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The COVID-19 pandemic underscored the need for rapid evidence generation to inform public health decisions beyond the limitations of conventional clinical trials. This report summarises presentations and discussions from a conference on the role of Real-World Evidence (RWE) in expediting vaccine deployment. Attended by regulatory bodies, public health entities, and industry experts, the gathering was a collaborative exchange of experiences and recommendations for leveraging RWE for vaccine deployment. RWE proved instrumental in refining decision-making processes to optimise dosing regimens, enhance guidance on target populations, and steer vaccination strategies against emerging variants. Participants felt that RWE was successfully integrated into lifecycle management, encompassing boosters and safety considerations. However, challenges emerged, prompting a call for improvements in data quality, standardisation, and availability, acknowledging the variability and potential inaccuracies in data across diverse healthcare systems. Regulatory transparency should also be prioritised to foster public trust, and improved collaborations with governments are needed to streamline data collection and navigate data privacy regulations. Moreover, building and sustaining resources, expertise, and infrastructure in LMICs emerged as imperative for RWE-generating capabilities. Continued stakeholder collaboration and securing adequate funding emerged as vital pillars for advancing the use of RWE in shaping responsive and effective public health strategies.
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Pandemias , Vacinas , Humanos , Pandemias/prevenção & controle , Saúde PúblicaRESUMO
This report introduces a Brighton Collaboration (BC) case definition for autoimmune hepatitis (AIH), which has been classified as a priority adverse event of special interest (AESI), as there were possible cases seen following COVID-19 vaccination. The case definition was developed by a group of subject matter and BC process experts to facilitate safety data comparability across pre- and post-licensure clinical trials, as well as pharmacovigilance activities in multiple settings with diverse resources and healthcare access. The usual BC case definition development process was followed in an expedited manner, and took two months to complete, including finalising the manuscript for publication, instead of the usual 1 year development time. It includes a systematic review of the literature and an expert consensus to define levels of diagnostic certainty for AIH, and provides specific guidelines for data collection and analysis. Histology, serological and biochemical tests and exclusion of alternate diagnosis were considered necessary to define the levels of certainty (definitive, probable and possible). AEFI reports of suspected AIH were independently classified by the WG members to test its useability and these classifications were used to finalise the case definition. The document underwent peer review by external AIH experts and a Reference Group of vaccine safety stakeholders in high-, low- and middle-income countries to ensure case definition useability, applicability, and scientific integrity. The expedited process can be replicated for development of other standardised case definitions for priority AESIs for endemics and epidemics. While applicable to cases reported following immunisation, the case definition is independent of lapsed time following vaccination and, as such, can also be used to determine background incidence for vaccinated and unvaccinated control groups in studies of causal association. While use of this case definition is also appropriate for the study of safety of other products including drugs, it is not meant to guide clinical case management.
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Hepatite Autoimune , Humanos , Hepatite Autoimune/diagnóstico , Vacinas contra COVID-19/efeitos adversos , Farmacovigilância , Coleta de Dados/normas , Vacinação/efeitos adversos , Sistemas de Notificação de Reações Adversas a Medicamentos/normas , COVID-19/prevenção & controle , COVID-19/diagnóstico , Imunização/efeitos adversos , SARS-CoV-2/imunologiaRESUMO
Background: Long-term care residents were among the most vulnerable during the COVID-19 pandemic. We estimated vaccine effectiveness of mRNA COVID-19 vaccines in Medicare nursing home residents aged ≥65 years during pre-Delta and high Delta periods. Methods: We conducted a retrospective cohort study from 13 December 2020 to 20 November 2021 using Medicare claims data. Exposures included 2 and 3 doses of Pfizer-BioNTech and Moderna COVID-19 vaccines. We used inverse probability weighting and Cox proportional hazards models to estimate absolute and relative vaccine effectiveness. Results: Two-dose vaccine effectiveness against COVID-19-related death was 69.8% (95% CI, 65.9%â73.3%) during the pre-Delta period and 55.7% (49.5%â61.1%) during the high Delta period, without adjusting for time since vaccination. We observed substantial waning of effectiveness from 65.1% (54.2%â73.5%) within 6 months from second-dose vaccination to 45.2% (30.6%â56.7%) ≥6 months after second-dose vaccination in the high Delta period. Three doses provided 88.7% (73.5%â95.2%) vaccine effectiveness against death, and the incremental benefit of 3 vs 2 doses was 74.6% (40.4%â89.2%) during high Delta. Among beneficiaries with a prior COVID-19 infection, 3-dose vaccine effectiveness for preventing death was 78.6% (50.0%â90.8%), and the additional protection of 3 vs 2 doses was 70.0% (30.1%â87.1%) during high Delta. Vaccine effectiveness estimates against less severe outcomes (eg, infection) were lower. Conclusions: This nationwide real-world study demonstrated that mRNA COVID-19 vaccines provided substantial protection against COVID-19-related death. Two-dose protection waned after 6 months. Third doses during the high Delta period provided significant additional protection for individuals with or without a prior COVID-19 infection.
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Vaccine Benefit-Risk (B-R) assessment consists of evaluating the benefits and risks of a vaccine and making a judgment whether the expected key benefits outweigh the potential key risks associated with its expected use. B-R supports regulatory and public health decision-making throughout the vaccine's lifecycle. In August 2021, the Brighton Collaboration's Benefit-Risk Assessment of VAccines by TechnolOgy (BRAVATO) Benefit-Risk Assessment Module working group was established to develop a standard module to support the planning, conduct and evaluation of structured B-R assessments for vaccines from different platforms, based on data from clinical trials, post-marketing studies and real-world evidence. It enables sharing of relevant information via value trees, effects tables and graphical depictions of B-R trade-offs. It is intended to support vaccine developers, funders, regulators and policy makers in high-, middle- or low-income countries to help inform decision-making and facilitate transparent communication concerning development, licensure, deployment and other lifecycle decisions.
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Vacinas , Medição de Risco , Vacinas/efeitos adversos , HumanosRESUMO
Según lo establecido por la Organización Panamericana de la Salud (OPS), conseguir una alta cobertura de vacunación es una meta esencial para la Región de las Américas. Es indispensable lograr niveles de cobertura de 95 por ciento o mayores para poder alcanzar los objetivos de la OPS de eliminar el sarampión y la rubéola, controlar las enfermedades prevenibles mediante la vacunación, y hacer perdurar la eliminación de la poliomielitis en territorio americano. Para poder alcanzar esos niveles, es imprescindible que las estadísticas de vacunación sean fiables y que las autoridades sanita- rias midan y monitoreen los niveles de cobertura a lo largo del tiempo. Los métodos elegidos por los directores de los programas de vacunación para calcular la cobertura dependerán de la información que haga falta. En general, los directores del Programa Ampliado de Inmunización (PAI) necesitarán información acerca de la cobertura para poder: 1) determinar la verdadera cobertura en los niveles nacional y local, 2) determinar cuán adecuada es la cobertura en una zona determinada, 3) monitorear las tendencias a lo largo del tiempo, y 4) monitorear las actividades de vacunación mientras se están llevando a cabo. Para lograr lo primero -determinar cuáles son los niveles verdaderos de cobertura-, los administradores tienen dos opciones: a) valerse de los datos acerca de las dosis administradas (es decir, el número de dosis de la vacuna que se ha administrado, dividido por la población que debió recibir una dosis) o b) llevar a cabo una encuesta para determinar la cobertura. Para lograr lo segundo -saber si la cobertura en una zona determinada es adecuada (por ej., mayor de 90 por ciento)-, se puede realizar un muestreo por lotes para garantizar la calidad (MLGC). El MLGC es una metodología de encuesta basada en el uso de muestras pequeñas que permite determinar si la cobertura en una zona determinada es adecuada o no, pero no sirve para estimar el nivel de cobertura. Para el tercer propósito -monitorear las tendencias a lo largo del tiempo-, se pueden usar los datos correspondientes al número de dosis administradas. Para lograr el cuarto propósito -determinar si procede vacunar o llevar a cabo una campaña de vacunación u otra actividad afín-, la "herramienta de monitoreo rápido" creada por la OPS es una magnífica solución. Cada uno de estos métodos posee ventajas y desventajas. Los datos sobre el número de dosis...