Model-Based Evaluation of Highly and Low Pathogenic Avian Influenza Dynamics in Wild Birds

There is growing interest in avian influenza (AI) epidemiology to predict disease risk in wild and domestic birds, and prevent transmission to humans. However, understanding the epidemic dynamics of highly pathogenic (HPAI) viruses remains challenging because they have rarely been detected in wild birds. We used modeling to integrate available scientific information from laboratory and field studies, evaluate AI dynamics in individual hosts and waterfowl populations, and identify key areas for future research. We developed a Susceptible-Exposed-Infectious-Recovered (SEIR) model and used published laboratory challenge studies to estimate epidemiological parameters (rate of infection, latency period, recovery and mortality rates), considering the importance of age classes, and virus pathogenicity. Infectious contact leads to infection and virus shedding within 1–2 days, followed by relatively slower period for recovery or mortality. We found a shorter infectious period for HPAI than low pathogenic (LP) AI, which may explain that HPAI has been much harder to detect than LPAI during surveillance programs. Our model predicted a rapid LPAI epidemic curve, with a median duration of infection of 50–60 days and no fatalities. In contrast, HPAI dynamics had lower prevalence and higher mortality, especially in young birds. Based on field data from LPAI studies, our model suggests to increase surveillance for HPAI in post-breeding areas, because the presence of immunologically naïve young birds is predicted to cause higher HPAI prevalence and bird losses during this season. Our results indicate a better understanding of the transmission, infection, and immunity-related processes is required to refine predictions of AI risk and spread, improve surveillance for HPAI in wild birds, and develop disease control strategies to reduce potential transmission to domestic birds and/or humans

Tracking large carnivore dispersal using isotopic clues in claws: An application to cougars across the Great Plains

1. Cougar (Puma concolor) populations, like other large carnivores, have increased during recent decades and may be recolonizing their former ranges in Midwestern North America. The dispersal routes taken by these animals from established populations are unknown and insight into these movements would facilitate their conservation and management. 2. We inferred the origin and migration route of four dispersing cougars using stable hydrogen (δD) and carbon (δ13C) isotope values along one of their claws. We compared isotopic variations within claws to regional and large-scale isoscapes of δD and δ13C values in prey species. Using a likelihood-based assignment approach, we predicted the most likely dispersal route of each cougar (among several least-cost dispersal paths to potential source populations) in a chronological sequence dating back from its final location. 3. Our model predicted the origin of a radio-collared short-distance disperser and inferences about the most likely dispersal corridors for two long-distance dispersers matched reported information from re-sighting events and genetic investigations. 4. Insights about the most likely migration corridors may help identify critical areas and guide future conservation efforts of cougars and other large carnivores. We encourage managers to extend regional isoscapes based on sedentary prey species as they prove to be valuable tools in isotopic tracking of long-distance migration. 5. Our isotopic approach may be extended to other metabolically inert tissues that grow continuously, to investigate dispersal paths of species of interest, providing that individuals disperse across known isotopically structured landscapes

Impact of Imperfect Disease Detection on the Identification of Risk Factors in Veterinary Epidemiology

Risk factors are key epidemiological concepts that are used to explain disease distributions. Identifying disease risk factors is generally done by comparing the characteristics of diseased and non-diseased populations. However, imperfect disease detectability generates disease observations that do not necessarily represent accurately the true disease situation. In this study, we conducted an extensive simulation exercise to emphasize the impact of imperfect disease detection on the outcomes of logistic models when case reports are aggregated at a larger scale (e.g., diseased animals aggregated at farm level). We used a probabilistic framework to simulate both the disease distribution in herds and imperfect detectability of the infected animals in these herds. These simulations show that, under logistic models, true herd-level risk factors are generally correctly identified but their associated odds ratio are heavily underestimated as soon as the sensitivity of the detection is less than one. If the detectability of infected animals is not only imperfect but also heterogeneous between herds, the variables associated with the detection heterogeneity are likely to be incorrectly identified as risk factors. This probability of type I error increases with increasing heterogeneity of the detectability, and with decreasing sensitivity. Finally, the simulations highlighted that, when count data is available (e.g., number of infected animals in herds), they should not be reduced to a presence/absence dataset at the herd level (e.g., presence or not of at least one infected animal) but rather modeled directly using zero-inflated count models which are shown to be much less sensitive to imperfect detectability issues. In light of these simulations, we revisited the analysis of the French bovine abortion surveillance data, which has already been shown to be characterized by imperfect and heterogeneous abortion detectability. As expected, we found substantial differences between the quantitative outputs of the logistic model and those of the zero-inflated Poisson model. We conclude by strongly recommending that efforts should be made to account for, or at the very least discuss, imperfect disease detectability when assessing associations between putative risk factors and observed disease distributions, and advocate the use of zero-inflated count models if count data is available

Presence of Avian Influenza Viruses in Waterfowl and Wetlands during Summer 2010 in California: Are Resident Birds a Potential Reservoir?

Although wild waterfowl are the main reservoir for low pathogenic avian influenza viruses (LPAIv), the environment plays a critical role for the circulation and persistence of AIv. LPAIv may persist for extended periods in cold environments, suggesting that waterfowl breeding areas in the northern hemisphere may be an important reservoir for AIv in contrast to the warmer southern wintering areas. We evaluated whether southern wetlands, with relatively small populations (thousands) of resident waterfowl, maintain AIv in the summer, prior to the arrival of millions of migratory birds. We collected water and fecal samples at ten wetlands in two regions (Yolo Bypass and Sacramento Valley) of the California Central Valley during three bi-weekly intervals beginning in late July, 2010. We detected AIv in 29/367 fecal samples (7.9%) and 12/597 water samples (2.0%) by matrix real time Reverse Transcription Polymerase Chain Reaction (rRT-PCR). We isolated two H3N8, two H2N3, and one H4N8 among rRT-PCR positive fecal samples but no live virus from water samples. Detection of AIv RNA in fecal samples was higher from wetlands in the Sacramento Valley (11.9%) than in the Yolo Bypass (0.0%), but no difference was found for water samples (2.7 vs. 1.7%, respectively). Our study showed that low densities of hosts and unfavorable environmental conditions did not prevent LPAIv circulation during summer in California wetlands. Our findings justify further investigations to understand AIv dynamics in resident waterfowl populations, compare AIv subtypes between migratory and resident waterfowl, and assess the importance of local AIv as a source of infection for migratory birds

Evaluation of the cost-effectiveness of bovine brucellosis surveillance in a disease-free country using stochastic scenario tree modelling.

Surveillance systems of exotic infectious diseases aim to ensure transparency about the country-specific animal disease situation (i.e. demonstrate disease freedom) and to identify any introductions. In a context of decreasing resources, evaluation of surveillance efficiency is essential to help stakeholders make relevant decisions about prioritization of measures and funding allocation. This study evaluated the efficiency (sensitivity related to cost) of the French bovine brucellosis surveillance system using stochastic scenario tree models. Cattle herds were categorized into three risk groups based on the annual number of purchases, given that trading is considered as the main route of brucellosis introduction in cattle herds. The sensitivity in detecting the disease and the costs of the current surveillance system, which includes clinical (abortion) surveillance, programmed serological testing and introduction controls, were compared to those of 19 alternative surveillance scenarios. Surveillance costs included veterinary fees and laboratory analyses. The sensitivity over a year of the current surveillance system was predicted to be 91±7% at a design prevalence of 0.01% for a total cost of 14.9±1.8 million €. Several alternative surveillance scenarios, based on clinical surveillance and random or risk-based serological screening in a sample (20%) of the population, were predicted to be at least as sensitive but for a lower cost. Such changes would reduce whole surveillance costs by 20 to 61% annually, and the costs for farmers only would be decreased from about 12.0 million € presently to 5.3-9.0 million € (i.e. 25-56% decrease). Besides, fostering the evolution of the surveillance system in one of these directions would be in agreement with the European regulations and farmers perceptions on brucellosis risk and surveillance

Scénarios alternatifs pour l'amélioration de l'efficience du système de surveillance de la brucellose bovine en France

International audienceAbstract Alternative scenarios for improving the efficiency of the bovine brucellosis surveillance system in France Surveillance systems for exotic animal diseases aim to identify any introductions and to support the disease-free status. In a context of decreasing resources, evaluating surveillance efficiency – i.e. detection sensitivity versus cost – is essential to help stakeholders make informed decisions about funding allocation. The goal of this study was to evaluate the efficiency of the French bovine brucellosis surveillance system using stochastic scenario tree models. The current surveillance system, which includes mandatory abortion notification, annual serological testing in all herds, and selected controls of purchased cattle, meets the detection objectives of the European regulation. However, an alternative scenario including mandatory notification of series of abortions and serological screening in selected high-risk herds was predicted to be more efficient. Implementing these types of changes, while complying with European specifications for disease-free status, would strongly reduce annual surveillance costs. These savings could be reinvested in additional measures to improve the surveillance system.La surveillance des maladies animales exotiques vise à identifier toute introduction et à maintenir le statut officiellement indemne. Dans un contexte de diminution des ressources, l'évaluation de l'efficience – c'est-à-dire la sensibilité rapportée au coût – de la surveillance est essentielle pour aider les gestionnaires à prendre des décisions éclairées concernant l'allocation des ressources. L'objectif de cette étude était d'évaluer l'efficience du système français de surveillance de la brucellose bovine à partir de modèles stochastiques d'arbres décisionnels. Le système de surveillance actuel, qui inclut la déclaration obligatoire des avortements, un dépistage sérologique annuel dans tous les élevages et des contrôles sélectifs des bovins achetés, répond aux objectifs de détection fixée par la réglementation européenne. Toutefois, un système alternatif incluant la déclaration obligatoire des séries d'avortements et un dépistage sérologique d'élevages sélectionnés parmi ceux les plus à risque serait plus efficient. De telles évolutions, tout en respectant les spécifications européennes concernant le statut indemne, réduiraient fortement le coût annuel de la surveillance. Ces économies pourraient être réinvesties dans des mesures complémentaires visant à l'amélioration opérationnelle de la surveillance

Relationship between surveillance system sensitivity and cost-effectiveness for bovine brucellosis in France at P = 0.01%.

<p>Each scenario included programmed serological testing (PROG, described by marker shape), clinical surveillance of abortions (CLIN, described by marker fill), and testing at introduction or not (INTRO, described by marker outline color).</p

Establishing Winter Origins of Migrating Lesser Snow Geese Using Stable Isotopes

Increases in Snow Goose (Chen caerulescens) populations and large-scale habitat changes in North America have contributed to the concentration of migratory waterfowl on fewer wetlands, reducing resource availability, and enhancing risks of disease transmission. Predicting wintering locations of migratory individuals is critical to guide wildlife population management and habitat restoration. We used stable carbon (δ13C), nitrogen (δ 15N), and hydrogen (δ2H) isotope ratios in muscle tissue of wintering Snow Geese to discriminate four major wintering areas, the Playa Lake Region, Texas Gulf Coast, Louisiana Gulf Coast, and Arkansas, and infer the wintering locations of individuals collected later during the 2007 and 2008 spring migrations in the Rainwater Basin (RWB) of Nebraska. We predicted the wintering ground derivation of migrating Snow Geese using a likelihood-based approach. Our three-isotope analysis provided an efficient discrimination of the four wintering areas. The assignment model predicted that 53% [95% CI: 37-69] of our sample of Snow Geese from the RWB in 2007 had most likely originated in Louisiana, 38% [23-54] had wintered on Texas Gulf Coast, and 9% [0-20] in Arkansas; the assessment suggested that 89% [73-100] of our 2008 sample had most likely come from Texas Gulf Coast, 9% [0-27] from Louisiana Gulf Coast, and 2% [0-9] from Arkansas. Further segregation of wintering grounds and additional sampling of spring migrating Snow Geese would refine overall assignment and help explain interannual variations in migratory connectivity. The ability to distinguish origins of northbound geese can support the development of spatially-adaptive management strategies for the midcontinent Snow Goose population. Establishing migratory connectivity using isotope assignment techniques can be extended to other waterfowl species to determine critical habitat, evaluate population energy requirements, and inform waterfowl conservation and management strategies