Colección especial COVID-19

Esta colección especial recoge todo tipo de materales relacionados con la COVID-19 o de los coronavirus en general como aportación al mejor y más extenso conocimiento de estas enfermedades, como artículos o informes de investigación o materiales más divulgativo en las que ha participado la UPV.
RDA Recomendaciones y pautas sobre el intercambio de datos para COVID-19,

URI permanente para esta colecciónhttps://riunet.upv.es/handle/10251/147394

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Access status: Abierto ,
SARS-COV-2 viral RNA detection through oligonucleotide-capped nanoporous anodic alumina supports.
(Elsevier BV, 2025-06) López-Palacios, Alba; Aranda-Sobrino, María Nieves; Caballos-Gómez, María Isabel; Hernández-Montoto, Andy; Calbuig, Eva; Gómez-Ruiz, María Dolores; Tormo-Mas, M.A.; Peman, Javier; Sancenón Galarza, Félix; Martínez-Máñez, Ramón; Aznar, Elena; Climent Terol, Estela; Escuela Técnica Superior de Ingeniería de Telecomunicación; Escuela Técnica Superior de Ingeniería Aeroespacial y Diseño Industrial; Departamento de Química; Escuela Técnica Superior de Ingeniería Industrial; Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico; European Commission; Generalitat Valenciana; Ministerio de Universidades; Instituto de Salud Carlos III; Agencia Estatal de Investigación; Universitat Politècnica de València
[EN] We describe herein a sensor containing nanoporous anodic alumina (NAA) as sensing platform to identify SARSCOV-2 RNA using a gating mechanism. The system is based on NAA that contains a fluorescent dye (Rhodamine B; RhB) and is capped with an oligonucleotide sequence that hybridize specifically a region of SARS-CoV-2 genome. In the presence of RNA from SARS-COV-2 virus, the oligonucleotide of the surface is displaced, uncapping the pores, and producing a delivery of RhB. The detection of the virus is achieved measuring the fluorescence of the fluorophore. The nanosensor demonstrates to be highly sensitive and selective in aqueous buffers and in biological media, having a limit of detection (LOD) of 50 ± 30 copies mL-1 of SARS-CoV-2 RNA extracted from patients. Moreover, preliminary results using 18 real nasopharyngeal swab samples indicate the potential of the system to differentiate between infected and non-infected patients. Compared to the conventional RT-PCR method, in our system there is no need for sample pretreatment or RNA isolation, providing diagnostic outcomes within 60 mins while maintaining a high level of reliability
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Impact of Long SARS-CoV-2 Omicron Infection on the Health Care Burden: Comparative Case-Control Study Between Omicron and Pre-Omicron Waves
(JMIR Publications Inc., 2024) Valdivieso-Martínez, Bernardo; Lopez-Sanchez, Victoria; Sauri, Inmaculada; Díaz, Javier; Calderón, Jose Miguel; Gas-López, Maria Eugenia; Lidón, Laura; Philibert, Juliette; Lopez-Hontangas, Jose Luis; Navarro, David; Cuenca, L.; Forner, María José; Redón, Josep; Departamento de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Técnica Superior de Ingeniería Informática; Generalitat Valenciana
[EN] Background: Following the initial acute phase of COVID-19, health care resource use has escalated among individuals with SARS-CoV-2 infection. Objective: This study aimed to compare new diagnoses of long COVID and the demand for health services in the general population after the Omicron wave with those observed during the pre-Omicron waves, using similar assessment protocols for both periods and to analyze the influence of vaccination. Methods: This matched retrospective case-control study included patients of both sexes diagnosed with acute SARS-CoV-2 infection using reverse transcription polymerase chain reaction or antigen tests in the hospital microbiology laboratory during the pandemic period regardless of whether the patients were hospitalized. We included patients of all ages from 2 health care departments that cover 604,000 subjects. The population was stratified into 2 groups, youths (<18 years) and adults (>= 18 years). Patients were followed-up for 6 months after SARS-CoV-2 infection. Previous vaccination, new diagnoses, and the use of health care resources were recorded. Patients were compared with controls selected using a prospective score matched for age, sex, and the Charlson index. Results: A total of 41,577 patients with a history of prior COVID-19 infection were included, alongside an equivalent number of controls. This cohort encompassed 33,249 (80%) adults aged >= 18 years and 8328 (20%) youths aged <18 years. Our analysis identified 40 new diagnoses during the observation period. The incidence rate per 100 patients over a 6-month period was 27.2 for vaccinated and 25.1 for unvaccinated adults (P=.09), while among youths, the corresponding rates were 25.7 for vaccinated and 36.7 for unvaccinated individuals (P<.001). Overall, the incidence of new diagnoses was notably higher in patients compared to matched controls. Additionally, vaccinated patients exhibited a reduced incidence of new diagnoses, particularly among women (P<.001) and younger patients (P<.001) irrespective of the number of vaccine doses administered and the duration since the last dose. Furthermore, an increase in the use of health care resources was observed in both adult and youth groups, albeit with lower figures noted in vaccinated individuals. In the comparative analysis between the pre-Omicron and Omicron waves, the incidence of new diagnoses was higher in the former; however, distinct patterns of diagnosis were evident. Specifically, depressed mood (P=.03), anosmia (P=.003), hair loss (P<.001), dyspnea (<0.001), chest pain (P=.04), dysmenorrhea (P<.001), myalgia (P=.011), weakness (P<.001), and tachycardia (P=.015) were more common in the pre-Omicron period. Similarly, health care resource use, encompassing primary care, specialist, and emergency services, was more pronounced in the pre-Omicron wave. Conclusions: The rise in new diagnoses following SARS-CoV-2 infection warrants attention due to its potential implications for health systems, which may necessitate the allocation of supplementary resources. The absence of vaccination protection presents a challenge to the health care system.
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La orfandad en tiempos de Covid-19: intervenciones familiares en los procesos de duelo infantil y adolescente en programas del Servicio Mejor Niñez
(Universitat Politècnica de València, 2025-05-20) Farías Figueroa, Javier
[EN] The purpose of this study has been to describe the family interventions of professionals who work in child protection programs related to orphanhood that originated during the COVID-19 pandemic in Chile. The informants were professionals from four specialized foster care programs (FAE-PRO) of the Servicio Mejor Niñez that currently work with children and young people whose parents or caregivers died during the SARS-COV-2 pandemic. The study had a qualitative character with a phenomenological approach, the data collection technique was the semi-structured interview and the information was organized in the ATLAS.TI software. The main results reveal the difficulties in deploying family interventions in child and adolescent grief processes and how professionals have meant that social determinants and lack of protection factors would increase the psychological effects caused by grief during the COVID-19 pandemic. Furthermore, the partial absence of the state is described in relation to the commitments adopted to support child and adolescent grieving processes and, also, the importance of supporting family groups that care for children and adolescents who lost their parents or caregivers. These results highlight the need to increase efforts to provide psychosocial support to family groups that during the COVID-19 pandemic have experienced a child and adolescent grieving process.
Access status: Cerrado ,
Metabolomic Biomarkers of Pulmonary Fibrosis in COVID-19 Patients One Year After Hospital Discharge
(John Wiley & Sons, 2025-03) Botello-Marabotto, Marina Dolores; Tarraso, Julia; Mulet, Alba; Presa-Fernandez, Lucia; Fernandez-Fabrellas, Estrella; Rodriguez Portal, Jose A.; Ros, Jose A.; Lozano-Vicente, Desire; Bernardos Bau, Andrea; Martínez-Bisbal, M.Carmen; Martínez-Máñez, Ramón; Signes-Costa, Jaime; Escuela Técnica Superior de Ingeniería Aeroespacial y Diseño Industrial; Departamento de Química; Escuela Técnica Superior de Ingeniería Industrial; Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico; Generalitat Valenciana; Instituto de Salud Carlos III; Agencia Estatal de Investigación; European Regional Development Fund; Ministerio de Ciencia e Innovación; Ministerio de Ciencia, Innovación y Universidades; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina
[EN] Coronavirus disease 2019 (COVID-19) global pandemic has affected more than 600 million people up to date. The symptomatology and severity of COVID-19 are very broad, and there are still concerns about the long-term sequelae that it can have on discharged patients. The development of pulmonary fibrotic sequelae after this infection is especially worrying. Our aim was to determine if there was a metabolomic signature that could predict the development of pulmonary fibrotic sequelae. It is a multicenter prospective observation subcohort based on the COVID-FIBROTIC study. A metabolomic analysis was performed by nuclear magnetic resonance (NMR) on serum samples from patients admitted with bilateral COVID-19 pneumonia collected 2 months after hospital discharge. One year after admission, clinical, functional and radiological data were collected from these same patients. Finally, 109 patients (mean age 57.68 [DS14.03], 65.13% male) were available. Fibrotic sequelae 1 year after COVID-19 disease were found in 33% of them. Based on the NMR analysis of the serum samples, it was possible to distinguish with 80.82% of sensitivity, 72.22% of specificity and 0.83 of an area under the curve (AUC) value which patients would have radiological signs of pulmonary fibrotic pattern 1 year after sample collection. According to the metabolites participating in the discriminative model and the univariate statistics, glucose, valine, and fatty acids (& boxH;CH-CH2-CH & boxH;) were suggested as potential biomarkers of the development of pulmonary fibrotic sequelae after COVID-19.
Access status: Abierto ,
Development of Rapid Detection Tests for SARS-CoV-2 and other Pathogens based on Materials with Molecular Gates
(Universitat Politècnica de València, 2025-02-17) Caballos-Gómez, María Isabel; Aznar Gimeno, Elena; Martínez Mañez, Ramón; Escuela Técnica Superior de Ingeniería Aeroespacial y Diseño Industrial; Departamento de Química; Escuela Técnica Superior de Ingeniería Industrial; Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico; European Commission; Agencia Estatal de Investigación
[ES] La presente tesis doctoral titulada "Development of rapid detection tests for SARS-CoV-2 and other pathogens based on materials with molecular gates" se centra en el desarrollo de materiales avanzados de detección, diseñados para la identificación rápida de patógenos como SARS-CoV-2, Xylella fastidiosa y Mycobacterium tuberculosis. Para lograr este objetivo general, la investigación se estructura en cuatro metas específicas, las cuales se desarrollan a lo largo de los capítulos de esta tesis. En el primer capítulo, se presenta el desarrollo de un sistema de detección basado en el soporte de alúmina anódica nanoporosa (NAA) combinado con puertas moleculares de ADN complementario para la detección del ADN genómico de Xylella fastidiosa. Este sistema aprovecha estas hebras como agente de bloqueo de los poros de la NAA, lo que permite una detección específica de este patógeno de gran relevancia en ecología y agricultura. En el segundo capítulo se explora la creación de un sistema basado en materiales de alúmina con anticuerpos como puertas moleculares para la detección de Mycobacterium tuberculosis, el patógeno responsable de la tuberculosis. Este dispositivo busca brindar una detección específica mediante la implementación de anticuerpos que actúan como agentes de bloqueo de los poros a la vez que elemento reconocedor en el sistema. El tercer capítulo, aborda el diseño, síntesis y evaluación de los sistemas de NAA funcionalizados con aptámeros para la detección temprana de SARS-CoV-2. El proyecto de investigación se enfoca en obtener una alta sensibilidad y selectividad para identificar el virus, dado su impacto en la salud pública y la importancia de su detección temprana para controlar la propagación del COVID-19. Por último, el cuarto capítulo se desarrolló un novedoso sistema de detección para material genético de SARS-CoV-2, combinando el sistema CRISPR-Cas con el soporte de NAA funcionalizado con ADN de cadena simple. Esta metodología integró la especificidad de CRISPR-Cas con la amplificación de señal de los materiales de NAA, logrando detectar secuencias de oligonucleótidos específicos con alta precisión. Todos los capítulos profundizan en la síntesis y caracterización de estos materiales con puertas moleculares, que se han diseñado para detectar biomoléculas de diferente naturaleza como pueden ser proteínas o secuencias específicas de ADN. Además, se estudian las dinámicas de liberación del indicador encapsulado en los poros en presencia de sus respectivos analitos e interferentes, lo cual es crucial para evaluar la eficiencia y viabilidad práctica de los materiales en aplicaciones reales. Los estudios demuestran cómo la interacción entre el analito y la puerta molecular desplaza a esta última dando lugar a la liberación controlada del colorante, funcionando como una señal medible que confirma la presencia del patógeno. Estos avances en el diseño de sistemas de detección con puertas moleculares representan un importante progreso en los campos de reconocimiento y diagnóstico, ofreciendo métodos rápidos, altamente sensibles, selectivos y adaptables a la detección de un amplio rango de patógenos de importancia en la actualidad.
Access status: Abierto ,
Clinical phenotypes and outcomes in children with multisystem inflammatory syndrome across SARS-CoV-2 variant eras: a multinational study from the 4CE consortium
(Elsevier, 2023-10) Sperotto, Francesca; Gutiérrez-Sacristán, Alba; Makwana, Simran; Li, Xiudi; Rofeberg, Valerie N.; Cai, Tianxi; Bourgeois, Florence T.; Omenn, Gilbert S.; Hanauer, David A.; Sáez Silvestre, Carlos; Bonzel, Clara Lea; Bucholz, Emily; Dionne, Audrey; Elias, Matthew D.; Garcia-Barrio, Noelia; Departamento de Física Aplicada; Instituto Universitario de Tecnologías de la Información y Comunicaciones; Escuela Técnica Superior de Ingeniería Industrial
[EN] Background Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infection. It remains unclear how MIS-C phenotypes vary across SARS-CoV-2 variants. We aimed to investigate clinical characteristics and outcomes of MIS-C across SARS-CoV-2 eras. Methods We performed a multicentre observational retrospective study including seven paediatric hospitals in four countries (France, Spain, U.K., and U.S.). All consecutive confirmed patients with MIS-C hospitalised between February 1st, 2020, and May 31st, 2022, were included. Electronic Health Records (EHR) data were used to calculate pooled risk differences (RD) and effect sizes (ES) at site level, using Alpha as reference. Meta-analysis was used to pool data across sites. Findings Of 598 patients with MIS-C (61% male, 39% female; mean age 9.7 years [SD 4.5]), 383 (64%) were admitted in the Alpha era, 111 (19%) in the Delta era, and 104 (17%) in the Omicron era. Compared with patients admitted in the Alpha era, those admitted in the Delta era were younger (ES -1.18 years [95% CI -2.05, -0.32]), had fewer respiratory symptoms (RD -0.15 [95% CI -0.33, -0.04]), less frequent non-cardiogenic shock or systemic inflammatory response syndrome (SIRS) (RD -0.35 [95% CI -0.64, -0.07]), lower lymphocyte count (ES -0.16 x 109/uL [95% CI -0.30, -0.01]), lower C-reactive protein (ES -28.5 mg/L [95% CI -46.3, -10.7]), and lower troponin (ES -0.14 ng/mL [95% CI -0.26, -0.03]). Patients admitted in the Omicron versus Alpha eras were younger (ES -1.6 years [95% CI -2.5,-0.8]), had less frequent SIRS (RD -0.18 [95% CI -0.30, -0.05]), lower lymphocyte count (ES -0.39 x 109/uL [95% CI -0.52, -0.25]), lower troponin (ES -0.16 ng/mL [95% CI -0.30, -0.01]) and less frequently received anticoagulation therapy (RD -0.19 [95% CI -0.37, -0.04]). Length of hospitalization was shorter in the Delta versus Alpha eras (-1.3 days [95% CI -2.3,-0.4]). Interpretation Our study suggested that MIS-C clinical phenotypes varied across SARS-CoV-2 eras, with patients in Delta and Omicron eras being younger and less sick. EHR data can be effectively leveraged to identify rare complications of pandemic diseases and their variation over time.
Access status: Abierto ,
Modified SIQR model for the COVID-19 outbreak in several countries
(John Wiley & Sons, 2024-03-30) Pinto, Carla M. A.; Tenreiro Machado, J. A.; Burgos-Simon, Clara; Departamento de Matemática Aplicada; Escuela Técnica Superior de Ingeniería Geodésica, Cartográfica y Topográfica; Instituto Universitario de Matemática Multidisciplinar; European Regional Development Fund; Fundação para a Ciência e a Tecnologia, Portugal
[EN] In this paper, we propose a modified Susceptible-Infected-Quarantine-Recovered (mSIQR) model, for the COVID-19 pandemic. We start by proving the well-posedness of the model and then compute its reproduction number and the corresponding sensitivity indices. We discuss the values of these indices for epidemiological relevant parameters, namely, the contact rate, the proportion of unknown infectious, and the recovering rate. The mSIQR model is simulated, and the outputs are fit to COVID-19 pandemic data from several countries, including France, US, UK, and Portugal. We discuss the epidemiological relevance of the results and provide insights on future patterns, subjected to health policies.
Access status: Abierto ,
Extracting relevant predictive variables for COVID-19 severity prognosis: An exhaustive comparison of feature selection techniques
(Public Library of Science, 2023-04-13) Hayet-Otero, Miren; García-García, Fernando; Lee, Dae-Jin; Martínez-Minaya, Joaquín; España Yandiola, Pedro Pablo; Urrutia Landa, Isabel; Nieves Ermecheo, Mónica; Quintana, José María; Menéndez, Rosario; Torres, Antoni; Zalacain Jorge, Rafael; Arostegui, Inmaculada; Facultad de Administración y Dirección de Empresas; Departamento de Estadística e Investigación Operativa Aplicadas y Calidad; Grupo de Ingeniería Estadística Multivariante GIEM; Eusko Jaurlaritza; Agencia Estatal de Investigación; Ministerio de Ciencia, Innovación y Universidades
[EN] With the COVID-19 pandemic having caused unprecedented numbers of infections and deaths, large research efforts have been undertaken to increase our understanding of the disease and the factors which determine diverse clinical evolutions. Here we focused on a fully data-driven exploration regarding which factors (clinical or otherwise) were most informative for SARS-CoV-2 pneumonia severity prediction via machine learning (ML). In particular, feature selection techniques (FS), designed to reduce the dimensionality of data, allowed us to characterize which of our variables were the most useful for ML prognosis. We conducted a multi-centre clinical study, enrolling n = 1548 patients hospitalized due to SARS-CoV-2 pneumonia: where 792, 238, and 598 patients experienced low, medium and high-severity evolutions, respectively. Up to 106 patient-specific clinical variables were collected at admission, although 14 of them had to be discarded for containing > 60% missing values. Alongside 7 socioeconomic attributes and 32 exposures to air pollution (chronic and acute), these became d = 148 features after variable encoding. We addressed this ordinal classification problem both as a ML classification and regression task. Two imputation techniques for missing data were explored, along with a total of 166 unique FS algorithm configurations: 46 filters, 100 wrappers and 20 embeddeds. Of these, 21 setups achieved satisfactory bootstrap stability (> 0.70) with reasonable computation times: 16 filters, 2 wrappers, and 3 embeddeds. The subsets of features selected by each technique showed modest Jaccard similarities across them. However, they consistently pointed out the importance of certain explanatory variables. Namely: patient's C-reactive protein (CRP), pneumonia severity index (PSI), respiratory rate (RR) and oxygen levels -saturation Sp O2, quotients Sp O2/RR and arterial Sat O2/Fi O2-, the neutrophil-to-lymphocyte ratio (NLR) -to certain extent, also neutrophil and lymphocyte counts separately-, lactate dehydrogenase (LDH), and procalcitonin (PCT) levels in blood. A remarkable agreement has been found a posteriori between our strategy and independent clinical research works investigating risk factors for COVID-19 severity. Hence, these findings stress the suitability of this type of fully data-driven approaches for knowledge extraction, as a complementary to clinical perspectives.
Access status: Cerrado ,
Impacto de la pandemia COVID-19 en el sistema de la autonomía y atención a la dependencia
(Universitat Politècnica de València, 2024-10-16) Teodorova Todorova, Preslava; Vivas Consuelo, David José Juan; González de Julián, Silvia; Facultad de Administración y Dirección de Empresas; Departamento de Economía y Ciencias Sociales; Escuela Técnica Superior de Ingeniería Aeroespacial y Diseño Industrial; Centro de Investigación de Ingeniería Económica
[ES] El presente trabajo se centra en el análisis del impacto que la pandemia de SARS-CoV-2 ha tenido sobre el sistema de autonomía personal y atención a la dependencia en España. Con el objetivo de abordar de manera integral este problema, el estudio se estructura en varios apartados que permiten una comprensión detallada del marco normativo, la evolución del sistema durante la crisis sanitaria y la postpandemia. En primer lugar, se examina el marco legislativo que regula el sistema de autonomía y atención a la dependencia, abarcando tanto la legislación a nivel estatal como autonómico. Este análisis incluye una revisión de los grados de dependencia reconocidos por la normativa vigente y una evaluación del acceso de las personas dependientes al sistema público de servicios y prestaciones. Se presta especial atención a las diferencias en la implementación y cobertura del sistema en las distintas comunidades autónomas, lo cual es fundamental para entender el acceso y calidad de los servicios prestados. Tras analizar los diferentes grados de dependencia y los servicios y prestaciones disponibles para las personas dependientes, el estudio se enfoca en el impacto que la pandemia de COVID-19 ha tenido en las residencias. Se destaca el alto número de fallecimientos en estos centros, que reflejan la vulnerabilidad de la población residente frente al virus. Además, la crisis sanitaria provocó un incremento significativo en las listas de espera para acceder a los servicios de dependencia, dificultando aún más la atención y el cuidado de las personas que lo necesitaban. En conjunto, se busca analizar los efectos inmediatos de la pandemia sobre el sistema de dependencia, con especial énfasis en la identificación de áreas críticas y las carencias que han surgido durante este periodo.
Access status: Abierto ,
Identificación y estudio de variantes patogénicas en humanos que afectan a la gravedad por COVID-19
(Universitat Politècnica de València, 2024-10-14) Ángel Moreno Serrano, Ana; Cardona Serrate, Fernando; Pérez Tur, Jordi
[ES] La enfermedad de COVID-19 causada por el SARS-CoV-2, desencadenante de la pandemia global en 2020, destaca por su rango de sintomatología variable desde la ausencia de síntomas hasta la insuficiencia respiratoria grave y muerte incluso en individuos previamente sanos. Partiendo de ello, se ha propuesto que los factores genéticos podrían tener un papel crucial en la susceptibilidad y gravedad de la infección. En este contexto, se han utilizado estudios de asociación de genoma completo (GWAS) para identificar polimorfismos de nucleótido único (SNPs) que puedan estar asociados con la predisposición y/o gravedad de infección por SARS-CoV-2. Con el propósito de identificar genes cuyas variantes influyan en la gravedad de COVID-19, se realizó una revisión de estudios GWAS y se recopilaron variantes missense con predicción negativa y otras variantes potencialmente modificadoras de la pauta de lectura utilizando registros de secuenciación de variantes de pacientes. Posteriormente, se evaluó el impacto de dichas variantes utilizando SNP-Set Kernel Association Test (SKAT) y una prueba de Chi Cuadrado. En base a los análisis estadísticos, se seleccionaron dos variantes en dos genes distintos: rs12720356 en el gen TYK2 y rs17279437 en el gen SLC6A20. Así pues, se comprobó mediante mutagénesis in silico que las mutaciones producidas por estas variantes podían causar cambios estructurales significativos y alterar la disposición tridimensional original de sus proteínas. Por consiguiente, utilizando estrategias de transformación en E. coli y transfección de líneas celulares con los cDNAs de ambos genes, se diseñó un procedimiento para la obtención de las proteínas silvestres por Western Blot, que arrojó resultados incompletos y requiere el ajuste de las concentraciones de proteína. Paralelamente, se trazó un proceso de mutagénesis por PCR para introducir las mutaciones de las variantes, no obteniendo colonias que las incorporasen, lo que sugiere una revisión de los materiales y métodos empleados. Así pues, los estudios futuros permitirán comprobar diferencias en la expresión del genotipo silvestre y mutado y determinar si estas mutaciones influyen en la severidad de la infección por SARS-CoV-2.
Access status: Abierto ,
SARS-CoV-2 N protein IgG antibody detection employing nanoporous anodized alumina: A rapid and selective alternative for identifying naturally infected individuals in populations vaccinated with spike protein (S)-based vaccines
(Elsevier, 2024-11-15) Esteve-Sánchez, Yoel; Hernández-Montoto, Andy; Tormo-Mas, M.A.; Peman, Javier; Eva Calbuig; Gomez, Maria Dolores; Marcos Martínez, María Dolores; Martínez-Máñez, Ramón; Aznar, Elena; Climent Terol, Estela; Escuela Técnica Superior de Ingeniería de Telecomunicación; Escuela Técnica Superior de Ingeniería Aeroespacial y Diseño Industrial; Departamento de Química; Escuela Técnica Superior de Ingeniería Industrial; Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico; Banco Santander; European Commission; Generalitat Valenciana; Ministerio de Universidades; Instituto de Salud Carlos III; Agencia Estatal de Investigación; European Regional Development Fund; Universitat Politècnica de València; Instituto de Investigación Sanitaria La Fe; Consejo Superior de Investigaciones Científicas
[EN] Methods to detect naturally infected individuals, especially during or after a pandemic, are valuable in populations with a high rate of vaccination. Having in mind that after the COVID-19 pandemic people has been vaccinated against the virus by Spike protein (S)-based vaccines, we present in this paper a novel nanosensor based on gated nanoporous anodic alumina (NAA) material to detect naturally infected individuals in populations with high rates of vaccination. The nanosensor developed is based on a protein-capped nanomaterial for the identification of IgG antibodies that can detect nucleocapsid protein (N) of SARS-CoV-2. The NAA material has been loaded with an indicator (Rhodamine B (RhB)) and the pores of the material have been blocked with SARS-CoV-2 nucleocapsid protein (N) attached to a specific aptamer. In presence of antibodies against this antigen, the pores are uncapped, triggering the dye release and a fluorescent signal as a result. The biosensor has been tested in vitro and simulated serum for IgG detection, proving a detection limit of 1 mu g/mL. Moreover, specificity assays with N proteins from other coronaviruses have proved the robustness and efficacy of this nanosensor. Finally, the system has been tested on samples from patients that contained SARS-CoV-2 antibodies, demonstrating its potential for the discrimination of individuals that have been vaccinated or infected by SARS-CoV-2 virus.
Access status: Abierto ,
Cost-Sensitive Ordinal Classification Methods to Predict SARS-CoV-2 Pneumonia Severity
(Institute of Electrical and Electronics Engineers, 2024-05) García-García, Fernando; Lee, Dae-Jin; España Yandiola, Pedro Pablo; Urrutia Landa, Isabel; Martínez-Minaya, Joaquín; Hayet-Otero, Miren; Ermecheo, Monica Nieves; Quintana, José María; Menéndez, Rosario; Torres, Antoni; Jorge, Rafael Zalacain; Facultad de Administración y Dirección de Empresas; Departamento de Estadística e Investigación Operativa Aplicadas y Calidad; Grupo de Ingeniería Estadística Multivariante GIEM; Eusko Jaurlaritza; Agencia Estatal de Investigación
[EN] Objective: To study the suitability of costsensitive ordinal artificial intelligence-machine learning (AIML) strategies in the prognosis of SARS-CoV-2 pneumonia severity.; Materials & methods: Observational, retrospective, longitudinal, cohort study in 4 hospitals in Spain. Information regarding demographic and clinical status was supplemented by socioeconomic data and air pollution exposures. We proposed AI-ML algorithms for ordinal classification via ordinal decomposition and for cost-sensitive learning via resampling techniques. For performancebased model selection, we defined a custom score including per-class sensitivities and asymmetric misprognosis costs. 260 distinct AI-ML models were evaluated via 10 repetitions of 5 x 5 nested cross-validation with hyperparameter tuning. Model selection was followed by the calibration of predicted probabilities. Final overall performance was compared against five well-established clinical severity scores and against a 'standard' (non-cost sensitive, non-ordinal) AI-ML baseline. In our best model, we also evaluated its explainability with respect to each of the input variables. Results: The study enrolled n = 1548 patients: 712 experienced low, 238 medium, and 598 high clinical severity. d = 131 variables were collected, becoming d' = 148 features after categorical encoding. Model selection resulted in our best-performing AI-ML pipeline having:; 1) no imputation of missing data,; 2) no feature selection (i.e. using the full set of d' features),; 3) 'Ordered Partitions' ordinal decomposition,; 4) cost-based reimbalance, and; 5) a Histogram-based Gradient Boosting classifier.; This best model (calibrated) obtained a median accuracy of 68.1% [67.3%, 68.8%] (95% confidence interval), a balanced accuracy of 57.0% [55.6%, 57.9%], and an overall area under the curve (AUC) 0.802 [0.795, 0.808]. In our dataset, it outperformed all five clinical severity scores and the 'standard' AI-ML baseline. Discussion & conclusion: We conducted an exhaustive exploration of AI-ML methods designed for both ordinal and cost-sensitive classification, motivated by a real-world application domain (clinical severity prognosis) in which these topics arise naturally. Our model with the best classification performance exploited successfully the ordering information of ground truth classes, coping with imbalance and asymmetric costs. However, these ordinal and cost-sensitive aspects are seldom explored in the literature.
Access status: Abierto ,
Hospitalization Forecast to Inform COVID-19 Pandemic Planning and Resource Allocation Using Discrete Event Simulation
(OmniaScienc, 2024-01) Wikman-Jorgensen, Philip Erick; Ruiz, Angel; Giner-Galvan, Vicente; Llenas-García, Jara; Seguí-Ripoll, José Miguel; Salinas-Serrano, Jose Maria; Borrajo, Emilio; Ibarra-Sánchez, Jose Maria; García Sabater, José Pedro; Marin-Garcia, Juan A.; Departamento de Organización de Empresas; Escuela Técnica Superior de Ingeniería Industrial; Grupo de Investigación en Reingeniería, Organización, trabajo en Grupo y Logística Empresarial - ROGLE; European Commission; Generalitat Valenciana; European Regional Development Fund
[EN] Purpose: This study aims to address the pressing need for accurate forecasting of healthcare resource demands during the COVID-19 pandemic. It presents an approach that combines a stochastic Markov model and a discrete event simulation model to dynamically predict hospital admissions and daily occupancy of hospital and ICU beds. Design/methodology/approach: The research builds upon existing work related to predicting COVID-19 spread and patient influx to hospital emergency departments. The proposed model was developed and validated at San Juan de Alicante University Hospital from July 10, 2020, to January 10, 2022, and externally validated at Hospital Vega Baja. The model involves an admissions generator based on a stochastic Markov model, feeding data into a discrete event simulation model in the R programming language. The probabilities of hospital admission were calculated based on age-stratified positive SARS-COV-2 results from the health department's catchment population. The discrete event simulation model simulates distinct patient pathways within the hospital to estimate bed occupancy for the upcoming week. The performance of the model was measured using the median absolute difference (MAD) between predicted and actual demand. Findings: When applied to data from San Juan hospital, the admissions generator demonstrated a MAD of 6 admissions/week (interquartile range [IQR] 2-11). The MAD between the model's predictions and actual bed occupancy was 20 beds/day (IQR 5-43), equivalent to 5% of total hospital beds. For ICU occupancy, the MAD was 4 beds/day (IQR 2-7), constituting 25% of ICU beds. Evaluation with data from Hospital Vega Baja showcased an admissions generator MAD of 2.42 admissions/week (IQR 1.02-7.41). The MAD between the model's predictions and actual bed occupancy was 18 beds/day (IQR 19.57-38.89), approximately 5.1% of hospital beds. The ICU occupancy MAD was 3 beds/day (IQR 1-5), making up 21.4% of ICU beds. Practical implications: The dynamic predictions of hospital admissions, ward beds, and ICU occupancy for COVID-19 patients proved highly valuable to hospital managers, facilitating early and informed planning of resource allocation. Originality/value: This study introduces a hybrid approach that combines stochastic modeling and discrete event simulation to forecast healthcare resource demands during the COVID-19 pandemic. The methodology's effectiveness in predicting admissions and bed occupancy contributes to improved resource planning and situational awareness.
Access status: Abierto ,
Water Consumption variation in Latin America due to COVID-19 Pandemic
(Editorial Universitat Politècnica de València, 2024-03-06) Ortiz, Catalina; Clavijo, William; Mahlknecht, Jürgen; Saldarriaga, Juan
[EN] To stop the spread of the COVID-19 pandemic, governments all over the world have applied social distancing measures, which have drastically altered people’s lifestyles. Many studies suggest that the water sector, including its demand and supply, has been strongly affected by these regulations. The importance of hygiene practices confers a crucial role to potable water availability as an ally for tackling the spread of the virus, heightening the alteration of water demand patterns during the ongoing pandemic. Therefore, this research aimed to assess the impact of the pandemic on the water consumption patterns in four Latin-American cities and the differences among the type of users. The case studies include two Colombian and two Mexican cities known for their important industrial and touristic features. The outcomes reveal a diminishing effect on water consumption for industrial and commercial customers. Touristic cities were the most affected, even experiencing decreased domestic water demand. Understanding these changes and challenges is essential for keeping and improving the resilience of water systems in different scenarios, especially under fluctuating environmental conditions.
Access status: Abierto ,
Predicting COVID19 pandemic waves including vaccination data with deep learning
(Frontiers Media S.A., 2023-12-15) Begga, Ahmed; Garibo-i-Orts, Óscar; de María-García, Sergi; Escolano, Francisco; Lozano, Miguel A.; Oliver, Nuria; Conejero, J. Alberto; Departamento de Matemática Aplicada; Instituto Universitario de Matemática Pura y Aplicada; Escuela Técnica Superior de Ingeniería Informática; Banco Santander; Fundación BBVA; GENERALITAT VALENCIANA; Universitat Politècnica de València
[EN] IntroductionDuring the recent COVID-19 pandemics, many models were developed to predict the number of new infections. After almost a year, models had also the challenge to include information about the waning effect of vaccines and by infection, and also how this effect start to disappear.MethodsWe present a deep learning-based approach to predict the number of daily COVID-19 cases in 30 countries, considering the non-pharmaceutical interventions (NPIs) applied in those countries and including vaccination data of the most used vaccines.ResultsWe empirically validate the proposed approach for 4 months between January and April 2021, once vaccination was available and applied to the population and the COVID-19 variants were closer to the one considered for developing the vaccines. With the predictions of new cases, we can prescribe NPIs plans that present the best trade-off between the expected number of COVID-19 cases and the social and economic cost of applying such interventions.DiscussionWhereas, mathematical models which include the effect of vaccines in the spread of the SARS-COV-2 pandemic are available, to the best of our knowledge we are the first to propose a data driven method based on recurrent neural networks that considers the waning effect of the immunization acquired either by vaccine administration or by recovering from the illness. This work contributes with an accurate, scalable, data-driven approach to modeling the pandemic curves of cases when vaccination data is available.
Access status: Abierto ,
Enablers of post-COVID-19 customer demand resilience: evidence for fast-fashion MSMEs
(Emerald Publishing Limited, 2023-07-06) Fares, Naila; Lloret, Jaime; Kumar. Vikas; Frederico, Guilherme F.; Kumar, Anil; Garza-Reyes, Jose Arturo; Departamento de Comunicaciones; Escuela Politécnica Superior de Gandia
[EN] Purpose This study aims to analyse the resilience of customer demand management post-coronavirus disease 2019, using fast fashion as an example. The paper provides insights for potential applications to micro-, small and medium enterprises (MSMEs). Design/methodology/approach Based on the qualitative analysis and an integrated Plan-Do-Check-Act (PDCA)-decision making trial and evaluation laboratory (DEMATEL)-fuzzy technique for order of preference by similarity to the ideal solution (TOPSIS) methodology of fuzzy multi-criteria decision-making, we explored and prioritised the enablers of resilience management for fast-fashion MSMEs. Findings The results reveal that the highest priority enabler is maintaining customer loyalty. Other enablers are associated with e-commerce endorsement, a customer-focussed assortment of items and flexible store operations. Research limitations/implications The study findings will enable fast-fashion MSMEs to develop effective actions and priorities in operations efforts to promote post-pandemic recovery. Originality/value Despite the importance of the resilience project and the changing fast-fashion customer patterns, only a handful of studies have explored how resilience can be managed in this field. Thus, the findings can contribute to closing this gap in the context of operations resilience research as well as MSME operations.
Access status: Abierto ,
Discrimination of non-infectious SARS-CoV-2 particles from fomites by viability RT-qPCR
(Elsevier, 2022-01) Cuevas-Ferrando, Enric; Girón-Guzmán, Inés; Falcó, Irene; Pérez-Cataluña, Alba; Díaz-Reolid, Azahara; Aznar, Rosa; Randazzo, Walter; Sánchez, Gloria; EIT Food; Generalitat Valenciana; Agencia Estatal de Investigación; European Regional Development Fund; Consejo Superior de Investigaciones Científicas; Ministerio de Educación y Formación Profesional
[EN] The ongoing coronavirus 2019 (COVID-19) pandemic constitutes a concerning global threat to public health and economy. In the midst of this pandemic scenario, the role of environment-to-human COVID-19 spread is still a matter of debate because mixed results have been reported concerning SARS-CoV-2 stability on high-touch surfaces in real-life scenarios. Up to now, no alternative and accessible procedures for cell culture have been applied to evaluate SARS-CoV-2 infectivity on fomites. Several strategies based on viral capsid integrity have latterly been developed using viability markers to selectively remove false-positive qPCR signals resulting from free nucleic acids and damaged viruses. These have finally allowed an estimation of viral infectivity. The present study aims to provide a rapid molecular-based protocol for detection and quantification of viable SARS-CoV-2 from fomites based on the discrimination of non-infectious SARS-CoV-2 particles by platinum chloride (IV) (PtCl4) viability RT-qPCR. An initial assessment compared two different swabbing procedures to recover inactivated SARS-CoV-2 particles from fomites coupled with two RNA extraction methods. Procedures were validated with human (E229) and porcine (PEDV) coronavirus surrogates, and compared with inactivated SARS-CoV-2 suspensions on glass, steel and plastic surfaces. The viability RT-qPCR efficiently removed the PCR amplification signals from heat and gamma-irradiated inactivated SARS-CoV-2 suspensions that had been collected from specified surfaces. This study proposes a rapid viability RT-qPCR that discriminates non-infectious SARS-CoV-2 particles on surfaces thus helping researchers to better understand the risk of contracting COVID-19 through contact with fomites and to develop more efficient epidemiological measures.
Access status: Cerrado ,
Spatial and temporal distribution of SARS-CoV-2 diversity circulating in wastewater.
(Elsevier, 2022-03-01) Pérez-Cataluña, Alba; Chiner-Oms, Álvaro; Cuevas-Ferrando, Enric; Díaz-Reolid, Azahara; Falcó, Irene; Randazzo, Walter; Girón-Guzmán, Inés; Allende, Ana; Bracho, María A.; Comas, Iñaki; Sánchez, Gloria; European Commission; Generalitat Valenciana; Agencia Estatal de Investigación; Consejo Superior de Investigaciones Científicas
[EN] Wastewater-based epidemiology (WBE) has proven to be an effective tool for epidemiological surveillance of SARS-CoV-2 during the current COVID-19 pandemic. Furthermore, combining WBE together with highthroughput sequencing techniques can be useful for the analysis of SARS-CoV-2 viral diversity present in a given sample. The present study focuses on the genomic analysis of SARS-CoV-2 in 76 sewage samples collected during the three epidemiological waves that occurred in Spain from 14 wastewater treatment plants distributed throughout the country. The results obtained demonstrate that the metagenomic analysis of SARS-CoV-2 in wastewater allows the detection of mutations that define the B.1.1.7 lineage and the ability of the technique to anticipate the detection of certain mutations before they are detected in clinical samples. The study proves the usefulness of sewage sequencing to track Variants of Concern that can complement clinical testing to help in decision-making and in the analysis of the evolution of the pandemic.
Access status: Cerrado ,
Lung Cancer and SARS-CoV-2 infection: Identifying important knowledge gaps for investigation
(Elsevier, 2022-02) Rolfo, Christian; Meshulami, Noy; Russo, Alessandro; Krammer, Florian; Garcia-Sastre, Adolfo; Mack, Philip C.; Gomez, Jorge E.; Bhardwaj, Nina; Benyounes, Amin; Sirera Pérez, Rafael; Moore, Amy; Rohs, Nicholas; Henschke, Claudia I.; Yankelevitz, David; King, Jennifer; Departamento de Biotecnología; Centro Avanzado de Microbiología Aplicada; Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural; Open Philanthropy Project; National Cancer Institute, EEUU; National Institutes of Health, EEUU; National Institute of Allergy and Infectious Diseases, EEUU
[EN] Patients with lung cancer are especially vulnerable to coronavirus disease 2019 (COVID-19) with a greater than sevenfold higher rate of becoming infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) COVID-19, a greater than threefold higher hospitalization rate with high complication rates, and an estimated case fatality rate of more than 30%. The reasons for the increased vulnerability are not known. In addition, beyond the direct impact of the pandemic on morbidity and mortality among patients with lung cancer, COVID-19, with its disruption of patient care, has also resulted in substantial impact on lung cancer screening and treatment/management.COVID-19 vaccines are safe and effective in people with lung cancer. On the basis of the available data, patients with lung cancer should continue their course of cancer treatment and get vaccinated against the SARS-CoV-2 virus. For unknown reasons, some patients with lung cancer mount poor antibody responses to vaccination. Thus, boosting vaccination seems urgently indicated in this subgroup of vulnerable patients with lung cancer. Nevertheless, many unanswered questions regarding vaccination in this population remain, including the magnitude, quality, and duration of antibody response and the role of innate and acquired cellular immunities for clinical protection. Additional important knowledge gaps also remain, including the following: how can we best protect patients with lung cancer from developing COVID-19, including managing care in patient with lung cancer and the home environment of patients with lung cancer; are there clinical/treatment demographics and tumor molecular demographics that affect severity of COVID-19 disease in patients with lung cancer; does anticancer treatment affect antibody production and protection; does SARS-CoV-2 infection affect the develop-ment/progression of lung cancer; and are special measures and vaccine strategies needed for patients with lung cancer as viral variants of concern emerge.
Access status: Abierto ,
How does the COVID-19 economic crisis impact resilience? A configurational analysis of the spinoffs.
(Springer-Verlag, 2023-12-22) Castello-Sirvent, Fernando; Peris-Ortiz, Marta; Llopis-Amorós, Malar; Pinazo-Dallenbach, Pablo; Departamento de Organización de Empresas; Departamento de Proyectos de Ingeniería; Escuela Técnica Superior de Ingeniería Industrial; Centro de Investigación en Dirección de Proyectos, Innovación y Sostenibilidad (PRINS)
[EN] Spin-offs are companies with a high level of disruption that facilitate University-Society-Business knowledge transfer, promoting innovation and economic development of knowledge-based economies. On the other hand, globalization, climate change and anthropogenic pressure increase the probability of the appearance of community-transmitted pandemics between animals and people. In this context, the study of the conditions that facilitate resilience in companies with a high innovative content are important to guarantee long-term economic development. COVID-19 presents the appropriate conditions for carrying out an exploratory natural experiment that allows the identification, description, and analysis of conditions that facilitated the resilience of spin-offs promoted in a technological university. A database of spin-offs created before COVID-19 in the Universitat Politècnica de València was analyzed. A causal model was proposed and tested with fsQCA to identify the conditions that facilitate the business resilience of this type of startups with a high technological component that link areas of university research with the market. The proposed model defines resilience as the ability of a spin-off to withstand the impact of the shock, calculating differences of natural logarithms of sales in 2020 and 2019. The causal conditions used in the model are TMT Gender Diversity, the Distribution of Added Value to Workers and Ambidexterity (concerning Exploitation and Exploration). The results of this study show the necessary and sufficient conditions for the resilience to environmental shocks of spin-offs from a polytechnic university. This research offers promising lines of development for academics and suggests to policy makers ways to develop public¿private initiatives and investment to improve business performance in crisis contexts. The results of this article offer practitioners a useful guide to design strategies that improve the resilience of these types of companies. This exploratory study based on case analysis makes it possible to identify design elements of the strategy that improve resilience before supply crises. A relevant contribution of this research is linked to its managerial implications in the design of strategies to improve resilience in crisis management. The lessons learned and the analysis of best practices can help improve the robustness of new spin offs in a context of crises caused by recurring pandemics.

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