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Spadea A, Oleiro Hidalgo M, Quevedo S, Begue C, L'Arco G, Pérez A, Cueto G, Konfino J. La equidad en la campaña de vacunación COVID de la Provincia de Buenos Aires (Argentina): un análisis del Municipio de Quilmes. Glob Health Promot 2024:17579759231219493. [PMID: 38293782 DOI: 10.1177/17579759231219493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
INTRODUCCIÓN la pandemia de la COVID-19 ha acentuado las desigualdades sociales, económicas y relacionadas con la salud, afectando desproporcionadamente a las personas en situación de vulnerabilidad y perpetuando la inequidad en salud. En Argentina se implementó una campaña nacional gratuita de vacunación contra la COVID-19 con una perspectiva de equidad. OBJETIVO identificar desigualdades territoriales en el acceso a la vacunación contra la COVID-19 en Quilmes. MÉTODOS se analizó la información referida a la vacunación contra la COVID-19 de personas residentes en el Municipio. Se efectuó la georreferenciación de cada vacunatorio y de cada persona a partir del domicilio declarado en el momento de la vacunación. Para caracterizar el grado de vulnerabilidad de las personas vacunadas, a cada una se le asignó el índice de carencias múltiples (ICM) correspondiente al radio censal de residencia. RESULTADOS al menos el 82 % de la población completó el esquema primario de vacunación (dosis 1 y dosis 2), porcentaje que alcanzó el 97 % en los mayores de 65 años. Analizando la media de dosis aplicadas se observa algo similar con un gradiente hacia los quintiles más altos pero con una mínima diferencia entre sí, situación que también se corrobora en todos los grupos etarios. DISCUSIÓN no se observaron brechas significativas entre los diferentes niveles socioeconómicos. Si bien se observó un mínimo gradiente en el promedio de dosis recibidas, el tiempo de acceso a las diferentes vacunas y el porcentaje de esquemas primarios completos recibidos, las mismas tienen escasa relevancia clínica y sanitaria.
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Affiliation(s)
- Agostina Spadea
- Secretaría de Salud de Quilmes, Quilmes, Buenos Aires, Argentina
| | | | - Sofía Quevedo
- Secretaría de Salud de Quilmes, Buenos Aires, Argentina
| | - Carolina Begue
- Secretaría de Salud de Quilmes, Quilmes, Buenos Aires, Argentina
| | - Gabriela L'Arco
- Secretaría de Salud de Quilmes, Quilmes, Buenos Aires, Argentina
| | - Adriana Pérez
- Grupo de Bioestadística Aplicada. Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Gerardo Cueto
- Grupo de Bioestadística Aplicada. Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Jonatan Konfino
- Centro de Estudios de Estado y Sociedad (CEDES), Buenos Aires, Argentina
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Hon C, Liang J, Chen R, Lin Z, Wang Y, He W, Liu R, Sun J, Li Q, Liang L, Zhang M, Chang Z, Guo Y, Zeng W, Liu T, Oliveira AL. Temporary impact on medical system and effectiveness of mitigation strategies after COVID-19 policy adjustment in China: a modeling study. Front Public Health 2023; 11:1259084. [PMID: 38106897 PMCID: PMC10722892 DOI: 10.3389/fpubh.2023.1259084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Accepted: 10/19/2023] [Indexed: 12/19/2023] Open
Abstract
Background As China amends its "zero COVID" strategy, a sudden increase in the number of infections may overwhelm medical resources and its impact has not been quantified. Specific mitigation strategies are needed to minimize disruption to the healthcare system and to prepare for the next possible epidemic in advance. Method We develop a stochastic compartmental model to project the burden on the medical system (that is, the number of fever clinic visits and admission beds) of China after adjustment to COVID-19 policy, which considers the epidemiological characteristics of the Omicron variant, age composition of the population, and vaccine effectiveness against infection and severe COVD-19. We also estimate the effect of four-dose vaccinations (heterologous and homologous), antipyretic drug supply, non-pharmacological interventions (NPIs), and triage treatment on mitigating the domestic infection peak. Result As to the impact on the medical system, this epidemic is projected to result in 398.02 million fever clinic visits and 16.58 million hospitalizations, and the disruption period on the healthcare system is 18 and 30 days, respectively. Antipyretic drug supply and booster vaccination could reduce the burden on emergency visits and hospitalization, respectively, while neither of them could not reduce to the current capacity. The synergy of several different strategies suggests that increasing the heterologous booster vaccination rate for older adult to over 90% is a key measure to alleviate the bed burden for respiratory diseases on the basis of expanded healthcare resource allocation. Conclusion The Omicron epidemic followed the adjustment to COVID-19 policy overloading many local health systems across the country at the end of 2022. The combined effect of vaccination, antipyretic drug supply, triage treatment, and PHSMs could prevent overwhelming medical resources.
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Affiliation(s)
- Chitin Hon
- Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, China
- Guangzhou Laboratory, Guangzhou, Guangdong, China
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, China
| | - Jingyi Liang
- Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, China
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, China
| | - Ruihan Chen
- Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, China
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, China
| | - Zhijie Lin
- Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, China
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, China
| | - Yangqianxi Wang
- Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, China
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, China
| | - Wei He
- Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, China
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, China
| | - Ruibin Liu
- Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, China
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, China
| | - Jiaxi Sun
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
| | - Qianyin Li
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Lixi Liang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Minyi Zhang
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
| | - Zichen Chang
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
| | - Yinqiu Guo
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
| | - Wenting Zeng
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
| | - Tie Liu
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
| | - Arlindo L. Oliveira
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, China
- Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento em Lisboa, Lisboa, Portugal
- Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal
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Bottero D, Rudi E, Martin Aispuro P, Zurita E, Gaillard E, Gonzalez Lopez Ledesma MM, Malito J, Stuible M, Ambrosis N, Durocher Y, Gamarnik AV, Wigdorovitz A, Hozbor D. Heterologous booster with a novel formulation containing glycosylated trimeric S protein is effective against Omicron. Front Immunol 2023; 14:1271209. [PMID: 38022542 PMCID: PMC10667599 DOI: 10.3389/fimmu.2023.1271209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 10/26/2023] [Indexed: 12/01/2023] Open
Abstract
In this study, we evaluated the efficacy of a heterologous three-dose vaccination schedule against the Omicron BA.1 SARS-CoV-2 variant infection using a mouse intranasal challenge model. The vaccination schedules tested in this study consisted of a primary series of 2 doses covered by two commercial vaccines: an mRNA-based vaccine (mRNA1273) or a non-replicative vector-based vaccine (AZD1222/ChAdOx1, hereafter referred to as AZD1222). These were followed by a heterologous booster dose using one of the two vaccine candidates previously designed by us: one containing the glycosylated and trimeric spike protein (S) from the ancestral virus (SW-Vac 2µg), and the other from the Delta variant of SARS-CoV-2 (SD-Vac 2µg), both formulated with Alhydrogel as an adjuvant. For comparison purposes, homologous three-dose schedules of the commercial vaccines were used. The mRNA-based vaccine, whether used in heterologous or homologous schedules, demonstrated the best performance, significantly increasing both humoral and cellular immune responses. In contrast, for the schedules that included the AZD1222 vaccine as the primary series, the heterologous schemes showed superior immunological outcomes compared to the homologous 3-dose AZD1222 regimen. For these schemes no differences were observed in the immune response obtained when SW-Vac 2µg or SD-Vac 2µg were used as a booster dose. Neutralizing antibody levels against Omicron BA.1 were low, especially for the schedules using AZD1222. However, a robust Th1 profile, known to be crucial for protection, was observed, particularly for the heterologous schemes that included AZD1222. All the tested schedules were capable of inducing populations of CD4 T effector, memory, and follicular helper T lymphocytes. It is important to highlight that all the evaluated schedules demonstrated a satisfactory safety profile and induced multiple immunological markers of protection. Although the levels of these markers were different among the tested schedules, they appear to complement each other in conferring protection against intranasal challenge with Omicron BA.1 in K18-hACE2 mice. In summary, the results highlight the potential of using the S protein (either ancestral Wuhan or Delta variant)-based vaccine formulation as heterologous boosters in the management of COVID-19, particularly for certain commercial vaccines currently in use.
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Affiliation(s)
- Daniela Bottero
- Laboratorio VacSal, Instituto de Biotecnología y Biología Molecular (IBBM), Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Centro Científico Tecnológico – Consejo Nacional de Investigaciones Científicas y Técnicas (CCT-CONICET), La Plata, Argentina
| | - Erika Rudi
- Laboratorio VacSal, Instituto de Biotecnología y Biología Molecular (IBBM), Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Centro Científico Tecnológico – Consejo Nacional de Investigaciones Científicas y Técnicas (CCT-CONICET), La Plata, Argentina
| | - Pablo Martin Aispuro
- Laboratorio VacSal, Instituto de Biotecnología y Biología Molecular (IBBM), Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Centro Científico Tecnológico – Consejo Nacional de Investigaciones Científicas y Técnicas (CCT-CONICET), La Plata, Argentina
| | - Eugenia Zurita
- Laboratorio VacSal, Instituto de Biotecnología y Biología Molecular (IBBM), Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Centro Científico Tecnológico – Consejo Nacional de Investigaciones Científicas y Técnicas (CCT-CONICET), La Plata, Argentina
| | - Emilia Gaillard
- Laboratorio VacSal, Instituto de Biotecnología y Biología Molecular (IBBM), Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Centro Científico Tecnológico – Consejo Nacional de Investigaciones Científicas y Técnicas (CCT-CONICET), La Plata, Argentina
| | - Maria M. Gonzalez Lopez Ledesma
- Fundación Instituto Leloir-Instituto de Investigaciones Bioquímicas de Buenos Aires (IIBBA) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Juan Malito
- INCUINTA Instituto Nacional de Tecnología Agropecuaria (INTA), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), HURLINGHAM, Instituto Nacional de Tecnología Agropecuaria (INTA) Castelar, Buenos Aires, Argentina
| | - Matthew Stuible
- Human Health Therapeutics Research Center, National Research Council Canada, Montreal, QC, Canada
| | - Nicolas Ambrosis
- Laboratorio VacSal, Instituto de Biotecnología y Biología Molecular (IBBM), Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Centro Científico Tecnológico – Consejo Nacional de Investigaciones Científicas y Técnicas (CCT-CONICET), La Plata, Argentina
| | - Yves Durocher
- Human Health Therapeutics Research Center, National Research Council Canada, Montreal, QC, Canada
| | - Andrea V. Gamarnik
- Fundación Instituto Leloir-Instituto de Investigaciones Bioquímicas de Buenos Aires (IIBBA) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Andrés Wigdorovitz
- INCUINTA Instituto Nacional de Tecnología Agropecuaria (INTA), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), HURLINGHAM, Instituto Nacional de Tecnología Agropecuaria (INTA) Castelar, Buenos Aires, Argentina
| | - Daniela Hozbor
- Laboratorio VacSal, Instituto de Biotecnología y Biología Molecular (IBBM), Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Centro Científico Tecnológico – Consejo Nacional de Investigaciones Científicas y Técnicas (CCT-CONICET), La Plata, Argentina
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