Avian influenza viruses in New Zealand wild birds, with an emphasis on subtypes H5 and H7: Their distinctive epidemiology and genomic properties.

The rapid spread of highly pathogenic avian influenza (HPAI) A (H5N1) viruses in Southeast Asia in 2004 prompted the New Zealand Ministry for Primary Industries to expand its avian influenza surveillance in wild birds. A total of 18,693 birds were sampled between 2004 and 2020, including migratory shorebirds (in 2004-2009), other coastal species (in 2009-2010), and resident waterfowl (in 2004-2020). No avian influenza viruses (AIVs) were isolated from cloacal or oropharyngeal samples from migratory shorebirds or resident coastal species. Two samples from red knots (Calidris canutus) tested positive by influenza A RT-qPCR, but virus could not be isolated and no further characterization could be undertaken. In contrast, 6179 samples from 15,740 mallards (Anas platyrhynchos) tested positive by influenza A RT-qPCR. Of these, 344 were positive for H5 and 51 for H7. All H5 and H7 viruses detected were of low pathogenicity confirmed by a lack of multiple basic amino acids at the hemagglutinin (HA) cleavage site. Twenty H5 viruses (six different neuraminidase [NA] subtypes) and 10 H7 viruses (two different NA subtypes) were propagated and characterized genetically. From H5- or H7-negative samples that tested positive by influenza A RT-qPCR, 326 AIVs were isolated, representing 41 HA/NA combinations. The most frequently isolated subtypes were H4N6, H3N8, H3N2, and H10N3. Multivariable logistic regression analysis of the relations between the location and year of sampling, and presence of AIV in individual waterfowl showed that the AIV risk at a given location varied from year to year. The H5 and H7 isolates both formed monophyletic HA groups. The H5 viruses were most closely related to North American lineages, whereas the H7 viruses formed a sister cluster relationship with wild bird viruses of the Eurasian and Australian lineages. Bayesian analysis indicates that the H5 and H7 viruses have circulated in resident mallards in New Zealand for some time. Correspondingly, we found limited evidence of influenza viruses in the major migratory bird populations visiting New Zealand. Findings suggest a low probability of introduction of HPAI viruses via long-distance bird migration and a unique epidemiology of AIV in New Zealand.

Modelling the field personnel resources to control foot-and-mouth disease outbreaks in New Zealand.

The objective of the study was to simulate New Zealand's foot-and-mouth disease (FMD) operational plan to determine personnel requirements for an FMD response and understand how the numbers of front-line staff available could affect the size and duration of FMD outbreaks, when using stamping-out (SO) measures with or without vaccination. The model utilized a national dataset of all known livestock farms. Each simulation randomly seeded infection into a single farm. Transmission mechanisms included direct and indirect contacts, local and airborne spread. Prior to each simulation, the numbers of personnel available for front-line tasks (including contact tracing, surveillance of at-risk farms, depopulation and vaccination) were set randomly. In a random subset of simulations, vaccination was allowed to be deployed as an adjunct to SO. The effects of personnel numbers on the size and duration of epidemics were explored using machine learning methods. In the second stage of the study, using a subset of iterations where numbers of personnel were unconstrained, the number of personnel used each day were quantified. When personnel resources were unconstrained, the 95th percentile and maximum number of infected places (IPs) were 78 and 462, respectively, and the 95th percentile and maximum duration were 69 and 217 days, respectively. However, severe constraints on personnel resources allowed some outbreaks to exceed the size of the UK 2001 FMD epidemic which had 2026 IPs. The number of veterinarians available had a major influence on the size and duration of outbreaks, whereas the availability of other personnel types did not. A shortage of veterinarians was associated with an increase in time to detect and depopulate IPs, allowing for continued transmission. Emergency vaccination placed a short-term demand for additional staff at the start of the vaccination programme, but the overall number of person days used was similar to SO-only strategies. This study determined the optimal numbers of front-line personnel required to implement the current operational plans to support an FMD response in New Zealand. A shortage of veterinarians was identified as the most influential factor to impact disease control outcomes. Emergency vaccination led to earlier control of FMD outbreaks but at the cost of a short-term spike in demand for personnel. In conclusion, a successful response needs to have access to sufficient personnel, particularly veterinarians, trained in response roles and available at short notice.

Using multiple data sources to explore disease transmission risk between commercial poultry, backyard poultry, and wild birds in New Zealand.

The movements of backyard poultry and wild bird populations are known to pose a disease risk to the commercial poultry industry. However, it is often difficult to estimate this risk due to the lack of accurate data on the numbers, locations, and movement patterns of these populations. The main aim of this study was to evaluate the use of three different data sources when investigating disease transmission risk between poultry populations in New Zealand including (1) cross-sectional survey data looking at the movement of goods and services within the commercial poultry industry, (2) backyard poultry sales data from the online auction site TradeMe®, and (3) citizen science data from the wild bird monitoring project eBird. The cross-sectional survey data and backyard poultry sales data were transformed into network graphs showing the connectivity of commercial and backyard poultry producers across different geographical regions. The backyard poultry network was also used to parameterise a Susceptible-Infectious (SI) simulation model to explore the behaviour of potential disease outbreaks. The citizen science data was used to create an additional map showing the spatial distribution of wild bird observations across New Zealand. To explore the potential for diseases to spread between each population, maps were combined into bivariate choropleth maps showing the overlap between movements within the commercial poultry industry, backyard poultry trades and, wild bird observations. Network analysis revealed that the commercial poultry network was highly connected with geographical clustering around the urban centres of Auckland, New Plymouth and Christchurch. The backyard poultry network was also a highly active trade network and displayed similar geographic clustering to the commercial network. In the disease simulation models, the high connectivity resulted in all suburbs becoming infected in 96.4 % of the SI simulations. Analysis of the eBird data included reports of over 80 species; the majority of which were identified as coastal seabirds or wading birds that showed little overlap with either backyard or commercial poultry. Overall, our study findings highlight how the spatial patterns of trading activity within the commercial poultry industry, alongside the movement of backyard poultry and wild birds, have the potential to contribute significantly to the spread of diseases between these populations. However, it is clear that in order to fully understand this risk landscape, further data integration is needed; including the use of additional datasets that have further information on critical variables such as environmental factors.

Informing adaptive management strategies: Evaluating a mechanism to predict the likely qualitative size of foot-and-mouth disease outbreaks in New Zealand using data available in the early response phase of simulated outbreaks.

The objective of the study was to define and then evaluate an early decision indicator (EDI) trigger that operated within the first 5 weeks of a response that would indicate a large and/or long outbreak of FMD was developing, to be able to inform control options within an adaptive management framework. To define the EDI trigger, a previous dataset of 10,000 simulated FMD outbreaks in New Zealand, controlled by the standard stamping-out approach, was re-analysed at various time points between Days 11 and 35 of each response to find threshold values of cumulative detected infected premises (IPs) that indicated upper quartile sized outbreaks and estimated dissemination rate (EDR) values that indicated sustained spread. Both sets of thresholds were then parameterized within the InterSpread Plus modelling framework, such that if either the cumulative IPs or the EDR exceeded the defined thresholds, the EDI trigger would fire. A new series of simulations were then generated. The EDI trigger was like two diagnostic tests interpreted in parallel, with the diagnostic outcome positive if either test was positive at any time point between Days 11 and 35 inclusive. The diagnostic result was then compared to the final size of each outbreak, to see if the outbreak was an upper quartile outbreak in terms of cumulative IPs and/or final duration. The performance of the EDI trigger was then evaluated across the population of outbreaks, and the sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) were calculated. The Se, Sp, PPV and NPV for predicting large outbreaks were 0.997, 0.513, 0.404 and 0.998, respectively. The study showed that the EDI trigger was very sensitive to detecting large outbreaks, although not all outbreaks predicted to be large were so, whereas outbreaks predicted to be small invariably were small. Therefore, it shows promise as a mechanism that could support an adaptive management approach to FMD control.

Early Decision Indicators for Foot-and-Mouth Disease Outbreaks in Non-Endemic Countries.

Disease managers face many challenges when deciding on the most effective control strategy to manage an outbreak of foot-and-mouth disease (FMD). Decisions have to be made under conditions of uncertainty and where the situation is continually evolving. In addition, resources for control are often limited. A modeling study was carried out to identify characteristics measurable during the early phase of a FMD outbreak that might be useful as predictors of the total number of infected places, outbreak duration, and the total area under control (AUC). The study involved two modeling platforms in two countries (Australia and New Zealand) and encompassed a large number of incursion scenarios. Linear regression, classification and regression tree, and boosted regression tree analyses were used to quantify the predictive value of a set of parameters on three outcome variables of interest: the total number of infected places, outbreak duration, and the total AUC. The number of infected premises (IPs), number of pending culls, AUC, estimated dissemination ratio, and cattle density around the index herd at days 7, 14, and 21 following first detection were associated with each of the outcome variables. Regression models for the size of the AUC had the highest predictive value (R2 = 0.51-0.9) followed by the number of IPs (R2 = 0.3-0.75) and outbreak duration (R2 = 0.28-0.57). Predictability improved at later time points in the outbreak. Predictive regression models using various cut-points at day 14 to define small and large outbreaks had positive predictive values of 0.85-0.98 and negative predictive values of 0.52-0.91, with 79-97% of outbreaks correctly classified. On the strict assumption that each of the simulation models used in this study provide a realistic indication of the spread of FMD in animal populations. Our conclusion is that relatively simple metrics available early in a control program can be used to indicate the likely magnitude of an FMD outbreak under Australian and New Zealand conditions.

Factors Associated with Highly Pathogenic Avian Influenza H5N2 Infection on Table-Egg Layer Farms in the Midwestern United States, 2015.

A case-control study was conducted among commercial table-egg layer and pullet operations in Iowa and Nebraska, United States, to investigate potential risk factors for infection with highly pathogenic avian influenza (HPAI) H5N2. A questionnaire was developed and administered to 28 case farms and 31 control farms. Data were collected at the farm and barn levels, enabling two separate analyses to be performed-the first a farm-level comparison of case farms vs. control farms, and the second a barn-level comparison between case barns on case farms and control barns on control farms. Multivariable logistic regression models were fit using a forward-selection procedure. Key risk factors identified were farm location in an existing control zone, rendering and garbage trucks coming near barns, dead-bird disposal located near barns, and visits by a company service person. Variables associated with a decreased risk of infection included visitors changing clothing, cleaning and disinfecting a hard-surface barn entryway, and ceiling/eaves ventilation in barns.

Helicobacter bilis and Helicobacter trogontum: infectious causes of abortion in sheep.

The aim of our study was to determine the association of Helicobacter spp. that had flexispira morphology with ovine abortion, and to understand the importance of these organisms as a cause of ovine abortion in New Zealand. A retrospective diagnostic survey was carried out on laboratory submissions from ovine abortion outbreaks. A comparison was made of the proportion of laboratory submissions where Helicobacter spp. were detected from flocks that had no other agent identified (group A) with a group that had a known cause of abortion identified (group B). This latter group was considered to be a negative control, given the premise that Helicobacter spp. were not causing abortions and that Helicobacter spp. should be present at a lower rate in the group. Where no diagnosis had been made, aborted material was positive for Helicobacter spp. with flexispira morphology in 8 submissions (20%, 8/40) from 5 of the 31 survey farms (16%, 5/31). Helicobacter spp. were not detected in any of the 18 submissions from the 17 control farms (group B). Helicobacter spp. were confirmed by 16S ribosomal RNA sequencing of 3 of the Helicobacter spp. isolated by culture from the livers of aborted sheep fetuses, and 7 of the 8 where samples were positive in a Helicobacter PCR assay. The Helicobacter spp. were identified as Helicobacter trogontum (Flexispira taxon 5 genotype) and Helicobacter bilis (Flexispira taxon 8 genotype). The findings support Helicobacter spp. being a probable causative agent of ovine abortions in New Zealand.