Inferring within-flock transmission dynamics of highly pathogenic avian influenza H5N8 virus in France, 2020

Are all avian influenza outbreaks in poultry the same? The predicted impact of poultry species and virus subtype

AIMS

Outbreaks of avian influenza in poultry farms are currently increasing in frequency, with devastating consequences for animal welfare, farmers and supply chains. Some studies have documented the direct spread of the avian influenza virus between farms. Prevention of spread between farms relies on biosecurity surveillance and control measures. However, the evolution of an outbreak on a farm might vary depending on the virus strain and poultry species involved; this would have important implications for surveillance systems, epidemiological investigations and control measures.

METHODS AND RESULTS

In this study, we utilized existing parameter estimates from the literature to evaluate the predicted course of an epidemic in a standard poultry flock with 10,000 birds. We used a stochastic SEIR simulation model to simulate outbreaks in different species and with different virus subtypes. The simulations predicted large differences in the duration and severity of outbreaks, depending on the virus subtypes. For both turkeys and chickens, outbreaks with HPAI were of shorter duration than outbreaks with LPAI. In outbreaks involving the infection of chickens with different virus subtypes, the shortest epidemic involved H7N7 and HPAIV H5N1 (median duration of 9 and 17 days, respectively) and the longest involved H5N2 (median duration of 68 days). The most severe outbreaks (number of chickens infected) were predicted for H5N1, H7N1 and H7N3 virus subtypes, and the least severe for H5N2 and H7N7, in which outbreaks for the latter subtype were predicted to develop most slowly.

CONCLUSIONS

These simulation results suggest that surveillance of certain subtypes of avian influenza virus, in chicken flocks in particular, needs to be sensitive and timely if infection is to be detected with sufficient time to implement control measures. The variability in the predictions highlights that avian influenza outbreaks are different in severity, speed and duration, so surveillance and disease response need to be nuanced and fit the specific context of poultry species and virus subtypes.

A real-time colourimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay for the rapid detection of highly pathogenic H5 clade 2.3.4.4b avian influenza viruses

Highly pathogenic avian influenza viruses (HPAIV) are a major threat to the global poultry industry and public health due to their zoonotic potential. Since 2016, Europe and France have faced major epizootics caused by clade 2.3.4.4b H5 HPAIV. To reduce sample-to-result times, point-of-care testing is urgently needed to help prevent further outbreaks and the propagation of the virus. This study presents the design of a novel real-time colourimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay for the detection of clade 2.3.4.4b H5 HPAIV. A clinical validation of this RT-LAMP assay was performed on 198 pools of clinical swabs sampled in 52 poultry flocks during the H5 HPAI 2020-2022 epizootics in France. This RT-LAMP assay allowed the specific detection of HPAIV H5Nx clade 2.3.4.4b within 30 min with a sensitivity of 86.11%. This rapid, easy-to-perform, inexpensive, molecular detection assay could be included in the HPAIV surveillance toolbox.

A systematic review of mechanistic models used to study avian influenza virus transmission and control

The global spread of avian influenza A viruses in domestic birds is causing increasing socioeconomic devastation. Various mechanistic models have been developed to better understand avian influenza transmission and evaluate the effectiveness of control measures in mitigating the socioeconomic losses caused by these viruses. However, the results of models of avian influenza transmission and control have not yet been subject to a comprehensive review. Such a review could help inform policy makers and guide future modeling work. To help fill this gap, we conducted a systematic review of the mechanistic models that have been applied to field outbreaks. Our three objectives were to: (1) describe the type of models and their epidemiological context, (2) list estimates of commonly used parameters of low pathogenicity and highly pathogenic avian influenza transmission, and (3) review the characteristics of avian influenza transmission and the efficacy of control strategies according to the mechanistic models. We reviewed a total of 46 articles. Of these, 26 articles estimated parameters by fitting the model to data, one evaluated the effectiveness of control strategies, and 19 did both. Values of the between-individual reproduction number ranged widely: from 2.18 to 86 for highly pathogenic avian influenza viruses, and from 4.7 to 45.9 for low pathogenicity avian influenza viruses, depending on epidemiological settings, virus subtypes and host species. Other parameters, such as the durations of the latent and infectious periods, were often taken from the literature, limiting the models' potential insights. Concerning control strategies, many models evaluated culling (n = 15), while vaccination received less attention (n = 6). According to the articles reviewed, optimal control strategies varied between virus subtypes and local conditions, and depended on the overall objective of the intervention. For instance, vaccination was optimal when the objective was to limit the overall number of culled flocks. In contrast, pre-emptive culling was preferred for reducing the size and duration of an epidemic. Early implementation consistently improved the overall efficacy of interventions, highlighting the need for effective surveillance and epidemic preparedness.

A review of estimated transmission parameters for the spread of avian influenza viruses

Avian influenza poses an increasing problem in Europe and around the world. Simulation models are a useful tool to predict the spatiotemporal risk of avian influenza spread and evaluate appropriate control actions. To develop realistic simulation models, valid transmission parameters are critical. Here, we reviewed published estimates of the basic reproduction number (R₀ ), the latent period and the infectious period by virus type, pathogenicity, species, study type and poultry flock unit. We found a large variation in the parameter estimates, with highest R₀ estimates for H5N1 and H7N3 compared with other types; for low pathogenic avian influenza compared with high pathogenic avian influenza types; for ducks compared with other species; for estimates from field studies compared with experimental studies; and for within-flock estimates compared with between-flock estimates. Simulation models should reflect this observed variation so as to produce more reliable outputs and support decision-making. How to incorporate this information into simulation models remains a challenge.

Estimation of introduction time window of highly pathogenic avian influenza virus into broiler chicken farms during the 2020 - 2021 winter season outbreak in Japan

When an infectious disease occurs in an area, early detection of infected farms is important to respond quickly and contain the outbreak on a small scale. Estimating the time window for the introduction of the infection is important for its prevention and control. The aim of this study was to estimate the farm-specific time window from the introduction of the highly pathogenic avian influenza (HPAI) virus into poultry farms using field data from the HPAI H5N8 outbreak in the 2020-2021 winter season in Japan. Daily mortality data from 12 broiler chicken farms during the outbreak were used for the analysis. A mathematical model (Susceptible-Exposed-Infectious-Removed, SEIR model) was applied to generate the within-flock transmission of HPAI. The model-predicted mortality was fitted to the observed excess mortality data induced by HPAI to estimate the farm-specific transmission rate and the time of virus introduction. The estimated value of the transmission rate in each farm was 1.449 day^-1 in median (min: 0.661 day^-1, max: 3.387 day^-1). The time window from the introduction of the virus to notification in each farm was estimated at 14.0 days in median (min: 8.6 days, max: 24.1 days) in the deterministic model. In addition, in the stochastic model considering the randomness of transmission in the early phase of the outbreak, the upper value of 95 % credible interval of the time window ranged from 12 to 34 days, with a median of 21 days. The results suggest that although one to three weeks had elapsed on most farms until notification after the virus introduction, the time window could exceed three weeks considering the stochasticity of disease transmission. As for the potential farm characteristics affecting within-flock transmission, the transmission rate was smaller (p-value=0.02) and the estimated time window from introduction to notification was longer (p-value=0.02) when birds were older. This study provides reliable information for setting up a tracing period for a potential source farm and enhancing the efforts for early detection.

Phylodynamic analysis of the highly pathogenic avian influenza H5N8 epidemic in France, 2016-2017

In 2016-2017, France experienced a devastating epidemic of highly pathogenic avian influenza (HPAI) H5N8, with more than 400 outbreaks reported in poultry farms. We analyzed the spatiotemporal dynamics of the epidemic using a structured-coalescent-based phylodynamic approach that combined viral genomic data (n = 196; one viral genome per farm) and epidemiological data. In the process, we estimated viral migration rates between départements (French administrative regions) and the temporal dynamics of the effective viral population size (Ne) in each département. Viral migration rates quantify viral spread between départements and Ne is a population genetic measure of the epidemic size and, in turn, is indicative of the within-département transmission intensity. We extended the phylodynamic analysis with a generalized linear model to assess the impact of multiple factors-including large-scale preventive culling and live-duck movement bans-on viral migration rates and Ne. We showed that the large-scale culling of ducks that was initiated on 4 January 2017 significantly reduced the viral spread between départements. No relationship was found between the viral spread and duck movements between départements. The within-département transmission intensity was found to be weakly associated with the intensity of duck movements within départements. Together, these results indicated that the virus spread in short distances, either between adjacent départements or within départements. Results also suggested that the restrictions on duck transport within départements might not have stopped the viral spread completely. Overall, we demonstrated the usefulness of phylodynamics in characterizing the dynamics of a HPAI epidemic and assessing control measures. This method can be adapted to investigate other epidemics of fast-evolving livestock pathogens.

Highly Pathogenic Avian Influenza A(H5N8) Clade 2.3.4.4b Virus in Dust Samples from Poultry Farms, France, 2021

Avian influenza A(H5N8) virus has caused major epizootics in Europe since 2016. We conducted virologic analysis of aerosol and dust collected on poultry farms in France during 2020–2021. Our results suggest dust contributes to viral dispersal, even early in an outbreak, and could be a valuable surveillance tool.

Avian influenza overview February - May 2021

The 2020-2021 epidemic with a total of 3,555 reported HPAI detections and around 22,400,000 affected poultry birds in 28 European Countries appears to be one of the largest and most devastating HPAI epidemics ever occurred in Europe. Between 24 February and 14 May 2021, 1,672 highly pathogenic avian influenza (HPAI) virus detections were reported in 24 EU/EEA countries and the UK in poultry (n=580), and in wild (n=1,051) and captive birds (n=41). The majority of the detections in poultry were reported by Poland that accounted for 297 outbreaks occurring in a densely populated poultry area over a short period of time, followed by Germany with 168 outbreaks. Germany accounted for 603 detections in wild birds, followed by Denmark and Poland with 167 and 56 detections, respectively. A second peak of HPAI-associated wild bird mortality was observed from February to April 2021 in north-west Europe. The observed longer persistence of HPAI in wild birds compared to previous years may result in a continuation of the risk for juveniles of wild birds and mammals, as well as for virus entry into poultry farms. Therefore, enhanced awareness among farmers to continue applying stringent biosecurity measures and to monitor and report increases in daily mortality and drops in production parameters, are recommended. Sixteen different genotypes were identified to date in Europe and Russia, suggesting a high propensity of these viruses to reassort. The viruses characterized to date retain a preference for avian-type receptors; however, transmission events to mammals and the identification of sporadic mutations of mammal adaptation, indicate ongoing evolution processes and possible increased ability of viruses within this clade to further adapt and transmit to mammals including humans. Since the last report, two human infections due to A(H5N6) HPAI were reported from China and Laos and 10 human cases due to A(H9N2) low pathogenic avian influenza (LPAI) virus identified in China and Cambodia. The risk of infection for the general population in the EU/EEA is assessed as very low and for occupationally exposed people low. People exposed during avian influenza outbreaks should adhere to protection measures, strictly wear personal protective equipment and get tested immediately when developing respiratory symptoms or conjunctivitis within 10 days after exposure.

Unravelling direct and indirect contact patterns between duck farms in France and their association with the 2016-2017 epidemic of Highly Pathogenic Avian Influenza (H5N8)

Live animal movements generate direct contacts (via the exchange of live animals) and indirect contacts (via the transit of transport vehicles) between farms, which can contribute to the spread of pathogens. However, most analyses focus solely on direct contacts and can therefore underestimate the contribution of live animal movements in the spread of infectious diseases. Here, we used French live duck movement data (2016-2018) from one of the largest transport companies to compare direct and indirect contact patterns between duck farms and evaluate how these patterns were associated with the French 2016-2017 epidemic of highly pathogenic avian influenza H5N8. A total number of 614 farms were included in the study, and two directed networks were generated: the animal introduction network (exchange of live ducks) and the transit network (transit of transport vehicles). Following descriptive analyses, these two networks were scrutinized in relation to farm infection status during the epidemic. Results showed that farms were substantially more connected in the transit network than in the animal introduction network and that the transit of transport vehicles generated more opportunities for transmission than the exchange of live animals. We also showed that animal introduction and transit networks' statistics decreased substantially during the epidemic (January-March 2017) compared to non-epidemic periods (January-March 2016 and January-March 2018). We estimated a probability of 33.3 % that a farm exposed to the infection through either of the two live duck movement networks (i.e. that was in direct or indirect contact with a farm that was reported as infected in the following seven days) becomes infected within seven days after the contact. However, we also demonstrated that the level of exposure of farms by these two contact patterns was low, leading only to a handful of transmission events through these routes. As a consequence, we showed that live animal movement patterns are efficient transmission routes for HPAI but have been efficiently reduced to limit the spread during the French 2020-2021 epidemic. These results underpin the relevance of studying indirect contacts resulting from the movement of animals to understand their transmission potential and the importance of accounting for both routes when designing disease control strategies.