonstrate how this approach quantitatively captures the observed stabilization, resulting from sustained adherence to non-pharmaceutical measures by the Chilean population. The model reveals that maintaining the infection rate below its intrinsic value required sustained collective effort, enabling controlled management of hospital demand during the pre-vaccination stage.
CONCLUSIONS: Our results validate the usefulness of Contagion Mechanics in explaining complex epidemiological dynamics and offer new perspectives on the population response to prolonged health interventions.
METHODS: Unlike traditional (, )-SIR models, with constant parameters and associated respectively with the transmission and removal rates in the infectious process, which predict unimodal behavior, we propose an approach based on Contagion Mechanics that incorporates a dynamic law for the transmission rate .
RESULTS: Using official data from the Department of Health Statistics and Information, we demonstrate how this approach quantitatively captures the observed stabilization, resulting from sustained adherence to non-pharmaceutical measures by the Chilean population. The model reveals that maintaining the infection rate below its intrinsic value required sustained collective effort, enabling controlled management of hospital demand during the pre-vaccination stage.
CONCLUSIONS: Our results validate the usefulness of Contagion Mechanics in explaining complex epidemiological dynamics and offer new perspectives on the population response to prolonged health interventions.