Abstract
Background
The ongoing H5N1 panzootic in mammals has amplified zoonotic pathways to facilitate human infection. Characterising key epidemiological parameters for H5N1 is critical should it 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 and the 2003 Netherlands H7N7 outbreak.
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 PubMed and Google Scholar for studies of any design providing relevant estimates. We estimated the basic reproduction number for the recent outbreak in the United States (US) and the 2003 Netherlands H7N7 outbreak. In addition we estimated the serial interval for H5N1 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 46 articles, we identified H5N1s epidemiological profile as having lower transmissibility (R0 < 0.2) but higher severity compared to other human subtypes. Evidence suggests H5N1 has a longer incubation (~4 days vs ~2 days) and serial intervals (~6 days vs ~3 days) than human subtypes, impacting transmission dynamics. The epidemiology of the US H5 outbreak is similar to the 2003 Netherlands H7N7 outbreak. Key gaps remain regarding latent and infectious periods.
Conclusions
We characterised critical epidemiological parameters for H5N1 infection. The current US 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.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
This work was supported by the ESCAPE project (101095619), co-funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Health and Digital Executive Agency (HADEA). Neither the European Union nor the granting authority can be held responsible for them. This work was co-funded by UK Research and Innovation (UKRI) under the UK governments Horizon Europe funding guarantee [grant number 10051037]. Epiverse is supported by data.org
Source: MedRxIV, https://www.medrxiv.org/content/10.1101/2024.12.11.24318702v4
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