Design and results of an intensive monitoring programme for avian influenza in meat-type turkey flocks during four epidemics in northern Italy

A method to identify the areas at risk for the introduction of avian influenza virus into poultry flocks through direct contact with wild ducks

Wild dabbling ducks are the main reservoir for avian influenza (AI) viruses and pose an ongoing threat to commercial poultry flocks. Combining the (i) size of that population, (ii) their flight distances and (iii) their AI prevalence, the density of AI-infected dabbling ducks (DID) was calculated as a risk factor for the introduction of AI viruses into poultry holdings of Emilia-Romagna region, Northern Italy. Data on 747 poultry holdings and on 39 AI primary outbreaks notified in Emilia-Romagna between 2000 and 2017 were used to validate that risk factor. A multivariable Bayesian logistic regression was performed to assess whether DID could be associated with the occurrence of AI primary outbreaks. DID value, being an outdoor flock, hobby poultry trading, species reared, length of cycle and flock size were used as explanatory variables. Being an outdoor poultry flock was significantly associated with a higher risk of AI outbreak occurrence. The probability of DID to be a risk factor for AI virus introduction was estimated to be 90%. A DID cut-off of 0.23 was identified to define high-risk areas for AI virus introduction. Using this value, the high-risk area covers 43% of the region. Seventy-four per cent of the primary AI outbreaks have occurred in that area, containing 39% of the regional poultry holdings. Poultry holdings located in areas with a high DID value should be included in a risk-based surveillance programme aimed at AI early detection.

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

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.

Avian influenza: virology, diagnosis and surveillance

Avian influenza virus (AIV) is the causative agent of a zoonotic disease that affects populations worldwide with often devastating economic and health consequences. Most AIV subtypes cause little or no disease in waterfowl, but outbreaks in poultry can be associated with high mortality. Although transmission of AIV to humans occurs rarely and is strain dependent, the virus has the ability to mutate or reassort into a form that triggers a life-threatening infection. The constant emergence of new influenza strains makes it particularly challenging to predict the behavior, spread, virulence or potential for human-to-human transmission. Because it is difficult to anticipate which viral strain or what location will initiate the next pandemic, it is difficult to prepare for that event. However, rigorous implementation of biosecurity, vaccination and education programs can minimize the threat of AIV. Global surveillance programs help record and identify newly evolving and potentially pandemic strains harbored by the reservoir host.

Evaluating surveillance strategies for the early detection of low pathogenicity avian influenza infections

In recent years, the early detection of low pathogenicity avian influenza (LPAI) viruses in poultry has become increasingly important, given their potential to mutate into highly pathogenic viruses. However, evaluations of LPAI surveillance have mainly focused on prevalence and not on the ability to act as an early warning system. We used a simulation model based on data from Italian LPAI epidemics in turkeys to evaluate different surveillance strategies in terms of their performance as early warning systems. The strategies differed in terms of sample size, sampling frequency, diagnostic tests, and whether or not active surveillance (i.e., routine laboratory testing of farms) was performed, and were also tested under different epidemiological scenarios. We compared surveillance strategies by simulating within-farm outbreaks. The output measures were the proportion of infected farms that are detected and the farm reproduction number (R_h). The first one provides an indication of the sensitivity of the surveillance system to detect within-farm infections, whereas R_h reflects the effectiveness of outbreak detection (i.e., if detection occurs soon enough to bring an epidemic under control). Increasing the sampling frequency was the most effective means of improving the timeliness of detection (i.e., it occurs earlier), whereas increasing the sample size increased the likelihood of detection. Surveillance was only effective in preventing an epidemic if actions were taken within two days of sampling. The strategies were not affected by the quality of the diagnostic test, although performing both serological and virological assays increased the sensitivity of active surveillance. Early detection of LPAI outbreaks in turkeys can be achieved by increasing the sampling frequency for active surveillance, though very frequent sampling may not be sustainable in the long term. We suggest that, when no LPAI virus is circulating yet and there is a low risk of virus introduction, a less frequent sampling approach might be admitted, provided that the surveillance is intensified as soon as the first outbreak is detected.

Transmission dynamics of low pathogenicity avian influenza infections in Turkey flocks

Low pathogenicity avian influenza (LPAI) viruses of H5 and H7 subtypes have the potential to mutate into highly pathogenic strains (HPAI), which can threaten human health and cause huge economic losses. The current knowledge on the mechanisms of mutation from LPAI to HPAI is insufficient for predicting which H5 or H7 strains will mutate into an HPAI strain, and since the molecular changes necessary for the change in virulence seemingly occur at random, the probability of mutation depends on the number of virus replicates, which is associated with the number of birds that acquire infection. We estimated the transmission dynamics of LPAI viruses in turkeys using serosurveillance data from past epidemics in Italy. We fitted the proportions of birds infected in 36 flocks into a hierarchical model to estimate the basic reproduction number (R₀) and possible variations in R₀ among flocks caused by differences among farms. We also estimated the distributions of the latent and infectious periods, using experimental infection data with outbreak strains. These were then combined with the R₀ to simulate LPAI outbreaks and characterise the resulting dynamics. The estimated mean within-flock R₀ in the population of infected flocks was 5.5, indicating that an infectious bird would infect an average of more than five susceptible birds. The results also indicate that the presence of seropositive birds does not necessarily mean that the virus has already been cleared and the flock is no longer infective, so that seropositive flocks may still constitute a risk of infection for other flocks. In light of these results, the enforcement of appropriate restrictions, the culling of seropositive flocks, or pre-emptive slaughtering may be useful. The model and parameter estimates presented in this paper provide the first complete picture of LPAI dynamics in turkey flocks and could be used for designing a suitable surveillance program.