This talk is based on the research article:
K. Glass and B. Barnes, “Eliminating infectious diseases in
livestock: A metap...
Kathryn Glass1 & Belinda Barnes1,2
1Australian National University
2Department of Agriculture, Fisheries and Forestry
MOTIVATION
OUTLINE
1. Model
2. Results
3. Applications
and relevance to biosecurity
4. Conclusions
disease occurs in clust...
THE MODEL
spread in
local
regions
global
spread
low density high density
The model
global
spread
local regions
more local regions
low densityhigh density low density
low densityhigh density
The model
local regions
more local regions
high
mixing
event
The model
local
within region
spread
high
mixing
global
between
region
spread
ERADICATION STRATEGIES
1. Quarantine
2. Vaccination
3. Culling
4. Restrict attendance at, or
cancel, high-mixing events
5....
QUARANTINE
local
spread
high
mixing
event
global
spread
slow
response
1.
2. rapid
response
VACCINATION
homogeneous vaccination
or
heterogeneous vaccination
1.
2. Vaccine efficacy
GLOBAL TRANSMISSION
MATRIX








)1(
)1(


LL
HH
xx
xx
with no control
mean outbreak
size in local H
a...
RESULTS for quarantine
disease elimination in shaded areas
rapid response
certain
elimination
elimination
local infection ...
RESULTS for quarantine
disease elimination in shaded areas
rapid response
certain
elimination
local infection rate
global ...
RESULTS for vaccination
local and global infection rates have considerable impact on the
probability of elimination throug...
RESULTS for
quarantine, vaccination and high-mixing
70% coverage,
med efficacy
90% coverage,
high efficacy
disease elimina...
RESULTS for
quarantine, vaccination and high-mixing
high mixing events are a powerful mechanism
for spread
70% coverage,
m...
y-axis is probability of disease elimination
elimination elimination
global infection rate
whether quarantine, heterogeneo...
SUMMARY
• the ‘best’ intervention for eradication is highly
dependent on local and global disease characteristics
• in gen...
Relevance to biosecurity
questions
• assessment of alternative elimination strategies
• impact of delayed response
• estim...
CONCLUSIONS
• branching process
• probability of disease elimination
• early stages of an outbreak
and what it offers
• co...
RESULTS
RESULTS
disease elimination including high mixing events
global infection
rate
local infection rate
if mixing events open ...
y-axis is probability of disease elimination
elimination elimination
global infection
rate
local infection
rate
if vaccina...
TRANSMISSION MATRIX
    
   







LL
HHHH
yppypp
yppyppfxf
2121
2121
)1(
)1()1(


wit...
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Eliminating Infectious Diseases: a metapopulation model of infection control with an application to livestock. - Belinda Barnes

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This talk was presented by Belinda Barnes at “ A Planet at Risk” (BioInvasion and BioSecurity Workshop, at CSIRO)

Abstract. When novel disease outbreaks occur, policy makers must respond promptly, and are typically called on to make control decisions before detailed analysis of disease parameters can be undertaken. In this talk I will present a flexible metapopulation model of disease spread that incorporates variation in population density and distinct mechanisms of spread, and includes occasional high-mixing locations or events. Using a statistical approach (probability generating functions derived from this branching process model), we compare the likely success of reactive control strategies in eliminating disease spread in livestock. We compare distinct vaccination strategies and find that the optimal strategy varies according to the disease transmission rate. Quarantine combines well with vaccination, with the chance of disease elimination enhanced even for vaccines with low efficacy. We show that high-mixing events (for example, markets or race meetings) are a powerful spread mechanism, even when the proportion of time spent at such events is low. And if such events continue, elimination will require a highly effective vaccine with high coverage. However, banning animals from quarantined regions from attending such events can provide an effective alternative if full closure of events is economically untenable.


When novel disease outbreaks occur, policy makers must respond promptly, and are typically called on to make control decisions before detailed analysis of disease parameters can be undertaken. In this talk I will present a flexible metapopulation model of disease spread that incorporates variation in population density and distinct mechanisms of spread, and includes occasional high-mixing locations or events. Using a statistical approach (probability generating functions derived from this branching process model), we compare the likely success of reactive control strategies in eliminating disease spread in livestock. We compare distinct vaccination strategies and find that the optimal strategy varies according to the disease transmission rate. Quarantine combines well with vaccination, with the chance of disease elimination enhanced even for vaccines with low efficacy. We show that high-mixing events (for example, markets or race meetings) are a powerful spread mechanism, even when the proportion of time spent at such events is low. And if such events continue, elimination will require a highly effective vaccine with high coverage. However, banning animals from quarantined regions from attending such events can provide an effective alternative if full closure of events is economically untenable.

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Eliminating Infectious Diseases: a metapopulation model of infection control with an application to livestock. - Belinda Barnes

  1. 1. This talk is based on the research article: K. Glass and B. Barnes, “Eliminating infectious diseases in livestock: A metapopulation model of infection control”, Theoretical Population Biology, 2013, 85, 63-72.
  2. 2. Kathryn Glass1 & Belinda Barnes1,2 1Australian National University 2Department of Agriculture, Fisheries and Forestry
  3. 3. MOTIVATION OUTLINE 1. Model 2. Results 3. Applications and relevance to biosecurity 4. Conclusions disease occurs in clusters locally and globally how can this structure inform elimination strategies can it be used to delay and mobilise
  4. 4. THE MODEL spread in local regions global spread low density high density
  5. 5. The model global spread local regions more local regions low densityhigh density low density low densityhigh density
  6. 6. The model local regions more local regions high mixing event
  7. 7. The model local within region spread high mixing global between region spread
  8. 8. ERADICATION STRATEGIES 1. Quarantine 2. Vaccination 3. Culling 4. Restrict attendance at, or cancel, high-mixing events 5. Combinations
  9. 9. QUARANTINE local spread high mixing event global spread slow response 1. 2. rapid response
  10. 10. VACCINATION homogeneous vaccination or heterogeneous vaccination 1. 2. Vaccine efficacy
  11. 11. GLOBAL TRANSMISSION MATRIX         )1( )1(   LL HH xx xx with no control mean outbreak size in local H and L density regions mean number of new regions infected by a single infective proportion of regions that are high density mean number of low density regions infected by a high density region
  12. 12. RESULTS for quarantine disease elimination in shaded areas rapid response certain elimination elimination local infection rate global infection rate infectiousness BEFORE quarantine possible elimination slower response reproductive number R=1
  13. 13. RESULTS for quarantine disease elimination in shaded areas rapid response certain elimination local infection rate global infection rate local infection rate has relatively little impact on the probability of elimination through quarantine slower response certain elimination infectiousness BEFORE quarantine
  14. 14. RESULTS for vaccination local and global infection rates have considerable impact on the probability of elimination through vaccination
  15. 15. RESULTS for quarantine, vaccination and high-mixing 70% coverage, med efficacy 90% coverage, high efficacy disease elimination in shaded areas no high-mixing events no high-mixing from quarantined areas high-mixing events open to all rapid quarantine vaccination high mixing localinfectionrate global infection rate
  16. 16. RESULTS for quarantine, vaccination and high-mixing high mixing events are a powerful mechanism for spread 70% coverage, med efficacy 90% coverage, high efficacy disease elimination in shaded areas no high-mixing events no high-mixing from quarantined areas high-mixing events open to all rapid quarantine vaccination high mixing localinfectionrate global infection rate
  17. 17. y-axis is probability of disease elimination elimination elimination global infection rate whether quarantine, heterogeneous vaccination or homogeneous vaccination is `best’, depends... RESULTS for quarantine and vaccination 90% coverage high efficacy probabilityof elimination 50% coverage high efficacy 90% coverage low efficacy
  18. 18. SUMMARY • the ‘best’ intervention for eradication is highly dependent on local and global disease characteristics • in general local spread amplifies the outbreak, while global spread and high-mixing disperse infection • high-mixing events are a powerful mechanism of spread • interventions in combination may be the most cost effective means to eradication • in certain cases, parameter uncertainty has minimal impact on the results, while in others it is considerable
  19. 19. Relevance to biosecurity questions • assessment of alternative elimination strategies • impact of delayed response • estimation of time until elimination • impact of vaccination in all/some regions • incorporation of different high mixing events for region types • implications of non-compliance • estimation of early spread rates under different interventions ($$) • optimal points of surveillance Current applications under consideration: - infection through interactions between wild animals, feral animals and domestic populations - avian influenza: bird shows and markets, commercial flocks
  20. 20. CONCLUSIONS • branching process • probability of disease elimination • early stages of an outbreak and what it offers • comparison of interventions • generic and flexible infectious disease model • variety of spread mechanisms, region types, population densities and infectiousness functions • appropriate when few data are available • can be interpreted across a wide range of parameter combinations to give general insights • relevant for planning policy, or the reactive response to an outbreak the mathematical/statistical approach
  21. 21. RESULTS
  22. 22. RESULTS disease elimination including high mixing events global infection rate local infection rate if mixing events open to all animals, little chance of disease elimination until vaccine efficacy and coverage is considerable if mixing events closed to some animals, quarantine or moderate vaccination can be very effective quarantine vaccination
  23. 23. y-axis is probability of disease elimination elimination elimination global infection rate local infection rate if vaccination is effective, it can be better than quarantine the better vaccination policy depends on the situation vaccination vaccination quarantine RESULTS for quarantine, vaccination and high-mixing
  24. 24. TRANSMISSION MATRIX                 LL HHHH yppypp yppyppfxf 2121 2121 )1( )1()1(   with high mixing events and quarantine mean number of primary and secondary cases before detection and quarantine         )1( )1()1(   LL HHHH xx xfxxf with high mixing events f = proportion of ‘time at high mixing events with different infection rate
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