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Gastón Romeo, Martín

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https://academica-e.unavarra.es/handle/2454/49134

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Gastón Romeo

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Martín

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Estadística, Informática y Matemáticas

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ISC. Institute of Smart Cities

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0000-0001-5175-9381

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4616

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2020 - 20243
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Author: Cildoz Esquíroz, Marta ×

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  • Thumbnail Image
    PublicationOpen Access
    Operations research helps public health services managers planning resources in the COVID-19 crisis
    (Sociedad de Estadística e Investigación Operativa, 2020) García de Vicuña Bilbao, Daniel; Cildoz Esquíroz, Marta; Gastón Romeo, Martín; Azcárate Camio, Cristina; Mallor Giménez, Fermín; Esparza, Laida; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y Matemáticas
    This article presents the usefulness of operational research models tosupport the decision-making in management problems on the COVID-19 pandemic. The work describes a discrete event simulation model combined with population growth models, which has been used to provide daily predictions of the needs of ward and intensive care unit beds during the COVID-19 outbreak in the Autonomous Community of Navarre, in Spain. This work also discusses the use of the simulation model in non-acutephases of the pandemic to support decision-making during the return to the normal operation of health services or as a resource management learning tool for health logistic planners.
  • Thumbnail Image
    PublicationOpen Access
    I Congreso Salud, Desastres y Desarrollo Sostenible: libro congreso
    (2022) Azcárate Camio, Cristina; Cildoz Esquíroz, Marta; Frías Paredes, Laura; Ibarra, Amaia; Galbete Jiménez, Arkaitz; García de Vicuña Bilbao, Daniel; Gastón Romeo, Martín; Moler Cuiral, José Antonio; Mallor Giménez, Fermín; Jean Louis, Clint; Institute of Smart Cities - ISC
    El congreso se plantea como un foro de encuentro de investigadores del área de Investigación Operativa con interés en aplicaciones a la salud, los desastres y el desarrollo sostenible, y los profesionales de la toma de decisiones concernientes a los ámbitos anteriores. Este encuentro promueve el intercambio de conocimiento y experiencias entre Universidad y Servicios de Salud para afrontar retos asociados al acceso de la población a unos servicios de salud de calidad y a la gestión del riesgo creciente de desastres naturales o provocados por el ser humano. El envejecimiento de la población y el desarrollo tecnológico plantean nuevos entornos para la provisión de los servicios de salud, en los que su correcta planificación y gestión debe contribuir a garantizar su eficiencia y sostenibilidad. El creciente impacto en términos de vidas humanas y daños económicos causados por desastres naturales y no naturales, como incendios, inundaciones, terremotos, fugas industriales, pandemias, etc. precisa de su comprensión para desarrollar estrategias de prevención y elaborar planes efectivos de respuesta.
  • Thumbnail Image
    PublicationOpen Access
    Early detection of new pandemic waves: control chart and a new surveillance index
    (Public Library of Science, 2024) Cildoz Esquíroz, Marta; Gastón Romeo, Martín; Frías Paredes, Laura; García de Vicuña Bilbao, Daniel; Azcárate Camio, Cristina; Mallor Giménez, Fermín; Institute of Smart Cities - ISC
    The COVID-19 pandemic highlights the pressing need for constant surveillance, updating of the response plan in post-peak periods and readiness for the possibility of new waves of the pandemic. A short initial period of steady rise in the number of new cases is sometimes followed by one of exponential growth. Systematic public health surveillance of the pandemic should signal an alert in the event of change in epidemic activity within the community to inform public health policy makers of the need to control a potential outbreak. The goal of this study is to improve infectious disease surveillance by complementing standardized metrics with a new surveillance metric to overcome some of their difficulties in capturing the changing dynamics of the pandemic. At statistically-founded threshold values, the new measure will trigger alert signals giving early warning of the onset of a new pandemic wave. We define a new index, the weighted cumulative incidence index, based on the daily new-case count. We model the infection spread rate at two levels, inside and outside homes, which explains the overdispersion observed in the data. The seasonal component of real data, due to the public surveillance system, is incorporated into the statistical analysis. Probabilistic analysis enables the construction of a Control Chart for monitoring index variability and setting automatic alert thresholds for new pandemic waves. Both the new index and the control chart have been implemented with the aid of a computational tool developed in R, and used daily by the Navarre Government (Spain) for virus propagation surveillance during post-peak periods. Automated monitoring generates daily reports showing the areas whose control charts issue an alert. The new index reacts sooner to data trend changes preluding new pandemic waves, than the standard surveillance index based on the 14-day notification rate of reported COVID-19 cases per 100,000 population.