Module 7 - One Health Research Tools Flashcards
6 Factors of epidemiological triangle
- Microbial adaptation and change
- Economic development and land use
- Changing ecosystems
- Human demographics and behavior
- International Travel and commerce
- Poverty and Social inequity
The purpose of spatial epidemiological investigations in
zoonotic diseases (SuGAR) - what does it stand for?
- Su-rveillance: investigating how diseases changes in space & time, unusual occurrences of
disease. (Outbreak investigations; location, source, aetiology of
outbreaks) - G-enerating/testing hypotheses about
environmental determinants of diseases
(Relationship between disease and landscape factors. Spatial autocorrelation; friend or foe?) - A-dvocacy: delivering information to encourage investment in disease control, surveillance, etc. (Highlighting areas where information is lacking)
- R-esource allocation for control programmes
(Geographic targeting; improved efficiency; prioritising
interventions for sub-populations most at-risk. Objective decision framework; uncertainty & decision)
The purpose of spatial epidemiological investigations in
zoonotic diseases (SuGAR) - what does it stand for?
- Su-rveillance: investigating how diseases changes in space & time, unusual occurrences of
disease. (Outbreak investigations; location, source, aetiology of
outbreaks) - G-enerating/testing hypotheses about
environmental determinants of diseases
(Relationship between disease and landscape factors. Spatial autocorrelation; friend or foe?) - A-dvocacy: delivering information to encourage investment in disease control, surveillance, etc. (Highlighting areas where information is lacking)
- R-esource allocation for control programmes
(Geographic targeting; improved efficiency; prioritising
interventions for sub-populations most at-risk. Objective decision framework; uncertainty & decision)
Layers of information
Spatial Data collection
- Disease data: Surveillance + disease reporting systems, field surveys
- Climate data: RS, weather stations (point locations –
need interpolation) - Administrative/infrastructural data: Paper maps, aerial
photos (need digitisation)
Spatial Disease data
- you need to know the location of disease events in
both animal and humans. - XY co-ordinates – point source data (Determined using global positioning systems (GPS) or reading of map co- ordinates (typical of field surveys))
- Aggregated by administrative/geographic unit
(District, state, province) typical of surveillance data
Rastor vs vector data
Rastor:
- simple data e.g. temp, air pressure, elevation etc,
Vector:
- complex data e.g. borders, roads, rivers
GIS (geographical information systems)
Data collected and stored for analysis and interpretation
- stored geographical (i.e. topology) and attribute (e.g. quantitative and qualitative) information
- stored in format:
vector (polygons, points, lines)
raster (pixels/grid cells)
images (photos.jpeg etc)
Choropleth vs cartogram maps
Choropleth: maps used where colour codes determine data e.g. darker green means higher population density and lighter green means less etc.
Cartogram: a map in which the geometry of regions is distorted in order to convey the information of an alternate variable. The region area will be inflated or deflated according to its numeric value
Types of spatial distribution
Uniform: Uncommon. Evenly spaced.
Random: very rare. random (dots) everywhere
Clumped: most common. clumped in groups (e.g populations)
Test statistics
- Spatial v. spatiotemporal
- Point (eg. SatScan) v. area data (Moran’s I)
- Global v. local v. putative source
- Just case v. case-control & case-population
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Spatial analysis framework
this diagram who knows maybe ill need to know this
Issues with spatial clusters of One Health
diseases/events
diagram
Determinants of disease clustering
- Population distribution
– Human population
– Animal density
distribution
– Farm locations - Distribution of disease
control
– Vaccination coverage
– Distribution of water
and sanitation - Distribution of
socioeconomic factors
– Behavior
– Health access
– Husbandry systems - Distribution of
landscape variation
– Physical environment
– Climate indicators
Example Applications of Risk Analysis
- Management and finance
* bank loans
* stock market
* insurance - Engineering
* nuclear power plants - Environmental impact
* industrial production
Define Hazard with examples
something that can cause adverse effects
(harm)
e.g.
- presence of microbiological
organisms in food
- infection with specific diseases
in animals/environment
- radiation from nuclear power
plant
- crash of an airplane
Define Risk
- one unwanted outcome amongst several possible
(uncertainty about which outcome will occur) - likelihood of occurrence of adverse effects and magnitude of consequences given occurrence
- probability AND consequences
Risk Assessment
process of defining risk(s) associated with hazard
* evaluation of likelihood, of biological and economic
consequences of entry, establishment, or spread of
pathogenic agent within population
may be qualitative or quantitative
* qualitative assessment more common due to lack of data
Risk Management
- process of formulating and implementing measures designed to reduce likelihood of unwanted event occurring, or magnitude of its consequences
- balance risks against benefits
- economic analysis
- decision & policy makers
Risk Communication
Interactive exchange
* of information and opinions on hazards and risk
* among risk assessment team, risk managers and other interested parties (stakeholders)
During RA and afterwards
6 Steps in defining a Risk Question
1, What is the specific hazard of concern?
* Pathogen X ; Long list of pathogens
2. What are the vector/vehicle/of the hazard of concern
* Live animals
* products
3. What is the source population
* Country
* Farm
4. What is the receptor population
* Country
* Farm
5. What specific risk do we want to assess
* Importation
* Introduction
6. What particular time frame are we interested in?
* E.g. Risk per year
The RA components in a OIE quantitative
framework
- Release of Hazard (from the individual/physical location) – EVENTS OUTSIDE END RECEPTOR
o Starts by using prevalence data.
o Looks at pathways in which the infected “commodities” are not detected under the surveillance system components (sanitary measures; diagnostic tests) - Exposure to Hazard (exposure of individual in end receptor) – EVENTS IN END RECEPTOR
o Conditional probability
o The exposure end-point is usually taken as the point of entry into the end receptor, not exposure of a
susceptible animal – which is harder to estimate.
o Looks at pathways in which the infected individuals (or animal products) are not detected under the
sanitary measure (usually diagnostic tests). - Establishment, spread and other consequences
o Is considerably harder to model
o Involves dose-response relationship and modelling spread of outbreak, and social, financial and public
health costs.
Risk Pathways – Definition & purpose
- Framework on which to base the risk assessment
- Entirely dependent on the risk question
- Describe all stages (physical and biological) in the
processes that lead to the outcome of interest - model
the system of interest. - Identify sources and types of relevant data for the RA
- Transversal to the three components of the RA
Two types:
* Physical
* Biological
* Not all are needed to assess the risk
* All identified are to be assessed
Modelling physical risk pathways
Physical Process – Stage in the real world
* Framework Node – Stage in our model
* Connectors
directional dependencies - QlRA
Probabilistic - QnRA
Relevant or irrelevant to the RA: data must be sought
* Outcome – end point(s) of the model
Dependant on the risk question
Relevant to the RA
Desired or not
