SIMID | Simulation Models of Infectious Disease

Tracking the emerging dynamics and risks of H5N1 flu | NEW PREPRINT

Tracking the emerging dynamics and risks of H5N1 flu | NEW PREPRINT

The ongoing spread of Highly Pathogenic Avian Influenza A (H5N1) among dairy cattle in the US and the subsequent growing number of human cases makes it crucial to understand how this virus spreads and behaves. Our latest research, posted on the preprint server medRxiv, focuses on identifying key epidemiological parameters of H5N1, comparing them to those of human influenza, and assessing their implications for public health.

In a collaboration with our collaborators from the UK and Germany, we analyzed data gathered from systematic reviews and primary research on past and current outbreaks. We also used modeling approaches to fill critical knowledge gaps, such as the basic reproduction number (R₀) and transmission patterns.

The primary findings are:

  • H5N1 has lower transmissibility (R₀ < 0.2) compared to human influenza subtypes.
  • The incubation period (~4 days) and serial interval (~6 days) for H5N1 are longer than those for human influenza (~2 days and ~3 days, respectively).
  • While previous outbreaks of H5N1 have shown a high Case Fatality Ratio (CFR), there have been no fatalities reported for the current outbreak.
  • Modeling of H5N1 transmission dynamics suggest that there is limited potential for large outbreaks under current conditions.
  • Key data on latency and infectious period is still missing and need further research.

Our findings have some clear public health relevance especially if the outbreak were to expand. H5N1’s longer incubation and serial intervals may provide more opportunities for effective contact tracing and containment during outbreaks. While H5N1 is less transmissible than human influenza, the potential for reassortment with human influenza viruses could result in a variant capable of sustained human transmission. Public health authorities must continue monitoring H5N1’s evolution to assess if the risk is increasing.

Read our paper here

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