Key strategies for reducing spread of avian influenza among commercial poultry holdings: lessons for transmission to humans

Abstract

Recent avian flu epidemics (A/H5N1) in Southeast Asia and case reports from around the world have led to fears of a human pandemic. Control of these outbreaks in birds would probably lead to reduced transmission of the avian virus to humans. This study presents a mathematical model based on stochastic farm-to-farm transmission that incorporates flock size and spatial contacts to evaluate the impact of control strategies. Fit to data from the recent epidemic in the Netherlands, we evaluate the efficacy of control strategies and forecast avian influenza dynamics. Our results identify high-risk areas of spread by mapping of the farm level reproductive number. Results suggest that an immediate depopulation of infected flocks following an accurate and quick diagnosis would have a greater impact than simply depopulating surrounding flocks. Understanding the relative importance of different control measures is essential for response planning.

Figure 1

Avian influenza transmission dynamics between domestic flocks. Infected premises (IPs): a farm is first susceptible (S) and may become infected by infectious farms. Once infected, a farm becomes latent (L) during δ days then infectious but not reported (NR) during γ days, becomes infectious and reported to authorities (R) before being depopulated (D) within τ days. ring-culled premises (RCPs) and dangerous contacts (DCs): farms (susceptible or infected with no specific clinical signs) that are in the vicinity or linked to an IP just revealed infected (R) would be depopulated within τ days also. The number of RCPs depends on the radius rpolicy of neighbourhood control measures and the number of depopulated DCs depends on the ratio of pre-emptive culled farm to infected IPs.

Figure 2

(a) Distribution of the farm size within Ede Municipality (Netherlands). (b) Demographic inputs: simulated locations of poultry farms in Gelderland and Utrecht. Observed affected municipalities are represented by dotted surface.

Figure 3

Reproducing the 2003 Dutch epidemic (a) Daily cases incidence. The dashed line represents the 5-day moving average incidence of reported cases; the black line represents the mean over the 1000 simulations (light grey lines). (b) Map of simulated cases aggregated at the regional level. Figures within municipalities correspond to the count of cases during the observed epidemic.

Figure 4

High-risk area of virus spreading based on R_t values at two time periods: (a) pre-control period: before the virus is known circulating (b) control period: disease is confirmed and first measures are put to place.

Figure 5

Multivariate sensitivity analysis for strategy control parameters (a) impact of each of the five parameters (delay between onset of infectious period and detection within a flock: γ; delay between detection and depopulation: τ; ratio of preventive depopulated farms to reported infected farms: ρ; pre-control period, i.e. lag time between virus importation and the day the disease is confirmed in a country: T₁; radius within which ring depopulation is carried out: rpolicy radius) on cumulative simulated cases. The blue lines represent non-parametric local polynomial regression fitting. (b) Impact of uncertainty of estimated spatial contact rates on the range of cumulative simulated cases.