ArticleMicrobial biotechnology2024
Pandemic preparedness: On the efficacy of non-pharmaceutical interventions in COVID-19 and about approaches to predict future pandemic viruses.
Article in Microbial biotechnology, 2024. 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, 7 citations in OpenAlex.
- Heterologous prime-boost vaccination against H5 avian influenza: Safety and immunogenicity of a MF59-adjuvanted, cell-culture derived H5N6 vaccine.Human vaccines & immunotherapeutics · 2026Trial
- Clinical and public health economic impact of rapid strain-matched vaccination in influenza pandemic mitigation: A UK-like population dynamic transmission model.Human vaccines & immunotherapeutics · 2026Article
- Risk Evaluation and Mitigation Strategies for Newly Detected Mysterious Dinga Dinga Virus Infection in Africa: A Narrative Review.Health science reports · 2025Article
- Engineering Genome-Free Bacterial Cells for Effective SARS-COV-2 Neutralisation.Microbial biotechnology · 2025Article
- Artificial intelligence-based prediction of pathogen emergence and evolution in the world of synthetic biology.Microbial biotechnology · 2024Review
- Pandemic preparedness: On the efficacy of non-pharmaceutical interventions in COVID-19 and about approaches to predict future pandemic viruses.Microbial biotechnology · 2024Article
- Pandemic preparedness-political perspectives.Sustainable microbiology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With three major viral pandemics over the last 100 years, namely the Spanish flu, AIDS and COVID-19 each claiming many millions of lives, pandemic preparedness has become an important issue for public health. The economic, social and political consequences of the upheaval caused by such pandemics also represent a major challenge for governments with respect to sustainable development goals. The field of pandemic preparedness is vast and the current article can only address selected aspects. The article looks first backwards and addresses the question of the efficacy of non-pharmaceutical interventions (NPI) on the trajectory of the COVID-19 pandemic. The article looks then forward by asking to what extent viral candidates for future pandemics can be predicted by virome analyses from metagenome and transcriptome sequencing, by focusing on the virome from specific animal species and using ecological and epidemiological data about spillover viral infections in veterinary and human medicine. As a comprehensive overview on pandemic preparedness is beyond the capacity of a single reviewer, only selected topics will be discussed using recent key scientific publications. Since COVID-19 has not run its course, a computational program able to predict the future evolution of SARS-CoV-2 is mentioned that could assist proactive mRNA vaccine developments against possible future variants of concern. Ending the COVID-19 epidemic necessitates mucosal vaccines that can suppress the transmission of SARS-CoV-2 and therefore this article closes by discussing a promising and versatile protein nanoparticle experimental vaccine approach for inhalation that does not depend on needles nor a cold chain for distribution.
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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.