Risk based surveillance for early detection of low pathogenic avian influenza outbreaks in layer chickens

Abstract

Current knowledge does not allow the prediction of when low pathogenic avian influenza virus (LPAIV) of the H5 and H7 subtypes infecting poultry will mutate to their highly pathogenic phenotype (HPAIV). This mutation may already take place in the first infected flock; hence early detection of LPAIV outbreaks will reduce the likelihood of pathogenicity mutations and large epidemics. The objective of this study was the development of a model for the design and evaluation of serological-surveillance programmes, with a particular focus on early detection of LPAIV infections in layer chicken flocks. Early detection is defined as the detection of an infected flock before it infects on average more than one other flock (between-flock reproduction ratio Rf<1), hence a LPAI introduction will be detected when only one or a few other flocks are infected. We used a mathematical model that investigates the required sample size and sampling frequency for early detection by taking into account the LPAIV within- and between-flock infection dynamics as well as the diagnostic performance of the serological test used. Since layer flocks are the target of the surveillance, we also explored whether the use of eggs, is a good alternative to sera, as sample commodity. The model was used to refine the current Dutch serological-surveillance programme. LPAIV transmission-risk maps were constructed and used to target a risk-based surveillance strategy. In conclusion, we present a model that can be used to explore different sampling strategies, which combined with a cost-benefit analysis would enhance surveillance programmes for low pathogenic avian influenza.

Data analysis and predictive modelling of HPAI H5 and H7 outbreaks in the EU 2005‐2015

“…While the infectiousness of HPAI is generally much higher that LPAI, at flock level the differences are limited, due to the fast detection and follow-up by culling for HPAI. This strongly contrasts to LPAI, which is rarely detected (Gonzales et al, 2014) and therefore rarely leads to control measures. The kernel found for LPAI effectively leads to a similar critical density as HPAI.…”

“…The kernels from these two publications were used as baseline, to compare with the new data. For LPAI we use the kernel of Gonzales et al (2014) …”

“…Therefore, the spatial transmission for LPAI is quite different from the HPAI transmission, and bears more similarity to the HPAI transmission without a transportation ban (transmission in the high risk period). We use the kernel derived by Gonzales et al (2014) to evaluate transmission of LPAI in Europe. This is to our knowledge the only published kernel for LPAI, but it has several drawbacks.…”

“…Because the number of birds is more or less stable over the years, the nationwide transmission risk would be constant too. However, the relation between risk and flock-size is nor linear, nor constant, but a dependency somewhere in between these two extremes (See Chister et al, 2009 andBoender et al, 2014). To solve the scaling problems for the simulation, these simulations are performed for the situation in the Netherlands in 2003.…”

Systematic review of surveillance systems and methods for early detection of exotic, new and re-emerging diseases in animal populations

“…Simulation models (n = 10) [30,41,97,107,[119][120][121][122][123][124] aimed to mimic disease transmission in a population in time, and sometimes in space, terms in specific circumstances. The outputs from the simulations could be used for estimating the risk of disease spread (n = 5).…”