Source: UNIVERSITY OF RHODE ISLAND submitted to NRP
TICK BORNE DISEASE PREVENTION, RI
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
Reporting Frequency
Annual
Accession No.
0219072
Grant No.
2009-34520-20120
Cumulative Award Amt.
$261,040.00
Proposal No.
2009-04498
Multistate No.
(N/A)
Project Start Date
Sep 1, 2009
Project End Date
Aug 31, 2012
Grant Year
2009
Program Code
[OJ]- Tick Borne Disease Prevention, RI
Recipient Organization
UNIVERSITY OF RHODE ISLAND
19 WOODWARD HALL 9 EAST ALUMNI AVENUE
KINGSTON,RI 02881
Performing Department
Plant Science
Non Technical Summary
Human and animal diseases transmitted by black-legged ticks are increasing in Rhode Island and the larger northeastern United States region-the health burden from Lyme disease is estimated to cost Rhode Island more than $30 million annual, and in just the past five years, cases of the sometimes fatal human babesiosis and human anaplasmosis have increased in Rhode Island by >1,500% and >2,500%, respectively. The current new project builds on previous work and will focus on improving health promotion tools for tick-bite protection and on increasing the number of people in Rhode Island that take risk-appropriate actions to prevent tick-bites and disease. The project integrates biological and geo-physical research with social science and public health marketing, to create credible health promotion tools and remove stakeholder barriers to implementing tick-bite protection and disease prevention. Specifically, we will create and validate various decision support products (tick risk index, risk calculator, tailored interventions, supporting content, etc) so that they are operational for the entire northeastern US. As a first step, the current project focuses on one research project and two extension projects in Rhode Island. In field experiments, we will test the hypothesis that extended durations of sub-optimum levels of atmospheric moisture directly affects black-legged tick activity and survival. Collected data will be used to develop models that predict nymphal black-legged tick activity. Expected outcomes from this project are improved decision support and an increase in the number of people taking risk-appropriate actions to prevent tick-bites and disease.
Animal Health Component
70%
Research Effort Categories
Basic
30%
Applied
70%
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
7210430117020%
7226050117040%
7236050113020%
7216099113020%
Goals / Objectives
There are three specific objectives of this new project. 1) To assess a multi-sensor approach for predicting tick encounter risk; we will attempt to correlate tick activity levels with direct measurements of relative humidity duration and remotely-sensed variables associated with tick habitat and moisture. Sub-projects under this objective will measure relative humidity in tick habitat as well as obtain humidity data from the Northeast Climate Data Center at Cornell University in an effort to develop an animated model of relative humidity dynamics in tick habitat; additionally, extensive tick encounter surveillance in randomly selected plots will be conducted to correlate with climate variables. Final outputs of the work will be graphs correlating duration of sub-optimal RH and host-seeking nymphal tick abundance. 2) To complete and validate a novel, user-friendly, TickEncounter Risk Calculator and customized health promotion plan to prevent tick-bites in backyard environments in Rhode Island. All modeling for the risk calculator portion is completed but thousands of lines of code remains to be written for the customized health promotion plan. Additionally, we will attempt to functionalize the calculator for Connecticut using town-based Lyme disease incidence data as a surrogate for tick encounter risk. Outputs will be in the form of easily interpreted products providing multi-channel tick-bite prevention decision support during the spring and summer tick risk season. 3) To develop a social marketing protocol for implementing a health promotion campaign to encourage people to regularly use clothing only tick repellents. Outputs will be extensive target audience analyses, detailed campaign goals, marketing mix, and recommendations for a pilot program. The expected outcomes from this project are improved tick-bite protection decision support and an increase in the number of people taking risk-appropriate actions to prevent tick-bites and disease.
Project Methods
Field experiments will be conducted to confirm previous lab-derived atmospheric moisture thresholds associated with blacklegged tick mortality. Additional GIS and remote sensing studies will provide critical data for fine-tuning the site-specificity of the relative humidity predictive model, and for extending the predictive capacity of our TickEncounter Risk Index to the larger Northeast Region. To validate the relationship between tick activity/survival and duration of exposure to sub-optimal RH, we will conduct weekly tick sampling at field sites where humidity data is being collected. An important component of this work will be to establish the relationship between relative humidity in tick habitat and a remotely sensed index. We will employ a hierarchical sampling design to scale-up from in situ field measurements of RH to remote sensing observations. We will take advantage of spatial, spectral, and temporal resolutions from multi-sensor remote sensing data. We will use these regression models to assess which humidity variable (daily average, weekly average, number of consecutive 4 or 6 hr periods below the 82% threshold, etc.) best predicts tick activity levels. Akaike Information Criterion and similar approaches will be used for final model evaluation and selection. A second model based on 15 years of tick encounter risk surveillance in Rhode Island will be used to develop a novel decision support tool, "TickEncounter Risk Calculator-My Backyard". The product will combine static risk maps with images of low and high-risk scenes and activities leading to a customized tick encounter risk value. Once these risk indices become operational, we will begin monitoring incoming web traffic to the TickEncounter Risk Index and TickEncounter Risk Calculator pages on www.tickencounter.org, and evaluate traffic patterns within the site, especially links to www.tickencounter.org/prevention/protectyourself. We also will conduct a follow-up pen and paper mail survey, soliciting 10,000 residents statewide (last conducted in 2004/05, n=1,835), to assess Rhode Islanders tick bite prevention practices.

Progress 09/01/09 to 08/31/10

Outputs
OUTPUTS: To identify barriers that exist in getting parents to adopt and sustain protective behaviors to prevent Lyme disease in their children, two focus groups were scheduled at Blake Middle School in Medfield, MA. Each group will contain no more than 9 participants. Recruitment was open to parents in Medfield, Dover and Sherborn. However, participants include only parents from Medfield which may suggest greater interest or parental involvement. Participants will be asked questions regarding general knowledge of Lyme disease, identifying barriers to preventative behavior, and best or preferred communication practices. Results from these focus groups will be used to develop a pilot tick bite protection social media campaign. PARTICIPANTS: Thomas N. Mather -PI directed project, analyzed data, provided content for website; Katherine Berger- graduate student collected data on ticks and relative humidity; Roland Duhaime- Research Associate assisted in organizing spatial data in databases and in constructing risk maps; Brian Mullen-Technical Programmer created web framework, programmed graphic user interface for risk calculator and 3D animations, web-site maintenance; Holly Spalt-undergraduate intern, tick collection; Jason LaPorte- undergraduate intern, tick collection; Matt Requintina-undergraduate intern, tick collection; David Nelson-undergraduate intern, tick collection; David Curtis-undergraduate intern, tick collection; Jared Carr-undergraduate intern, tick collection. The project provided training for post-doctoral fellows, graduate students and research experience for undergraduate interns. Greta Tessman- graduate student Emerson College, development of social marketing protocol. TARGET AUDIENCES: Rhode Island citizens at risk for tick-bites and tick-borne disease without distinction of racial, ethical, or socio-economical background. The website targeted a broader world-wide audience of people with tick-related questions or who were concerned about preventing tick bites and tick-borne disease. Science-based knowledge was delivered on-line and through workshops, lectures, practicum experiences, extension and outreach. PROJECT MODIFICATIONS: No Modifications to Report

Impacts
We continued to build capacity to make both spatially and temporally relevant tick encounter risk predictions; we demonstrated that National Climate Data Center (NCDC) relative humidity (RH) data can be used to predict RH in tick habitat when adjusted using a sigmoid model. A sigmoid mathematical model effectively described the relationship between hourly RH readings collected using loggers placed in tick habitat and NOAA-NCDC data; NCDC data were tested against previously recorded (2007) logger network data. The model successfully predicted general RH trends throughout Rhode Island; RH levels were predicted at one third of eighteen field sites using a model containing NCDC data from the 4 Rhode Island collection points. The study indicates that while NCDC station data can be predictive of general RH trends in tick habitat, additional parameters, such a site-specific topography, vegetation or elevation, may be needed to more accurately predict RH in specific locales. Additionally, we collected images of high- and low-risk backyard habitats for use in a novel decision support/information system "TickEncounter Risk Calculator My Back Yard". When completed, the product will combine static risk maps with images of low and high risk scenes and common human activities leading to a personalized tick encounter risk value. In this project, we will complete the statistical model for calculating risk, the computer graphics and web framework for both delivering the product in a user-friendly format and for collecting and storing individual users' responses in a secure database. The system will help users decide on tick control and other tick-bite prevention strategies to take by modifying the risk number based on estimates of the likely impact that each action would have on tick encounter risk.

Publications

  • No publications reported this period