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Mapping Disease Transmission Risk
from Biogeographic and Ecological
Perspectives
A. Townsend Peterson
University of Kansas
Why Maps for Diseases?
• Where to focus resources for vaccination?
• Where to focus educational efforts?
• Where to place ...
Published January 2004
• Marburg disease
distribution
• Spotty, patchy
potential distribution
across eastern and
southern Africa
• Distinct ecolo...
• Marburg disease
distribution
• Spotty, patchy
potential distribution
across eastern and
southern Africa
• Distinct ecolo...
Update to 2015:
• Approximate doubling in information
over 2004 efforts
• Species by species model
development
• Explicit ...
THE CURRENT DISEASE TOOLKIT
Dots on Maps
?
?
?
?
?
The Situation …
• Spatial-only models do nothing to establish a
connection between occurrence and context
• No good way to...
Geography
Disease
Incidence
Geography
Disease
Incidence
Spatial Modeling
Geography
Disease
Incidence
Environmental
Conditions
Geography
Disease
Incidence
Environmental
Conditions
Space-and-
environment Models
Geography
Disease
Incidence
Environmental
Conditions
Interactions
among species
Pathogens
Vectors
Hosts
Workflow
• Understand disease system in detail
• Identify suite of species relevant to the disease
(vectors, hosts, pathog...
Lutzomyia longipalpis
ResearchedRaw
Lassa: Uncareful Results
Effects of Quality Control
Effects of Reducing Oversampling
Effects of Error Balance
New Approaches, Gaps, and Impediments
• Mapping and modeling approaches based in ecology
and biogeography have much to off...
CASE STUDIES
Lutzomyia longipalpis and Climate Change
Chile?
• Aedes albopictus • Aedes aegypti
CONSTRAINTS AND LIMITATIONS
Examples of Disease-relevant Data
Examples of Disease-relevant Data
Examples of Disease-relevant Data
Examples of Disease-relevant Data
Examples of Disease-relevant Data
Examples of Disease-relevant Data
Examples of Disease-relevant Data
Examples of Disease-relevant Data
town@ku.edu
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
Mapping Disease Transmission Risk
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Mapping Disease Transmission Risk

  1. 1. Mapping Disease Transmission Risk from Biogeographic and Ecological Perspectives A. Townsend Peterson University of Kansas
  2. 2. Why Maps for Diseases? • Where to focus resources for vaccination? • Where to focus educational efforts? • Where to place diagnostic facilities and equipment? • In short, where to expect a disease to occur, and where not????
  3. 3. Published January 2004
  4. 4. • Marburg disease distribution • Spotty, patchy potential distribution across eastern and southern Africa • Distinct ecological distribution from ebola (open circles) • Potential distribution extends to Cameroon and northern Angola
  5. 5. • Marburg disease distribution • Spotty, patchy potential distribution across eastern and southern Africa • Distinct ecological distribution from ebola (open circles) • Potential distribution extends to Cameroon and northern Angola
  6. 6. Update to 2015: • Approximate doubling in information over 2004 efforts • Species by species model development • Explicit consideration of uncertainty in model predictions • In review for publication
  7. 7. THE CURRENT DISEASE TOOLKIT
  8. 8. Dots on Maps
  9. 9. ? ? ? ? ?
  10. 10. The Situation … • Spatial-only models do nothing to establish a connection between occurrence and context • No good way to anticipate disease transmission risk responses to future climates • Lots of talk, lots of discussion, not much data • Some adaptations of transmission models to the question, but not terribly spatially explicit • These gaps left open many questions…
  11. 11. Geography Disease Incidence
  12. 12. Geography Disease Incidence Spatial Modeling
  13. 13. Geography Disease Incidence Environmental Conditions
  14. 14. Geography Disease Incidence Environmental Conditions Space-and- environment Models
  15. 15. Geography Disease Incidence Environmental Conditions Interactions among species Pathogens Vectors Hosts
  16. 16. Workflow • Understand disease system in detail • Identify suite of species relevant to the disease (vectors, hosts, pathogen) • Develop hypotheses of relevant regions (M) for each species • Fit ecological niche models individually for each species • Model or simulate interactions between the species to create transmission system • Model or simulate human presence and behavior to create risk map • Transfer present model to future (post climate- change) environmental (and human) scenarios
  17. 17. Lutzomyia longipalpis
  18. 18. ResearchedRaw
  19. 19. Lassa: Uncareful Results
  20. 20. Effects of Quality Control
  21. 21. Effects of Reducing Oversampling
  22. 22. Effects of Error Balance
  23. 23. New Approaches, Gaps, and Impediments • Mapping and modeling approaches based in ecology and biogeography have much to offer to spatial epidemiology – Working to create a truly predictive methodology that can anticipate disease occurrence • Methods – Need to assure that the methodology used is consistent with the processes that are occurring – Ecology, biogeography, etc. • Data, data, and more data… – Occurrence data for species – Relevant geospatial data – Archival storage of existing samples to allow data recycling
  24. 24. CASE STUDIES
  25. 25. Lutzomyia longipalpis and Climate Change
  26. 26. Chile? • Aedes albopictus • Aedes aegypti
  27. 27. CONSTRAINTS AND LIMITATIONS
  28. 28. Examples of Disease-relevant Data
  29. 29. Examples of Disease-relevant Data
  30. 30. Examples of Disease-relevant Data
  31. 31. Examples of Disease-relevant Data
  32. 32. Examples of Disease-relevant Data
  33. 33. Examples of Disease-relevant Data
  34. 34. Examples of Disease-relevant Data
  35. 35. Examples of Disease-relevant Data
  36. 36. town@ku.edu

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