A Bayesian approach to quantifying the effects of mass poultry vaccination upon the spatial and temporal dynamics of H5N1 in Northern Vietnam.
Outbreaks of H5N1 in poultry in Vietnam continue to threaten the livelihoods of those reliant on poultry production whilst simultaneously posing a severe public health risk given the high mortality associated with human infection. Authorities have invested significant resources in order to control these outbreaks. Of particular interest is the decision, following a second wave of outbreaks, to move from a "stamping out" approach to the implementation of a nationwide mass vaccination campaign. Outbreaks which occurred around this shift in policy provide a unique opportunity to evaluate the relative effectiveness of these approaches and to help other countries make informed judgements when developing control strategies. Here we use Bayesian Markov Chain Monte Carlo (MCMC) data augmentation techniques to derive the first quantitative estimates of the impact of the vaccination campaign on the spread of outbreaks of H5N1 in northern Vietnam. We find a substantial decrease in the transmissibility of infection between communes following vaccination. This was coupled with a significant increase in the time from infection to detection of the outbreak. Using a cladistic approach we estimated that, according to the posterior mean effect of pruning the reconstructed epidemic tree, two thirds of the outbreaks in 2007 could be attributed to this decrease in the rate of reporting. The net impact of these two effects was a less intense but longer-lasting wave and, whilst not sufficient to prevent the sustained spread of outbreaks, an overall reduction in the likelihood of the transmission of infection between communes. These findings highlight the need for more effectively targeted surveillance in order to help ensure that the effective coverage achieved by mass vaccination is converted into a reduction in the likelihood of outbreaks occurring which is sufficient to control the spread of H5N1 in Vietnam.
Walker
Patrick G T
PG
MRC Centre for Outbreak Analysis Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom. patrick.walker@imperial.ac.uk
Cauchemez
Simon
S
Métras
Raphaëlle
R
Dung
Do Huu
do H
Pfeiffer
Dirk
D
Ghani
Azra C
AC
D000818:Animals; D001499:Bayes Theorem; D003198:Computer Simulation; D004196:Disease Outbreaks / Q000517:prevention & control / Q000662:veterinary*; D005843:Geography; D053124:Influenza A Virus, H5N1 Subtype / Q000276:immunology*; D007252:Influenza Vaccines / Q000008:administration & dosage* / Q000276:immunology; D005585:Influenza in Birds / Q000453:epidemiology / Q000276:immunology / Q000517:prevention & control* / Q000635:transmission; D032541:Mass Vaccination / Q000662:veterinary; D011200:Poultry / Q000821:virology; D011201:Poultry Diseases / Q000453:epidemiology / Q000276:immunology / Q000517:prevention & control* / Q000635:transmission; D014744:Vietnam / Q000453:epidemiology
D007252:Influenza Vaccines