Publications by authors named "Alejandro H Gonzalez"

A fraction of individuals infected with SARS-CoV-2 experienced rebounds when treated with effective antivirals such as Nirmatrelvir/Ritonavir (Paxlovid). Although this phenomenon has been studied from biological and statistical perspectives, the underlying dynamical mechanism is not yet fully understood. In this work, we characterize the dynamic behavior of a target-cell model to explain post-treatment rebounds from the perspective of set-theoretic stability analysis.

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Emerging and re-emerging pathogens are latent threats in our society with the risk of killing millions of people worldwide, without forgetting the severe economic and educational backlogs. From COVID-19, we learned that self isolation and quarantine restrictions (confinement) were the main way of protection till availability of vaccines. However, abrupt lifting of social confinement would result in new waves of new infection cases and high death tolls.

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Article Synopsis
  • Mathematical models are essential for understanding how pathogens spread and for assessing the effectiveness of non-pharmaceutical interventions (NPIs) in populations.
  • Recent strategies aim to minimize either the peak number of infections or the overall epidemic size, but there's no agreement on how to optimize both at the same time while limiting the negative impacts of interventions.
  • This study introduces a new approach to managing SIR-type models by distinguishing between short-term and long-term control goals, demonstrating its effectiveness through detailed analysis and simulations related to the COVID-19 pandemic.
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Mathematical models describing SARS-CoV-2 dynamics and the corresponding immune responses in patients with COVID-19 can be critical to evaluate possible clinical outcomes of antiviral treatments. In this work, based on the concept of virus spreadability in the host, antiviral effectiveness thresholds are determined to establish whether or not a treatment will be able to clear the infection. In addition, the virus dynamic in the host - including the time-to-peak and the final monotonically decreasing behavior - is characterized as a function of the time to treatment initiation.

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While many epidemiological models were proposed to understand and handle COVID-19 pandemic, too little has been invested to understand human viral replication and the potential use of novel antivirals to tackle the infection. In this work, using a control theoretical approach, validated mathematical models of SARS-CoV-2 in humans are characterized. A complete analysis of the main dynamic characteristic is developed based on the reproduction number.

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