D3T2 mapping disease transmission risk

Mapping Disease Transmission Risk from Biogeographic and Ecological

Perspectives

A. Townsend PetersonUniversity of Kansas

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????

Published January 2004

• 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

• 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

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

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 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…

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

Geographic Distributions

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

Lutzomyia longipalpis

Rese

arch

ed

Raw

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 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

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