A Bayesian approach to quantifying the effects of mass poultry vaccination upon the spatial and temporal dynamics of H5N1 in Northern Vietnam

Abstract

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.

Figure 1. Spatial and temporal distribution of outbreaks of H5N1 in poultry in northern Vietnam Dec 2004–Feb 2008.

a, Commune-level spatial distribution of reported outbreaks, b, Weekly incidence of outbreak reports in northern Vietnam. (As sufficiently accurate data on the timing and location of outbreaks during the first wave is not available, figure shows data from the second wave onwards).

Figure 2. Between-commune infectivity.

a, Risk map of the expected daily number of secondary infections arising from infected commune during each of the three waves, under the assumption all other communes remain susceptible. b, Plot of how the daily probability of between-commune transmission scales with distance, c, Histogram of commune-specific daily rate of infection (only those over 0.5 plotted), d, Relative changes in per-capita infectivity parameter between waves with associated 95% credible intervals (see Text S1).

Figure 3. The infectious period and local reproductive numbers.

a, Spatial distribution of local reproductive numbers calculated analytically using the infectivity and infectious period estimates, b, Estimate of probability (assumed gamma) distribution of the infectious period during each of the three waves, c, Histogram of local reproductive numbers for the three waves (only those with values greater than 0.8 plotted).

Figure 4. Reconstructing the epidemic tree.

a, Temporal pattern of average reproductive numbers throughout the three waves, b, Proportion of transmissions occurring at different distances for each of the three waves, c, Impact upon the 2007 wave of truncating the infectious period after a set amount of time if an outbreak remains unreported, reflecting the time at which infection would be detected using more pro-active surveillance. Columns show the estimated number of outbreaks which would have been averted as a result, the reduction in the time taken to control the wave and the probability the wave would have been eliminated within the first ten outbreaks.

Figure 5. Simulation study results.

Parameters used during simulation of outbreaks waves (black line), estimates from the posterior mean of the model parameters estimated from fitting the model to each simulated wave (dashed grey lines) and the overall mean of each of these estimates (dashed red line) for a, the commune-level infectious period and b, infectiousness over space as described by the product of β and the spatial kernel.