SynthesisAmerican journal of infection control2022
The long road of pandemic vaccine development to rollout: A systematic review on the lessons learnt from the 2009 H1N1 influenza pandemic.
Synthesis in American journal of infection control, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 15 citations in OpenAlex.
- The influenza B virus candidate vaccine expressing H3 hemagglutinin developed in suspension MDCK cells confers protection against lethal H3N2 avian influenza in BALB/c mice.Virus research · 2026Article
- A time-delayed epidemic model for control of highly pathogenic avian influenza (HPAI H5Nx) with vaccination, compliance, and non-pharmaceutical interventions.Frontiers in public health · 2026Article
- The Use and Importance ofArtificial Intelligence in Vaccine Research, Development, and Production.Archives of Razi Institute · 2025Review
- Highly Pathogenic Avian Influenza (H5N1) Clade 2.3.4.4b in Cattle: A Rising One Health Concern.Animals : an open access journal from MDPI · 2025Review
- Article
- The role of vaccine status homophily in the COVID-19 pandemic: a cross-sectional survey with modelling.BMC public health · 2024Article
- mRNA and Adenoviral Vector Vaccine Platforms Utilized in COVID-19 Vaccines: Technologies, Ecosystem, and Future Directions.Vaccines · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 2009 Influenza A(H1N1) pandemic prompted one of the largest public health responses in history. The continuous emergence of new and deadly pathogens has highlighted the need to reflect upon past experiences to improve pandemic preparedness. The aim of this study was to examine the development and rollout of 2009 influenza A(H1N1) pandemic vaccine and knowledge challenges for the effective implementation of vaccination programs for COVID-19 and future influenza pandemics.
methodsA systematic review was conducted searching EMBASE (inception to current date) and PUBMED (from January 2009 to current date) databases for relevant published studies about influenza A(H1N1) pandemic vaccines. A Google search was conducted to identify relevant documents from gray literature. Selected Studies were reviewed and summarized.
resultsA total of 22, comprising of 12 original studies and 10 relevant documents met the inclusion criteria. Fourteen papers reported an initial high demand that outweighed production capacity and caused vaccine shortages. Vaccine procurement and supply were skewed toward high-income countries. Low vaccination rates of about 5%-50% were reported in all studies mainly due to a low-risk perception of getting infected, safety concerns, and the fear of adverse effects.
conclusionsSafety concerns about the approved H1N1 vaccines resulted in many unsuccessful vaccination campaigns worldwide. Understanding the factors that influence people's decision to accept or refuse vaccination, effective risk communication strategies, adequate resources for vaccine deployment initiatives and building local capacities through shared knowledge and technology transfer may help to improve COVID-19 vaccine uptake and accelerate pandemic control.
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Registered trials
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.