The use of vaccines to control pathogen spread in pig populations

Vaccine efficacy has often been studied from the viewpoint of individual direct clinical protection. For several vaccines, a decrease in pathogen shedding in vaccinated animals has also been documented, which suggests that transmission between individuals has the potential to be reduced. In addition, vaccination induces an immune response in the host potentially decreasing susceptibility to infection in comparison with immunologically naïve animals. As a collective result of individual vaccinations, vaccine programmes generally have a wider impact on pathogen diffusion at the population scale. Beyond the individual protection conferred by mass vaccination campaigns, the indirect protection of non-immune individuals in contact with vaccinated ones also contributes to controlling pathogen spread at the population scale; a phenomenon known as herd immunity. Pathogen spread within pig populations is strongly related to the required vaccine coverage at the population level and to pathogen characteristics in terms of diffusion ([Formula: see text] ). Before setting up vaccination programmes, it is therefore necessary to have quantitative knowledge on vaccine efficacy as regards transmission reduction. These data can be obtained by carrying out experimental studies or observational protocols in real conditions. These quantitative data have mainly been estimated for major infectious diseases which have now been eradicated. A great gap in knowledge has however been identified for enzootic diseases which are daily impacting the swine sector as well as for the source of variation responsible for a decrease in vaccine efficacy as compared to assessments obtained in experimental conditions

Pig herd management and infection transmission dynamics: a challenge for modellers

The control of epidemics requires a thorough understanding of the complex interactions between pathogen transmission, disease impact, and population dynamics and management. Mechanistic epidemiological modelling is an effective way to address this issue, but handling highly structured and dynamic systems, remains challenging. We therefore developed a novel approach that combines Multi-Level Agent-Based Systems (MLABS) with spatial and temporal organization, allowing for a tuned representation of the transmission processes amongst the host population. We applied this method to model the spread of a PRRSv-like virus in pig farms, integrating the clinical consequences (conception and reproduction failures), in terms of animal husbandry practices. Results highlighted the importance to account for spatial and temporal structuring and herd management policies in epidemiological models. Indeed, disease-related abortions, inducing reassignments of sows in different batches, was shown to enhance the transmission process, favouring the persistence of the virus at the herd level. Supported by a declarative Domain-Specific Language (DSL), our approach provides flexible and powerful solutions to address the issues of on-farm epidemics and broader public health concerns. The present application, based on a simple Susceptible-Exposed-Infected-Recovered (SEIR) model, opens the way to the representation of more complex epidemiological systems, including more specific features such as maternally derived antibodies, vaccination, or dual infections, along with their respective clinical consequences on the management practices

Stream Geometry And Streambed Material Characteristics Of The Streams Within The Highland Silver Lake Watershed, Highland, Illinois

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Estimation of transmission parameters of a fluoroquinolone-resistant Escherichia coli strain between pigs in experimental conditions

Antimicrobial resistance is of primary importance regarding public and animal health issues. Persistence and spread of resistant strains within a population contribute to the maintenance of a reservoir and lead to treatment failure. An experimental trial was carried out to study the horizontal transmission of a fluoroquinolone-resistant Escherichia coli strain from inoculated to naïve pigs. All naïve contact pigs had positive counts of fluoroquinolone-resistant E. coli after only two days of contact. Moreover, re-infections of inoculated pigs caused by newly contaminated animals were suspected. A maximum likelihood method, based on a susceptible-infectious-susceptible (SIS) model, was used to determine the transmission parameters. Two transmission levels were identified depending on the quantity of bacteria shed by infected individuals: (i) low-shedders with bacterial counts of resistant E. coli in the faeces between 5*103 and 106 CFU/g (βL = 0.41 [0.27; 0.62]), (ii) high shedders with bacterial counts above 106 CFU/g (βH = 0.98 [0.59; 1.62]). Hence, transmission between animals could be pivotal in explaining the persistence of resistant bacteria within pig herds

Mathematical modeling at the livestock-wildlife interface: scoping review of drivers of disease transmission between species

Modeling of infectious diseases at the livestock-wildlife interface is a unique subset of mathematical modeling with many innate challenges. To ascertain the characteristics of the models used in these scenarios, a scoping review of the scientific literature was conducted. Fifty-six studies qualified for inclusion. Only 14 diseases at this interface have benefited from the utility of mathematical modeling, despite a far greater number of shared diseases. The most represented species combinations were cattle and badgers (for bovine tuberculosis, 14), and pigs and wild boar [for African (8) and classical (3) swine fever, and foot-and-mouth and disease (1)]. Assessing control strategies was the overwhelming primary research objective (27), with most studies examining control strategies applied to wildlife hosts and the effect on domestic hosts (10) or both wild and domestic hosts (5). In spatially-explicit models, while livestock species can often be represented through explicit and identifiable location data (such as farm, herd, or pasture locations), wildlife locations are often inferred using habitat suitability as a proxy. Though there are innate assumptions that may not be fully accurate when using habitat suitability to represent wildlife presence, especially for wildlife the parsimony principle plays a large role in modeling diseases at this interface, where parameters are difficult to document or require a high level of data for inference. Explaining observed transmission dynamics was another common model objective, though the relative contribution of involved species to epizootic propagation was only ascertained in a few models. More direct evidence of disease spill-over, as can be obtained through genomic approaches based on pathogen sequences, could be a useful complement to further inform such modeling. As computational and programmatic capabilities advance, the resolution of the models and data used in these models will likely be able to increase as well, with a potential goal being the linking of modern complex ecological models with the depth of dynamics responsible for pathogen transmission. Controlling diseases at this interface is a critical step toward improving both livestock and wildlife health, and mechanistic models are becoming increasingly used to explore the strategies needed to confront these diseases

Mediating gel formation from structurally controlled poly(electrolytes) through multiple "head-to-body" electrostatic interactions

Tuning the chain-end functionality of a short-chain cationic homopolymer, owing to the nature of the initiator used in the ATRP polymerisation step, can be used to mediate the formation of a gel of this poly(electrolyte) in water. While a neutral end group gives a solution of low viscosity, a highly homogeneous gel is obtained with a phosphonate anionic moiety, as characterized by rheometry and diffusion NMR. This novel type of supramolecular control over poly(electrolytic) gel formation could find potential use in a variety of applications in the field of electroactive materials