Jack Ward, etc.,al. [preprint]Estimates of epidemiological parameters for H5N1 influenza in humans: a rapid review. https://doi.org/10.1101/2024.12.11.24318702
Background The ongoing H5N1 panzootic in mammals has amplified zoonotic pathways to facilitate human infection. Characterising key epidemiological parameters for H5N1 is critical should this become widespread.
Aim To identify and estimate critical epidemiological parameters for H5N1 from past and current outbreaks, and to compare their characteristics with human influenza subtypes.
Methods We searched PubMed, Embase, and Cochrane Library for systematic reviews reporting parameter estimates from primary data or meta-analyses. To address gaps, we searched Google Scholar for studies of any design providing relevant estimates. We estimated the basic reproduction number for the outbreak in the US and estimated the serial interval using data from previous household clusters in Indonesia. We also applied a branching process model to simulate transmission chain size and duration to assess if simulated transmission patterns align with observed dynamics.
Results From 32 studies, we identified H5N1’s epidemiological profile as having lower transmissibility (R0 < 0.2) but higher severity compared to human subtypes. Evidence suggests H5N1 has longer incubation (~4 days vs ~2 days) and serial intervals (~6 days vs ~3 days) than human subtypes, impacting transmission dynamics. Key gaps remain regarding latent and infectious periods.
Conclusions We characterised critical epidemiological parameters for H5N1 infection. The current U.S. outbreak shows lower pathogenicity but similar transmissibility compared to prior outbreaks. Longer incubation and serial intervals may enhance contact tracing feasibility. These estimates offer a baseline for monitoring changes in H5N1 epidemiology.
Aim To identify and estimate critical epidemiological parameters for H5N1 from past and current outbreaks, and to compare their characteristics with human influenza subtypes.
Methods We searched PubMed, Embase, and Cochrane Library for systematic reviews reporting parameter estimates from primary data or meta-analyses. To address gaps, we searched Google Scholar for studies of any design providing relevant estimates. We estimated the basic reproduction number for the outbreak in the US and estimated the serial interval using data from previous household clusters in Indonesia. We also applied a branching process model to simulate transmission chain size and duration to assess if simulated transmission patterns align with observed dynamics.
Results From 32 studies, we identified H5N1’s epidemiological profile as having lower transmissibility (R0 < 0.2) but higher severity compared to human subtypes. Evidence suggests H5N1 has longer incubation (~4 days vs ~2 days) and serial intervals (~6 days vs ~3 days) than human subtypes, impacting transmission dynamics. Key gaps remain regarding latent and infectious periods.
Conclusions We characterised critical epidemiological parameters for H5N1 infection. The current U.S. outbreak shows lower pathogenicity but similar transmissibility compared to prior outbreaks. Longer incubation and serial intervals may enhance contact tracing feasibility. These estimates offer a baseline for monitoring changes in H5N1 epidemiology.
See Also:
Latest articles in those days:
- Engineered Bacillus subtilis to deliver dsRNA via extracellular vesicles against the H9N2 avian influenza virus 5 hours ago
- [preprint]Spatiotemporal dynamics and ecological risk factors of highly pathogenic avian influenza A(H5N1) in Canadian wildlife: A One Health surveillance analysis 5 hours ago
- Epidemiological and Virological Characteristics of H9N2 Avian Influenza Virus in Jiangsu Province, China, 2024 17 hours ago
- Innate Pathway Selection Modulates Antibody and T-Cell Responses to Mosaic Influenza Nucleoprotein in Cattle 2 days ago
- Game Over for the Baseline: Influenza Hospitalization Patterns Before, During, and After the COVID-19 Pandemic (FluSurv-NET, 2009–2025) 2 days ago
[Go Top] [Close Window]


