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Enhanced Surveillance for Avian Influenza and Other Disease Risks. Professor Roger Morris and colleagues Massey University EpiCentre Palmerston North New Zealand. Why do surveillance?. To provide evidence that a disease is absent

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enhanced surveillance for avian influenza and other disease risks

Enhanced Surveillance for Avian Influenza and Other Disease Risks

Professor Roger Morris and colleagues

Massey University EpiCentre

Palmerston North New Zealand

why do surveillance
Why do surveillance?
  • To provide evidence that a disease is absent
  • To reduce the risk of taking the wrong disease control action
  • And the risk of failing to act when necessary to do so
  • We are developing economic methods to decide how to invest each dollar of surveillance money most wisely
adapting surveillance to new needs
Adapting surveillance to new needs
  • Surveillance systems have not adapted fast enough to changing requirements
  • Need to make surveillance more “risk-based”
  • Diseases form a limited number of epitypes – require similar surveillance strategies
  • Scanning and targeted surveillance
  • Design better systems to collect and analyse surveillance data so that it is used effectively for making wise decisions
  • Make outputs more current and targeted to the various users of the data
risk based surveillance
Risk-based surveillance
  • Develop surveillance portfolio
  • Balanced combination of techniques
  • Scanning surveillance – broad assessment
  • Targeted surveillance – answer specific questions about a disease
  • Use information on risk factors for a disease to help allocate effort
  • Develop risk landscape to guide decisions on surveillance strategy – surveillance data lowers the risk mountains to a flat plain
the epidemiological toolbox
The epidemiological toolbox
  • Data gathering which can yield a valid and insightful assessment of field disease situation
  • Analytical tools which can achieve this
  • Modelling tools to evaluate and predict
  • Surveillance portfolio to guide decisions
  • Integrating information system to make it happen
disease mapping for surv eillance
Disease mapping for surveillance
  • GIS software now very important to interpret patterns of disease
  • Especially if used jointly with other epidemiological methods
  • Allows more cost-effective selection of samples to include in surveillance system
  • Now have powerful analytical techniques to interpret spatial patterns and relate to risk factors
data gathering methods
Data gathering methods
  • Expanding range of methods used
  • Participatory methods
  • Syndromic surveillance
  • Field investigation strategies
  • Molecular epidemiology linked with other tools
  • Laboratory data should be tightly targeted
  • Integrate laboratory and field methods
  • Multiple imperfect methods better than single perfect source
Farmer surveys – simple but effective

300 duck farmers in southern Vietnam interviewed in two weeks

Are ducks really the problem here? – 98% have more than 80% of ducks vaccinated

But 60% of these people have less than 80% of chickens vaccinated

Ducks are not moved nearly as far as senior vets thought

ai investigation in villages and markets
AI investigation in villages and markets
  • Investigating low path viruses as well as H5N1 can help give a better understanding of methods of spread of AI viruses, and how to control them
  • In Hong Kong markets, spread involved drinking water, minor poultry species (quail), pet rooster
  • Spread of H5N1 to local farms was from markets, not the other way
  • Molecular epidemiology showed that there were four incursions not one, with different spread
studies in vietnam
Studies in Vietnam
  • Vietnam has had a lot of outbreaks, has made good progress in reducing the number per year
  • Analysed spatial and temporal pattern of poultry outbreaks 2004-7, especially in two deltas
  • Association between human and poultry cases
  • Role of ducks and other birds in AI spread, factors influencing disease occurrence
  • Will use this information to develop a targeted surveillance system, with computer tools to support it
poisson regression of risk areas
Poisson regression of risk areas
  • Examined pattern of outbreaks 2003-4 using a grid overlaid on country
  • Areas with over 66% of land irrigated at much higher risk of outbreaks
  • Areas below 250m altitude at increased risk
  • Other factors examined were not influential
  • Potential use of satellite imaging to guide surveillance investment
how should we investigate ai
How should we investigate AI?
  • Sero-monitoring has only limited value in a vaccinated population
  • Is NOT a disease surveillance method in this situation, only checks vaccine coverage
  • Want 80%+ birds protected for AI
  • To test whether protection level adequate, test 250 animals – for any size population
  • So design sampling plan to test that vaccination program is working in different sectors (3, 4), production systems and regions of the country
disease surveillance
Disease surveillance
  • Want to determine distribution of infection and transmission patterns
  • PCR is a valuable technique, but only useful if use virus isolation as well, to confirm that virus is circulating and check PCR accuracy
  • PCR should always give some positives, even if no infection present!
  • Virus isolation and molecular strain investigation most useful investigation method to understand virus transmission
investigating ai
Investigating AI
  • Focus should be on understanding how infection is transmitted and maintained, then monitoring it
  • Main emphasis should be on investigating sector 3 and sector 4 flocks, live bird markets
  • Need epidemiological investigation strategy to answer key questions through good design
  • If you ask the right questions, spend far less on testing, but get more useful results
  • Use modern analytical methods
data analysis
Data Analysis
  • Many powerful analytical methods now available
  • Do not need perfect data provided that study design is sound
  • Carefully designed intensive epidemiological investigations to examine risk factors are far more useful than large-scale sampling done without collecting risk factor data
  • Then can use modelling and other techniques to test various explanations of the disease pattern
Number of cattle moved OUT of departments for finishing: Jan - Mar

Social network analysis can be used to investigate disease spread pathways

Grey lines indicate movement of > 1000 head for 3-month period. Symbols proportional to number of cattle moved.

spatial modelling of disease
Spatial modelling of disease
  • Valuable method of assessing possible causes
  • Valuable for evaluating control options
  • We use generic spatial models which can be given the “profile” of any known (or new) disease
  • Modelled foot and mouth disease epidemic in 2001 for Britain, modelling avian influenza with same model
monitoring control program results
Monitoring control program results
  • Need baseline data on the situation before control activities are started
  • Need to use a monitoring system which accurately measures change in prevalence of disease and/or infection
  • Need to gather information which will allow you to detect and respond to weaknesses in the program
animal health information system
Animal health information system
  • Use an approach which suits the needs of the country, start simple but with development plan
  • It must allow data analysis from the start, and be able to advance as the country’s needs change
  • Should include both disease control and surveillance
  • Ability to map disease data should be seen as an important feature which must be available, though it may not be used at first
developing a surveillance portfolio
Developing a surveillance portfolio
  • Retirement planning:
    • Invest in multiple assets to spread your risk
    • Evaluate performance by expected $$ return
    • Consider variation around $$ return
  • Surveillance assets:

Invest in multiple surveillance techniques to give balanced picture

Can use points per sample or investigation, instead of $$

Each component of surveillance program has a different cost and different number of points achieved by particular test or investigation

Applied to BSE and Trichinella, adapting to other diseases

Risk-based sampling can give better assurance of disease state

risk based sampling for exotic disease
Risk-based sampling for exotic disease

Comparison of the number of tests allocated per SA and the maximum possible disease prevalence in ewe flocks (α = 0.05) when distributing samples using portfolio theory (PT) and proportional allocation (PA)

risk assessment
Risk assessment





feedback to participants
Feedback to participants
  • A major issue in achieving effective surveillance is getting cooperation from data providers
  • Essential for completeness, and to minimise bias
  • Feedback is most important stimulus to continuing cooperation
  • We need to be ready to face and solve new disease challenges
  • Effective surveillance is the key to quick detection and effective control
  • Surveillance needs multiple sources of information, and smart tools for interpretation
  • Need integrated surveillance and response strategy if we are to control future diseases successfully, and a toolbox of techniques to quickly determine what is going on