Mapping tick dynamics and tick bite risk using data-driven approaches and volunteered observations

Presentation slides (Layman's talk, 15min) used during my PhD Defence, held on 27th of September 2019 at the University of Twente (the Netherlands). You can find the PhD thesis here: https://library.itc.utwente.nl/papers_2019/phd/garciamarti.pdf and a summary of the research in plain terms here: https://irenegarciamarti.com/post/rs00-explaining-my-phd-research/. Feel free to contact me at research [at] irenegarciamarti [dot] com if you have any questions.

Transcript

1. 1
   Mapping tick dynamics
   and tick bite risk using
   data-driven approaches
   and volunteered observations
   Irene Garcia-Marti
   27-09-2019
   

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2. CONTEXT
   • Re-emergence of vector-borne diseases:
   • Global & socio-economic changes
   • VDB: 23 diseases (including Zika)
   • Changes + ticks
   • Longer tick season
   • Increase in tick populations
   • Northward + elevation expansion
   • New suitable habitats
   • Concurrent increase of tick-borne diseases
   Source: WHO
   

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3. CONTEXT
   Source: RIVM
   Source: RIVM
   25K – 27K LD cases per year
   ~2K develop persisting symptoms
   

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4. CITIZEN SCIENCE
   TICK ACTIVITY
   • Monitoring tick activity
   • Project started and coordinated by
   WUR researchers
   • Monitoring 15-25 forested locations
   in the NL
   • Sampling:
   • Once a month, 2006-2016
   • Using dragging blanket
   • Counting ticks every 25m
   • ~4,000 samples
   • One of the longest time-series on
   tick activity: unique!
   

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5. CITIZEN SCIENCE
   TICK BITE REPORTS
   WUR + RIVM started Tekenradar in 2012
   Currently 50,000+ samples
   

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6. THE BIGGER PICTURE
   From “Lyme disease: The ecology of a complex system”
   R.Ostfeld (2012)
   

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7. R = H x E
   RESEARCH OBJECTIVES
   Modelling tick bite risk and tick activity using citizen science data
   

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8. DATA AND METHODS
   • General ML operations:
   • Classification
   • Regression
   • Pattern mining
   • ML methods:
   • Random Forest
   • Apriori
   • +
   • Statistics:
   • Poisson, neg. bin.
   • Zero-inflation, skewness
   

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9. TICK
   ACTIVITY (H)
   Daily tick activity
   15/4/2014 to 15/7/2014
   Time-aware
   random forest
   100+ covariates in
   11 time windows
   

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10. EXPLORING
    TICK BITE RISK
    What is the tick bites
    collection monitoring?
    Is there any information?
    EDA with Apriori to
    understand patterns
    of tick bites
    Tick bites are
    a realization of R!
    

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11. HUMAN
    EXPOSURE (E)
    Pre-step before developing
    tick bite risk model
    Bridges the need of
    ICT data
    E clustered at the edges of
    forests and natural areas
    Locating E means we can
    characterize it
    R = H x E E = R ÷ H
    

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12. 12
    TICK BITE
    RISK (R)
    Modification of random
    forest to handle skewed and
    zero-inflated distributions
    Risk is higher along the
    coast
    Combination of H and
    19 new covariates of E
    

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13. CONTRIBUTIONS
    • Illustrating intrinsic relationship
    between R, H, E
    • Atmospheric water levels drive tick
    dynamics
    • Tick bite risk is strongly influenced by
    human exposure
    • Principles can be applicable to
    other tick-borne diseases
    Scientific
    • Modify method to handle time-aware
    observations
    • Modify method to handle skewed
    and zero-inflated distributions
    • Devised simple method to estimate
    human exposure to ticks without ICT
    • Guidelines to explore patterns of R
    Methodological
    • Monitoring elusive phenomena at
    unprecedented levels of detail
    • Observations can have sufficient
    quality to support scientific research
    • Sharing creative approaches at
    validating citizen science observations
    Citizen science
    

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14. FUTURE WORK
    Improving
    prediction of tick
    dynamics
    Creating
    dynamic tick bite
    risk model
    Linking machine
    learning and
    statistics
    Creating apps
    for professionals
    and citizens
    

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15. View Slide

16. 16
    THANKS
    research@irenegarciamarti.com
    

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