Barriers and facilitators to mental health promotion for Mexican immigrants in the U.S. through the Ventanillas de Salud program

IntroductionMental health promotion and screenings are recommended as part of standard preventive care. Mexican immigrants in the U.S. are at high risk for mental health illness especially after the COVID-19 pandemic, however access to mental health prevention for this population has been limited, which results in important implementation and equity gaps. The Ventanilla de Salud (VDS) program provides preventive services through Mexican consulates in the U.S.ObjectiveThe objective of this study was to assess capability, opportunity, and motivation for promotores to implement mental health programming through the VDS, leveraging early experiences of ongoing mental health prevention efforts.MethodsThis was a qualitative study using the Capability, Opportunity, and Motivation for Behavior Change model (COM-B). We conducted 9 focus groups with 40 VDS promotores and 6 semi-structured interviews with program stakeholders. Data were analyzed using inductive and deductive coding.ResultsWe found high levels of interest from the leadership, partners, and promotores to provide mental health services through the VDS. Early implementation of a mental health strategy that included training sessions for promotores and mental health promotion, screenings and referrals for VDS users was ongoing. We identified facilitators and barriers that could affect capability, opportunity, and motivation to provide mental health services. Facilitators included promotores’ extensive knowledge about the importance of mental health, promotores service mindset and commitment to provide services to VDS users, and general support from the VDS network and partners. Barriers included promotores’ turnover, need for additional economic compensation, burnout, competing priorities, and lack of mental health professionals to provide clinical services or supervision. Additional investments are recommended to support promotores’ well-being.ConclusionThe main lesson learned from this study was that investing in VDS promotores’ training, resources, and well-being is key to their capability, opportunity and motivation to provide mental health services for Mexican immigrants in the US. Results from this study can be applied to improve the ongoing VDS mental health strategy and increase its impact on the mental health of Mexican immigrants

Cost-effective method to perform SARS-CoV-2 variant surveillance: detection of Alpha, Gamma, Lambda, Delta, Epsilon, and Zeta in Argentina

SARS-CoV-2 variants with concerning characteristics have emerged since the end of 2020. Surveillance of SARS-CoV-2 variants was performed on a total of 4,851 samples from the capital city and 10 provinces of Argentina, during 51 epidemiological weeks (EWs) that covered the end of the first wave and the ongoing second wave of the COVID-19 pandemic in the country (EW 44/2020 to EW 41/2021). The surveillance strategy was mainly based on Sanger sequencing of a Spike coding region that allows the identification of signature mutations associated with variants. In addition, whole-genome sequences were obtained from 637 samples. The main variants found were Gamma and Lambda, and to a lesser extent, Alpha, Zeta, and Epsilon, and more recently, Delta. Whereas, Gamma dominated in different regions of the country, both Gamma and Lambda prevailed in the most populated area, the metropolitan region of Buenos Aires. The lineages that circulated on the first wave were replaced by emergent variants in a term of a few weeks. At the end of the ongoing second wave, Delta began to be detected, replacing Gamma and Lambda. This scenario is consistent with the Latin American variant landscape, so far characterized by a concurrent increase in Delta circulation and a stabilization in the number of cases. The cost-effective surveillance protocol presented here allowed for a rapid response in a resource-limited setting, added information on the expansion of Lambda in South America, and contributed to the implementation of public health measures to control the disease spread in Argentina.Fil: Torres, Carolina. Instituto de Investigaciones En Bacteriologia y Virologia Molecular (ibavim) ; Facultad de Farmacia y Bioquimica ; Universidad de Buenos Aires; . Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Mojsiejczuk, Laura Noelia. Instituto de Investigaciones En Bacteriologia y Virologia Molecular (ibavim) ; Facultad de Farmacia y Bioquimica ; Universidad de Buenos Aires; . Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Acuña, Dolores. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez". Laboratorio de Virología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Alexay, Sofía. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez". Laboratorio de Virología; ArgentinaFil: Amadio, Ariel Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación de la Cadena Láctea. - Instituto Nacional de Tecnología Agropecuaria. Centro Regional Santa Fe. Estación Experimental Agropecuaria Rafaela. Instituto de Investigación de la Cadena Láctea; ArgentinaFil: Aulicino, Paula. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan". Laboratorio de Biología Celular y Retrovirus; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Debat, Humberto Julio. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigaciones Agropecuarias. Instituto de Patología Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Fay, Fabian. CIBIC Laboratorio; ArgentinaFil: Fernández, Franco. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigaciones Agropecuarias. Instituto de Patología Vegetal; ArgentinaFil: Giri, Adriana Angelica. Consejo Nacional de Investigaciones Científicas y Técnicas Centro Científico Tecnológico - CONICET -Rosario. Instituto de Biologia Molecular y Celular de Rosario; ArgentinaFil: Goya, Stephanie. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan". Laboratorio de Biología Celular y Retrovirus; ArgentinaFil: König, Guido Alberto. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Lucero, Horacio. Universidad Nacional del Nordeste. Instituto de Medicina Regional; ArgentinaFil: Nabaes Jodar, Mercedes Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez". Laboratorio de Virología; ArgentinaFil: Pianciola, Luis. Gobierno de la Provincia del Neuquén. Ministerio de Salud. Secretaría de Salud Pública Neuquén; ArgentinaFil: Sfalcin, Javier A.. CIBIC Laboratorio; ArgentinaFil: Acevedo, Raúl Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Botánica del Nordeste. Universidad Nacional del Nordeste. Facultad de Ciencias Agrarias. Instituto de Botánica del Nordeste; ArgentinaFil: Bengoa Luoni, Sofia Ailin. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Bolatti, Elisa Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Brusés, Bettina Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Botánica del Nordeste. Universidad Nacional del Nordeste. Facultad de Ciencias Agrarias. Instituto de Botánica del Nordeste; ArgentinaFil: Cacciabue, Marco Polo Domingo. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Casal, Pablo Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Cerri, Agustina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Chouhy, Diego. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Dus Santos, María José. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Virología e Innovaciones Tecnológicas. Grupo Vinculado Incuinta al IVIT | Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Virología e Innovaciones Tecnológicas. Grupo Vinculado Incuinta al IVIT; Argentina. Universidad Nacional de Hurlingham; ArgentinaFil: Eberhardt, Maria Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación de la Cadena Láctea. - Instituto Nacional de Tecnología Agropecuaria. Centro Regional Santa Fe. Estación Experimental Agropecuaria Rafaela. Instituto de Investigación de la Cadena Láctea; ArgentinaFil: Fernández, Ailén. Gobierno de la Provincia del Neuquén. Ministerio de Salud. Secretaría de Salud Pública Neuquén; ArgentinaFil: Fernández, Paula del Carmen. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Fernández Do Porto, Darío Augusto. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; ArgentinaFil: Formichelli, Laura Belén. Universidad Nacional del Nordeste. Instituto de Medicina Regional; ArgentinaFil: Gismondi, María Inés. Universidad Nacional de Lujan. Departamento de Ciencias Básicas. Laboratorio de Genómica Computacional; Argentina. CIBIC Laboratorio; ArgentinaFil: Irazoqui, José Matías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación de la Cadena Láctea. - Instituto Nacional de Tecnología Agropecuaria. Centro Regional Santa Fe. Estación Experimental Agropecuaria Rafaela. Instituto de Investigación de la Cadena Láctea; ArgentinaFil: Lorenzini Campos, Melina Noelia. Universidad Nacional del Nordeste. Instituto de Medicina Regional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lusso, Silvina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez". Laboratorio de Virología; ArgentinaFil: Marquez, Nathalie. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigaciones Agropecuarias. Instituto de Patología Vegetal; ArgentinaFil: Muñoz, Marianne. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Mussin, Javier Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Nordeste. Instituto de Medicina Regional; ArgentinaFil: Natale, Mónica Inés. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez". Laboratorio de Virología; ArgentinaFil: Oria, Griselda Ines. Universidad Nacional del Nordeste. Instituto de Medicina Regional; ArgentinaFil: Pisano, María Belén. Universidad Nacional de Córdoba. Facultad de Medicina. Instituto de Virología Dr. J. M. Vanella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Posner, Victoria Maria. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Laboratorio de Biotecnología Acuática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Puebla, Andrea. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Ré, Viviana Elizabeth. Universidad Nacional de Córdoba. Facultad de Medicina. Instituto de Virología Dr. J. M. Vanella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Sosa, Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Villanova, Gabriela Vanina. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Laboratorio de Biotecnología Acuática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Zaiat, Jonathan Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Zunino, Sebastián. Gobierno de la Provincia de Buenos Aires. Hospital Zonal General de Agudos Blas Dubarry; Argentina. Gobierno de la Provincia del Neuquén. Ministerio de Salud. Secretaría de Salud Pública Neuquén; ArgentinaFil: Acevedo, María Elina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez". Laboratorio de Virología; ArgentinaFil: Acosta, Julián. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; ArgentinaFil: Alvarez Lopez, Cristina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez". Laboratorio de Virología; ArgentinaFil: Álvarez, María Laura. Gobierno de la Provincia de Río Negro. Hospital Zonal Doctor Ramón Carrillo; ArgentinaFil: Angeleri, Patricia. Gobierno de la Ciudad Autónoma de Buenos Aires. Ministerio de Salud; ArgentinaFil: Angelletti, Andrés. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Laboratorio de Salud Pública; Argentina. Gobierno de la Provincia de Buenos Aires. Hospital Interzonal Especializado de Agudos y Crónicos San Juan de Dios; ArgentinaFil: Arca, Manuel. Municipalidad de Concepción del Uruguay (Entre Ríos). Hospital Justo José de Urquiza; ArgentinaFil: Ayala, Natalia A.. Gobierno de la Provincia de Chaco. Ministerio de Salud Publica; ArgentinaFil: Barbas, Maria Gabriela. Gobierno de la Provincia de Córdoba. Ministerio de Salud. Secretaría de Prevención y Promoción; ArgentinaFil: Bertone, Ana. Gobierno de la Provincia de La Pampa. Laboratorio de la Dirección de Epidemiología. Santa Rosa; ArgentinaFil: Bonnet, Maria Agustina. Municipalidad de Concepción del Uruguay (Entre Ríos). Hospital Justo José de Urquiza; ArgentinaFil: Bourlot, Ignacio. Gobierno de la Provincia de Entre Ríos. Laboratorio de Biología Molecular del Hospital Centenario. Gualeguaychú; ArgentinaFil: Cabassi, María Victoria. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Laboratorio de Salud Pública; ArgentinaFil: Castello, Alejandro. Universidad Nacional de Quilmes; ArgentinaFil: Castro, Gonzalo. Gobierno de la Provincia de Córdoba. Ministerio de Salud. Laboratorio Central de la Provincia; ArgentinaFil: Cavatorta, Ana Laura. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ceriani, Maria Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; ArgentinaFil: Cimmino, Carlos José. Instituto Nacional de Epidemiología Dr. Jara. Mar del Plata; ArgentinaFil: Cipelli, Julián. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez". Laboratorio de Virología; ArgentinaFil: Colmeiro, María. Gobierno de la Provincia de Buenos Aires. Hospital Interzonal Especializado de Agudos y Crónicos San Juan de Dios; ArgentinaFil: Cordero, Andrés. Universidad Nacional de la Plata. Facultad de Ciencias Exactas. Laboratorio de Salud Pública; ArgentinaFil: Cristina, Silvia Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia del Noroeste de la Provincia de Buenos Aires. Universidad Nacional del Noroeste de la Provincia de Buenos Aires. Centro de Investigaciones y Transferencia del Noroeste de la Provincia de Buenos Aires; ArgentinaFil: Di Bella, Sofia. Gobierno de la Provincia de Buenos Aires. Hospital Interzonal Especializado de Agudos y Crónicos San Juan de Dios; ArgentinaFil: Dolcini, Guillermina Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; ArgentinaFil: Ercole, Regina. Gobierno de la Provincia de Buenos Aires. Hospital Interzonal Especializado de Agudos y Crónicos San Juan de Dios; ArgentinaFil: Espasandin, Yesica Romina. Gobierno de la Provincia de Río Negro. Hospital Zonal Doctor Ramón Carrillo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Espul, Carlos. Gobierno de la Provincia de Mendoza. Ministerio de Salud Desarrollo Social y Deportes; ArgentinaFil: Falaschi, Andrea. Gobierno de la Provincia de Buenos Aires. Hospital Interzonal Especializado de Agudos y Crónicos San Juan de Dios; ArgentinaFil: Fernández Moll, Facundo Lucio. Universidad Nacional del Noroeste de la Provincia de Buenos Aires. Centro de Bioinvestigaciones (Sede Junín); ArgentinaFil: Foussal, María Delia. Gobierno de la Provincia de Chaco. Hospital Julio César Perrando; ArgentinaFil: Gatelli, Andrea. Gobierno de la Provincia de Buenos Aires. Hospital Interzonal Especializado de Agudos y Crónicos San Juan de Dios; ArgentinaFil: Goñi, Sandra Elizabeth. Universidad Nacional de Quilmes; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Jofré, María Estela. Laboratorio de Biología Molecular Bolívar; ArgentinaFil: Jaramillo Ortiz, José Manuel. Gobierno de la Provincia de Buenos Aires. Hospital Zonal General de Agudos Blas Dubarry; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Labarta, Natalia. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez". Laboratorio de Virología; ArgentinaFil: Lacaze, María Agustina. Gobierno de la Provincia de San Luis. Ministerio de Salud; ArgentinaFil: Larreche Calahorrano, María Rocío. Laboratorio de Biología Molecular Bolívar; ArgentinaFil: Leiva, Viviana. Laboratorio de Salud Pública; ArgentinaFil: Levin, Gustavo Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Entre Ríos. Universidad Nacional de Entre Ríos. Centro de Investigaciones y Transferencia de Entre Ríos; ArgentinaFil: Luczak, Erica Natalia. Gobierno de la Provincia de Buenos Aires. Hospital Interzonal de Agudos Evita; ArgentinaFil: Mandile, Marcelo Gastón. Universidad Nacional de Quilmes; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Marino, Gioia. Provincia de Chaco. Hospital Pediátrico Dr. Avelino Castelán; ArgentinaFil: Massone, Carla Antonella. Gobierno de la Provincia de Buenos Aires. Hospital Zonal General de Agudos Blas Dubarry; ArgentinaFil: Mazzeo, Melina. Gobierno de la Provincia del Neuquen. Ministerio de Salud; ArgentinaFil: Medina, Carla. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez". Laboratorio de Virología; ArgentinaFil: Monaco, Belén. Gobierno de la Provincia de Buenos Aires. Hospital Zonal General de Agudos Blas Dubarry; ArgentinaFil: Montoto, Luciana. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños Pedro Elizalde (ex Casa Cuna); ArgentinaFil: Mugna, Viviana. Gobierno de la Provincia de Santa Fe. Ministerio de Salud. Laboratorio Central de la Provincia de Santa Fe; ArgentinaFil: Musto, Alejandra Beatriz. Laboratorio de Salud Pública; ArgentinaFil: Nadalich, Victoria. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Laboratorio de Salud Pública; ArgentinaFil: Nieto Farías, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; ArgentinaFil: Ojeda, Guillermo. Gobierno de la Provincia de Santa Fe. Ministerio de Salud. Laboratorio Central de la Provincia de Santa Fe; ArgentinaFil: Piedrabuena, Andrea C.. Servicio de Microbiología. Hospital 4 de junio. Roque Sáenz Peña; ArgentinaFil: Pintos, Carolina. Gobierno de la Provincia del Neuquen. Ministerio de Salud; ArgentinaFil: Pozzati, Marcia. Gobierno de la Ciudad Autónoma de Buenos Aires. Hospital General de Agudos Doctor Cosme Argerich; ArgentinaFil: Rahhal, Marilina. Gobierno de la Provincia de Buenos Aires. Hospital El Cruce Doctor Néstor Carlos Kirchner. Centro de Medicina Traslacional; ArgentinaFil: Rechimont, Claudia. Laboratorio de la Dirección de Epidemiología; ArgentinaFil: Remes Lenicov, Federico. Consejo Nacional de Investigaci

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Background: Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods: We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings: From 1950 to 2017, TFRs decreased by 49\ub74% (95% uncertainty interval [UI] 46\ub74–52\ub70). The TFR decreased from 4\ub77 livebirths (4\ub75–4\ub79) to 2\ub74 livebirths (2\ub72–2\ub75), and the ASFR of mothers aged 10–19 years decreased from 37 livebirths (34–40) to 22 livebirths (19–24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83\ub78 million people per year since 1985. The global population increased by 197\ub72% (193\ub73–200\ub78) since 1950, from 2\ub76 billion (2\ub75–2\ub76) to 7\ub76 billion (7\ub74–7\ub79) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2\ub70%; this rate then remained nearly constant until 1970 and then decreased to 1\ub71% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2\ub75% in 1963 to 0\ub77% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2\ub77%. The global average age increased from 26\ub76 years in 1950 to 32\ub71 years in 2017, and the proportion of the population that is of working age (age 15–64 years) increased from 59\ub79% to 65\ub73%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1\ub70 livebirths (95% UI 0\ub79–1\ub72) in Cyprus to a high of 7\ub71 livebirths (6\ub78–7\ub74) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0\ub708 livebirths (0\ub707–0\ub709) in South Korea to 2\ub74 livebirths (2\ub72–2\ub76) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0\ub73 livebirths (0\ub73–0\ub74) in Puerto Rico to a high of 3\ub71 livebirths (3\ub70–3\ub72) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2\ub70% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation: Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress. Funding: Bill &amp; Melinda Gates Foundation

Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Background: Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods: We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings: From 1950 to 2017, TFRs decreased by 49·4% (95% uncertainty interval [UI] 46·4–52·0). The TFR decreased from 4·7 livebirths (4·5–4·9) to 2·4 livebirths (2·2–2·5), and the ASFR of mothers aged 10–19 years decreased from 37 livebirths (34–40) to 22 livebirths (19–24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83·8 million people per year since 1985. The global population increased by 197·2% (193·3–200·8) since 1950, from 2·6 billion (2·5–2·6) to 7·6 billion (7·4–7·9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2·0%; this rate then remained nearly constant until 1970 and then decreased to 1·1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2·5% in 1963 to 0·7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2·7%. The global average age increased from 26·6 years in 1950 to 32·1 years in 2017, and the proportion of the population that is of working age (age 15–64 years) increased from 59·9% to 65·3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1·0 livebirths (95% UI 0·9–1·2) in Cyprus to a high of 7·1 livebirths (6·8–7·4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0·08 livebirths (0·07–0·09) in South Korea to 2·4 livebirths (2·2–2·6) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0·3 livebirths (0·3–0·4) in Puerto Rico to a high of 3·1 livebirths (3·0–3·2) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2·0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation: Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress

Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. Methods: We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting. Findings: Globally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 3·9% (95% uncertainty interval [UI] 3·1-4·6) from 1990 to 2017; however, the all-age YLD rate increased by 7·2% (6·0-8·4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7·9% (6·6-9·2) for males and 6·5% (5·4-7·7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs 1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-harm and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]). Interpretation: Global all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury

Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill &amp; Melinda Gates Foundation

Nuevos escenarios para la docencia universitaria : entornos híbridos y pedagogías emergentes.

Memorias del IX Simposio Internacional de Docencia Universitaria (SIDU)Los trabajos reunidos en esta Memoria representan una contribución importante al campo de la educación y de la docencia universitaria, en tanto muestran distintas maneras de responder a las problemáticas educativas cotidianas y presentan propuestas para afrontar los retos emergentes en el campo de la educación superior. Invitamos a los lectores a realizar una lectura atenta y crítica de los trabajos compilados en esta publicación. Estamos seguros de que este acercamiento propiciará la reflexión y el análisis riguroso de los objetos de estudio abordados por los autores, y estimulará la generación de nuevos proyectos de investigación, intervención e innovación educativa que incidan en el desarrollo de mejores prácticas de docencia en educación media superior y superior.Pimera edición digitaldoi.org/10.56019/EDU-CETYS.2024.182