Movement Matters: Using Swine Shipment Patterns to Identify Farms For Targeted Disease Surveillance and Control - Dr. Amy Kinsley, from the 2018 Allen D. Leman Swine Conference, September 15-18, 2018, St. Paul, Minnesota, USA.
More presentations at http://www.swinecast.com/2018-leman-swine-conference-material
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Dr. Amy Kinsley - Movement Matters: Using Swine Shipment Patterns to Identify Farms For Targeted Disease Surveillance and Control
1. Movement Matters:
Using Swine Shipment Patterns to Identify
Farms For Targeted Disease Surveillance
and Control
Amy C. Kinsley, DVM, PhD
Meggan Craft, PhD
Andres Perez, DVM, PhD
Kim VanderWaal, PhD
2. 1. Describe movement patterns in swine production systems-two regions of
the U.S.
2. Describe and discuss results of analyses in which we used movement data
to better understand how we can identify farms which may be targeted to
increase the efficacy of infectious disease control strategies.
Today’s discussion
3. Contact is a key determinant of transmission of infectious diseases.
Because animal traceability in the US
is limited, there is a lack of
knowledge about the location and
movement of animals in livestock
systems.
Infectious disease epidemics in livestock are important
This is especially true in swine
whose production is
coordinated around stages of
production.
Infectious diseases can have devastating social, economic,
and environmental impacts.
4. Each farm has an equal chance
of mixing with every other
farm in study.
Homogenous mixing within a
defined geographical area.
Pomeroy et al., Transboundary and Emerging Diseases (2015)
Transmission is scaled inversely
with distance from infected
farm.
All means of contact that can
cause disease transmission
that is spatially independent.
Contact can be described in different ways
5. Each farm has an equal chance
of mixing with every other
farm in study.
Homogenous mixing within a
defined geographical area.
Pomeroy et al., Transboundary and Emerging Diseases (2015)
Transmission is scaled inversely
with distance from infected
farm.
All means of contact that can
cause disease transmission
that is spatially independent.
Contact can be described in different ways
11. Trends:
1. Finishing farms have
higher in-degrees
than out-degrees.
2. Nursery farms have
higher out-degrees
than in-degrees.
Is this in line with your
expectations? Why or
why not?
13. 50 day snapshots for
the entire year
Shweta Bansal et al. (2010)
Noremark et al. BMC Vet Research (2014)
14.
15. 𝑅𝑜 = 𝐷 ∗ 𝑝 ∗ 𝑐
D = duration of infectiousness
p=probability of infection given contact
c=average contact rate
Vulnerability of a system to disease spread
R0- “R nought”- The number of secondary infections an infected person (or farm) in a
completely susceptible population.
In the beginning of an outbreak in which there is no immunity
Take-away points of the equation:
1. R0 is a function of properties specific to the pathogen
and to the population’s contact rate (contact
necessary for disease transmission)
2. These two components can be separated and
quantified
18. Can we use these metrics to target farm in order to reduce vulnerability?
“Removing” farms can potentially decrease vulnerability to disease spread
19. Can we use these metrics to target farm in order to reduce vulnerability?
“Removing” farms can potentially decrease vulnerability to disease spread
20.
21. • Biosecurity
• We only focused on movement-based transmission
• Movement patterns change over time-one year might not represent the next
Limitations
22. Advisors and collaborators:
Andres Perez, Meggan Craft, Kimberly VanderWaal
Funding Sources:
Samuel Maheswaran Fellowship
Acknowledgements
Editor's Notes
Points within to solicit feedback-questions-what would expect for farms with the highest MIP ( have two or three points)
Will we use all 3 production systems?
Because
So we know that for livestock populations, infectious disease transmission occurs through three main routes.
Simplify-we don’t know anything about contact—location, movement, etc we know this is essential for tx
Spatial representation of FMDV transmission. Multiple methods have been used to capture FMDV transmission among farms. Some models assume homogeneous mixing, implying high rates of mixing in the host population (Garner and Lack, ; Haydon et al., ; Bouma et al., ; Tsutsui et al., ; Ap Dewi et al., ; Kobayashi et al., ). Other models assume local interactions (Doran and Laffan, ; Ward et al., ; Highfield et al., ) or kernel‐weighted spread (Keeling et al., ; Chis Ster and Ferguson, ), indicating that transmission is based on the distance between susceptible and infectious farms. Finally, network models provide an alternative representation, in which the contact structure is based on multiple factors (Green et al., ; Kiss et al., ; Kao et al., ).
IF THIS IMAGE HAS BEEN PROVIDED BY OR IS OWNED BY A THIRD PARTY, AS INDICATED IN THE CAPTION LINE, THEN FURTHER PERMISSION MAY BE NEEDED BEFORE ANY FURTHER USE. PLEASE CONTACT WILEY'S PERMISSIONS DEPARTMENT ON PERMISSIONS@WILEY.COM OR USE THE RIGHTSLINK SERVICE BY CLICKING ON THE 'REQUEST PERMISSIONS' LINK ACCOMPANYING THIS ARTICLE. WILEY OR AUTHOR OWNED IMAGES MAY BE USED FOR NONTO PROPER CITA
Spatial representation of FMDV transmission. Multiple methods have been used to capture FMDV transmission among farms. Some models assume homogeneous mixing, implying high rates of mixing in the host population (Garner and Lack, ; Haydon et al., ; Bouma et al., ; Tsutsui et al., ; Ap Dewi et al., ; Kobayashi et al., ). Other models assume local interactions (Doran and Laffan, ; Ward et al., ; Highfield et al., ) or kernel‐weighted spread (Keeling et al., ; Chis Ster and Ferguson, ), indicating that transmission is based on the distance between susceptible and infectious farms. Finally, network models provide an alternative representation, in which the contact structure is based on multiple factors (Green et al., ; Kiss et al., ; Kao et al., ).
IF THIS IMAGE HAS BEEN PROVIDED BY OR IS OWNED BY A THIRD PARTY, AS INDICATED IN THE CAPTION LINE, THEN FURTHER PERMISSION MAY BE NEEDED BEFORE ANY FURTHER USE. PLEASE CONTACT WILEY'S PERMISSIONS DEPARTMENT ON PERMISSIONS@WILEY.COM OR USE THE RIGHTSLINK SERVICE BY CLICKING ON THE 'REQUEST PERMISSIONS' LINK ACCOMPANYING THIS ARTICLE. WILEY OR AUTHOR OWNED IMAGES MAY BE USED FOR NONTO PROPER CITA
Basics of network analyses-how they have been used in animal movement before.
Add Dates- what we assumed-removed slaughter facilities etc.
Highlight an example
The dynamic nature of contact networks in infectious disease epidemiology
Shweta Bansal, Jonathan Read, Babak Pourbohloul & Lauren Ancel Meyers
https://doi.org/10.1080/17513758.2010.503376
(2010)
The dynamic nature of contact networks in infectious disease epidemiology
Shweta Bansal, Jonathan Read, Babak Pourbohloul & Lauren Ancel Meyers
https://doi.org/10.1080/17513758.2010.503376
(2010)
vulnerability of network (production system) to disease spread
vulnerability of network (production system) to disease spread
Removing removing nodes from the network-surveillance and removing with variation in degree. Remove the highest MIp-how does it lead to decreases
Removing removing nodes from the network-surveillance and removing with variation in degree. Remove the highest MIp-how does it lead to decreases