ArticlePloS one2009
Adaptive vaccination strategies to mitigate pandemic influenza: Mexico as a case study.
Article in PloS one, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Article
- Evaluating targeted COVID-19 vaccination strategies with agent-based modeling.PLoS computational biology · 2024Article
- Evaluating targeted COVID-19 vaccination strategies with agent-based modeling.medRxiv : the preprint server for health sciences · 2023Article
- Comparative performance of between-population vaccine allocation strategies with applications for emerging pandemics.Vaccine · 2023Article
- Where to locate COVID-19 mass vaccination facilities?Naval research logistics · 2022Article
- Fogarty International Center collaborative networks in infectious disease modeling: Lessons learnt in research and capacity building.Epidemics · 2019Review
- Controlling infectious disease outbreaks: A deterministic allocation-scheduling model with multiple discrete resources.Journal of systems science and systems engineering · 2017Article
- Perspectives on the role of mobility, behavior, and time scales in the spread of diseases.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Pandemic Risk Assessment Model (PRAM): a mathematical modeling approach to pandemic influenza planning.Epidemiology and infection · 2016Article
- Pattern transitions in spatial epidemics: Mechanisms and emergent properties.Physics of life reviews · 2016Review
- Measured voluntary avoidance behaviour during the 2009 A/H1N1 epidemic.Proceedings. Biological sciences · 2015Article
- The social benefits of private infectious disease-risk mitigation.Theoretical ecology · 2015Article
- Whole Tumor Antigen Vaccines: Where Are We?Vaccines · 2015Review
- Mathematical and computational approaches to epidemic modeling: a comprehensive review.Frontiers of computer science · 2015Review
- Disease risk mitigation: the equivalence of two selective mixing strategies on aggregate contact patterns and resulting epidemic spread.Journal of theoretical biology · 2014Article
- Merging economics and epidemiology to improve the prediction and management of infectious disease.EcoHealth · 2014Article
- Assessment of the intensive countermeasures in the 2009 pandemic influenza in Korea.Osong public health and research perspectives · 2014Article
- Modeling rapidly disseminating infectious disease during mass gatherings.BMC medicine · 2012Review
- Geographic prioritization of distributing pandemic influenza vaccines.Health care management science · 2012Article
- Vaccination against 2009 pandemic H1N1 in a population dynamical model of Vancouver, Canada: timing is everything.BMC public health · 2011Article
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5 authors.
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Abstract
backgroundWe explore vaccination strategies against pandemic influenza in Mexico using an age-structured transmission model calibrated against local epidemiological data from the Spring 2009 A(H1N1) pandemic. METHODS AND
findingsIn the context of limited vaccine supplies, we evaluate age-targeted allocation strategies that either prioritize youngest children and persons over 65 years of age, as for seasonal influenza, or adaptively prioritize age groups based on the age patterns of hospitalization and death monitored in real-time during the early stages of the pandemic. Overall the adaptive vaccination strategy outperformed the seasonal influenza vaccination allocation strategy for a wide range of disease and vaccine coverage parameters.
conclusionsThis modeling approach could inform policies for Mexico and other countries with similar demographic features and vaccine resources issues, with regard to the mitigation of the S-OIV pandemic. We also discuss logistical issues associated with the implementation of adaptive vaccination strategies in the context of past and future influenza pandemics.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.