Slides used in a session during the MOOC course on "Geohealth: Improving Public Health through Geographic Information" organized by the University of Twente. Link: https://www.futurelearn.com/courses/geohealth
2. Vector-borne diseases
A vector is “an insect or any living carrier that transports an
infectious agent from an infected individual or its wastes to a
susceptible individual or its food or most immediate surroundings”
A Dictionary for Epidemiology
Malaria | Dengue | Chikungunya | Yellow-fever
Japanese Encephalitis | Lymphatic filariasis | Leishmaniasis River
blindness | Congo haemorragic fever |Schistosomiasis | Chagas
Lyme disease | Tick-Borne Encephalitis
Source: A global brief on VBD, WHO (2014)
3. Distribution of Lyme disease
http://en.wikipedia.org/wiki/Lyme_disease
Lyme, CT
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8. Serious matter
Lyme disease has a high cost
For citizens:
Long-lasting sequels: muscles and joint pain, brain deterioration
For public health agents:
Treatment for a potentially chronical disease
Population at risk: children and elder
Public health entities and universities monitoring this phenomenon
9. Why is this happening?
Causes
Global warming
Changes in weather
dynamics
Landscape fragmentation
Alteration of wildlife
dynamics
Consequences
Longer tick season
Higher tick densities
Geographic distribution
of ticks is pushing
northwards
Development of new
habitats suitable for ticks
Challenges
How to monitor ticks?
What variables influence
the number of ticks?
Can we predict the
densities of ticks for each
point in the NL?
12. Tekenradar
Collaborative platform created in
2012 by RIVM and WUR
Conceived for the crowdsourced
monitoring of tick bites
More than 40.000 tick bites reports
collected in 4 years
Each tick bite report:
Location, date of the tick bite
Type of vegetation around
Type of activity carried out
13. Tekenradar
What are the situations to report a tick bite?
Mary is 65 years old and likes going to the forest to
pick mushrooms. She has been doing this activity
for 40 years and she knows the forest. Thus, she
says she is not scared of ticks and goes through
high grasses and bushes. But one day she
discovers a tick attached to her skin.
John and his two kids went to play to the
park next to their house. The kids had a
lot of fun rolling in the grass and running
to a nearby forest patch with high vegetation.
A week later, John discovers that one of
them has a big red rash in his shoulder.
Can you think in other common situations to report a tick bite?
15. Volunteered tick sampling
Since 2006:
Group of volunteers sample 17
locations in NL on a monthly
basis
Count ticks in its different life
stages (i.e. larvae, nymph,
adults)
First citizen science project of
its kind!
Source: WUR
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17. Volunteered tick sampling
Now we know the evolution of tick counts in the time series
and we can link it to environmental variables
to train models that predict tick densities…
…and understand main drivers of the phenomenon
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18. Motivation
What can we do with these volunteer data collections?
Answer scientific questions!
1. Identify the enviromental conditions in which tick bites are produced
2. Predict the abundance of ticks in forests
Next section
20. Methodology
Basic scientific method:
1. Identify important factors on the
phenomenon under study:
2. Apply algorithms:
1. Frequent pattern mining
2. Regression
3. Visualize and interpret information
Two use cases:
1. UC1: Identifying factors associated
to Tekenradar tick bites
2. UC2: Predicting tick abundances in
nature
21. UC1: Important factors on tick bites
• Warm days are suitable to go to the forest
• High temperatures means less risk for tick bitesTemperature
• Rainy days are not suitable to go the forest
• Precipitation prevents tick desiccationPrecipitation
• People tend to go to green spaces for leisure activities
• Dense forest canopy prevents tick dessicationVegetation
• Provides a measurement of where risky areas could beDistances
• Helps determining suitable tick habitatsSoil
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22. UC1: Frequent pattern Mining
Efficient form of extracting information from crowdsourced data
Conceptually similar to Amazon or Netflix recommendations:
Watch “Game of Thrones” + “Vikings” suggest “Lord of the Rings”
Buy “PS4” + “Uncharted” suggest “FIFA 2016”
Automatic exploration of data to find hidden patterns:
Suitable for big datasets, where visual exploration is not possible
Count the number of co-occurrences of the variables
Check references for the complete experiment description
24. UC2: Important factors on tick ecology
• Start questing season
• Survival through winterTemperature
• Increases tick survival
• Prevent tick dessicationPrecipitation
• Keeps soil moisture high
• Prevent tick dessicationVegetation
• Sustains tick populationWildlife
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25. UC2: Regression
Conceptually similar to linear regression in mathematics
Multiple variables involved Multivariate regression
Non-linear phenomenon Non-linear algorithms
Steps:
1. Volunteer flagging dataset is enriched with environmental data
2. Model is trained with the enriched dataset
3. Model learns the main traits of the non-linear phenomenon of tick densities
4. Model can predict unseen places create tick abundance maps for the Netherlands
27. Summary
Identified the main factors associated to tick bites
Predicted the tick abundance in the Netherlands
Volunteer data can be used to feed a scientific workflow