In this paper, we study a single serotype transmission model of dengue to determine the optimal vaccination age for Dengvaxia. The transmission dynamics are modelled with an age-dependent force of infection. The force of infection for each serotype is derived from the serological profile of dengue in Brazil without serotype distinction and from serotype-specific reported cases. The risk due to an infection is measured by the probability of requiring hospitalization based on Brazilian Ministry of Health data. The optimal vaccination age is determined for any number and combination of the four distinct dengue virus serotypes DENv1-4. The lifetime expected risk is adapted to include antibody dependent enhancement (ADE) and permanent cross-immunity after two heterologous infections. The risk is assumed to be serostatus-dependent. The optimal vaccination age is computed for constant, serostatus-specific vaccine efficacies. Additionally, the vaccination age is restricted to conform to the licence of Dengvaxia in Brazil and the achievable and minimal lifetime expected risks are compared. The optimal vaccination age obtained for the risk of hospitalization varies significantly with the assumptions relating to ADE and cross-immunity. Risk-free primary infections lead to higher optimal vaccination ages, as do asymptomatic third and fourth infections. Sometimes vaccination is not recommended at all, e.g. for any endemic area with a single serotype if primary infections are risk-free. Restricting the vaccination age to Dengvaxia licensed ages mostly leads to only a slightly higher lifetime expected risk and the vaccine should be administered as close as possible to the optimal vaccination age.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1093/imammb/dqaa007 | DOI Listing |
J Infect Dev Ctries
December 2024
Faculdade de Medicina de Campos, Campos dos Goytacazes, Brazil.
Introduction: Despite efforts by health organizations to share evidence-based information, fake news hindered the promotion of social distancing and vaccination during the coronavirus disease 2019 (COVID-19) pandemic. This study analyzed COVID-19 knowledge and practices in a vulnerable area in northern Rio de Janeiro, acknowledging the influence of the complex social and economic landscape on public health perceptions.
Methodology: This cross-sectional study was conducted in Novo Eldorado - a low-income, conflict-affected neighborhood in Campos dos Goytacazes - using a structured questionnaire, following the peak of COVID-19 deaths in Brazil (July-December 2021).
EBioMedicine
January 2025
Institute of Immunology, Hannover Medical School, Hannover, Germany; Cluster of Excellence RESIST (EXC 2155), Hannover Medical School, Hannover, Germany; German Centre for Infection Research, Partner Site Hannover-Braunschweig, Hannover, Germany. Electronic address:
Background: Aging increases disease susceptibility and reduces vaccine responsiveness, highlighting the need to better understand the aging immune system and its clinical associations. Studying the human immune system, however, remains challenging due to its complexity and significant inter-individual variability.
Methods: We conducted an immune profiling study of 550 elderly participants (≥60 years) and 100 young controls (20-40 years) from the RESIST Senior Individuals (SI) cohort.
Health Policy
January 2025
Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom; National Institute for Health Research Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom; Centre For Health Policy, University of Melbourne, Parkville, VIC 3010, Australia. Electronic address:
Background COVID-19 vaccine hesitancy was a key barrier to ending the pandemic via mass immunisation. Objectives Assess magnitudes and differences in socioeconomic inequality in stated COVID-19 vaccine acceptance (hesitancy) and uptake. Methods Online surveys were conducted in 13 countries, collecting data from 15,337 and 18,189 respondents respectively.
View Article and Find Full Text PDFJ Am Med Inform Assoc
January 2025
Department of Cardiology, Royal North Shore Hospital, Sydney, NSW, Australia.
Objective: We aimed to develop a highly interpretable and effective, machine-learning based risk prediction algorithm to predict in-hospital mortality, intubation and adverse cardiovascular events in patients hospitalised with COVID-19 in Australia (AUS-COVID Score).
Materials And Methods: This prospective study across 21 hospitals included 1714 consecutive patients aged ≥ 18 in their index hospitalization with COVID-19. The dataset was separated into training (80%) and test sets (20%).
Front Biosci (Landmark Ed)
January 2025
Department of Surgery, Laboratory of Tumor Immunology and Immunotherapy, Morehouse School of Medicine, Atlanta, GA 30310, USA.
Immunology advances have increased our understanding of autoimmune, auto-inflammatory, immunodeficiency, infectious, and other immune-mediated inflammatory diseases (IMIDs). Furthermore, evidence is growing for the immune involvement in aging, metabolic and neurodegenerative diseases, and different cancers. However, further research has indicated sex/gender-based immune differences, which further increase higher incidences of various autoimmune diseases (AIDs), such as systemic lupus erythematosus (SLE), myasthenia gravis, and rheumatoid arthritis (RA) in females.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!