Diagnostics and Surveillance

FLUTEST - Improved Diagnosis and early Warning Sytems for Avian Influenza Outbreak Management

Summary:

The primary goal of this proposal will be the joint development and application of technologies to combat avian influenza (AI) infections. This goal will be achieved through the interaction of leading European institutes along with the collaboration of non-EU laboratories experienced in AI outbreak control and management.

A study will be conducted to establish the effectiveness of the current EU surveillance and early warning systems for AI and then to develop blueprints for improvements to these programmes in disease-free periods and during outbreaks. The model will include criteria for harmonised diagnostic tests for on-farm outbreak investigation.

To complement this study a range of diagnostic tools will be developed, evaluated and validated alongside the evaluation of a range of commercially available tests. This will include sophisticated laboratory based methods, high throughput techniques for molecular and serological testing, penside testing and simplified tests for use in laboratories with limited resources or experience. Efforts will particularly focus on the validation of tests for use on clinical materials derived from Anseriformes, other wild bird species and some selected mammalian species.

Problem:

In recent years, Avian influenza (AI) outbreaks have caused severe losses to the poultry industry, its stakeholders and, ultimately, to the EU taxpayer. In addition, the ongoing Asian H5N1 outbreak is a serious concern for food security and human health. It is estimated that since 2000, more than 200 million birds have died or have been culled following infection with influenza viruses subtypes H5 or H7. Approximately 50 million of these birds were from Europe. Importantly, human infections have also been reported in several of these outbreaks. In Asia, due to both social conditions and the particular characteristics of the H5N1 virus, the crossing of the species barrier represents a serious potential risk of a new human pandemic virus emerging.

AI is a highly contagious trans-boundary animal disease, able to spread in a susceptible population in a short period of time. Therefore, the prompt identification of infected animals is crucial for control and eradication purposes. Surveillance must be targeted to appropriate areas and species, and diagnostic tests must be appropriate for the setting in which they will be used, be properly validated and 'fit for purpose'.

Aim:

This project aims to generate data on significant issues linked to AI surveillance and outbreak diagnosis and management, on which scientific knowledge is currently lacking. To complement this we will also develop and validate laboratory tests that can be used as tools in early warning systems and surveillance programmes for AI, in the presence and absence of vaccination. Protocols will be harmonised and applicable to surveillance of wild birds and to different areas of the poultry industry.

Expected results:

We will establish comprehensive, harmonised, validated AI surveillance, 'early warning' and diagnosis protocols, based on an intelligent framework, spanning different poultry populations and industry sectors in the EU. This will provide an appropriate surveillance system model for the EU, with capabilities extending beyond the immediate remit of establishing optimal surveillance strategies.

Such a dynamic surveillance model can also be utilised to provide decision-support mechanisms for disease control policies and enhanced analysis of novel, emerging test technologies and emerging threats or variables that may be encountered in the future. A report will be prepared describing the quality of the current EU surveillance programme and blueprints for improvement of surveillance programmes. A description of the poultry population and production sector demographics across European Union Member States will be provided and the average time between virus introduction and detection and the average number of infected flocks at the time of detection, given the current EU surveillance programme, will be established. Then we will determine the influence that factors such as vaccination, sensitivity and specificity of the test, sample sizes, sampling interval and frequency of clinical inspection have on these parameters.

In addition, factors such as the efficient capture and use of data in the face of an outbreak and the optimum distribution of resources for surveillance and for action on disclosure of the first detected case will be evaluated. This will enable us to establish the optimal lay-out of surveillance programmes, developed 'fit-for-purpose' for different conditions between EU Member States, using different tests available and/or developed in FLUTEST.

FLUTEST will address the issues of molecular diagnostics, antigen detection and novel technologies. The purpose is to focus efforts on the development, evaluation, application and harmonisation of these novel molecular techniques, for detection and differential diagnosis of AI virus infections in domestic and free-living avian populations. The assays will be internationally standardised and validated, by following the OIE rules of assay validation, in order to harmonise and standardise the diagnosis of avian influenza across the EU and to provide tests according to to the standard specified in the EU diagnostic manual. Where appropriate, the assays developed will be transferred to portable formats, trialled between partners and 'in field'.

Experience has shown that introduction of HPAI strains to poultry may not be reported immediately and the situation is exacerbated for LPAI strains. Serological surveillance programmes are not primarily suited to detect an infected flock at a very early stage based on the time lag for detectable seroconversion to occur following exposure and challenge. However, a high-test frequency can counter this disadvantage. Using blood samples at high frequency of testing is impractical and not cost-effective, but the measurement of AI antibodies in egg yolk could offer many advantages. A laboratory test to detect AI antibodies in eggs will be developed, validated and automated to make it cost-effective for use in surveillance programmes.

Many laboratories experience difficulties when subtyping AI isolates with success, influenced by the reagents and the expertise required when interpreting the test results.

A competitive lateral flow device (LFD) will be developed that will subtype the virus isolates. This will involve the use of recombinant antigens and phage display antibodies. An LFD capable of detecting virus specific antibodies will be developed in conjunction with an antigen sub-typing LFD, as both benefit from utilisation of the same recombinant antigens/peptides. This test could have applications for DIVA surveillance when vaccination strategies are employed.

We will also explore innovative technologies for their applicability as avian influenza diagnostic tests. DNA microarrays are powerful tools for the detection and comprehensive characterisation of viruses. They enable multi-agent detection and hence differential diagnosis. However, the optical detection is expensive and difficult to implement in portable instrumentation. An AI biosensor based on microarrays, but using label-free electrical detection of DNA hybridisation, and a novel sensing mechanism employing low-temperature polycrystalline silicon-thin film transistors (LTPS-TFTs) technology will be developed. The advantages of this technology are cost (two to three euro per device), portability and rapid results, typically in less than 15 minutes. Thus it would be ideal for field use and point-of-care diagnosis.

Potential applications:

FLUTEST specifically addresses areas of knowledge which are currently lacking and unexplored and that are crucial to the attainment of high levels of animal health and welfare and consumer protection. In addition, the outcomes of the research will support some of the unanswered questions that are of pivotal importance in the management of the globally expanding impacts and threat of avian influenza.

The data generated will aid decision makers within the European Commission with regard to the prevention and control of epizootic disease of poultry. The project addresses the needs within the EU for sustained improvements in animal health and welfare standards, particularly for a disease which has resulted in high economic losses and poses potential risks to human health.

A key strategic impact of FLUTEST will be the development and provision of a range of validated diagnostic tests tailored to complement surveillance and outbreak management programmes. Techniques will include novel, simple, user-friendly and inexpensive pen-side tests to provide cost-effective, biosecure, point-of-care surveillance and diagnostic test capabilities, tools which can be readily used in the field by veterinarians, abattoirs and small laboratories globally. FLUTEST will therefore provide for validated, front line diagnosis of potential disease. These tests will be complemented and supported with 'high throughput' and rapid assays for use in well equipped laboratories for surveillance and differential diagnosis.

This presents a strategically fundamental factor in the fight against AI. With the availability of such tools, rapid diagnosis is made possible, spread of infection can be limited and all necessary control and/or eradication procedures can be implemented more rapidly.

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