Community-based participatory surveillance; utility of the Kidenga App as a vector surveillance and prevention tool

Transcription

1 Community-based participatory surveillance; utility of the Kidenga App as a vector surveillance and prevention tool NACCHO Presentation, March by Steve Waterman, CDC Dengue Branch Chief

2 Aedes-borne Viruses in the Continental U.S. Ae. aegypti and Ae. albopictus Highly invasive Distribution projected but unconfirmed Vectors of Zika, dengue, chikungunya and yellow fever viruses ZIKV, DENV and CHIKV Small local outbreaks (FL, TX) Evidence of undetected transmission (FL) Predicted suitability for Ae. aegypti or Ae. albopictus, adapted from Kraemer et al., elife 2015;4:e08347 Mild or moderate symptoms common (ZIKV/DENV) Kidenga sponsored by University of Arizona with support from the Centers for Disease Control, Skoll Global Threats Fund

3 Kidenga Quick Overview Kidenga is a mobile crowd-sourcing surveillance system and educational tool for mosquito-borne diseases Public provides weekly symptom and mosquito data Experts provide up-to-date guidance and case data Public health departments can receive weekly data Launched late summer 2016 (ios + Android) Spanish version August 2017 Initial focus on Arizona, Texas, Florida Kidenga, mobile crowd-sourcing surveillance for mosquito-borne diseases.

4 Kidenga s Survey: Report Now! Weekly push notification to report on themselves and family No symptoms? Report mosquito activity Symptoms? Symptoms checklist Highest fever Onset date Travel history Medical care Testing Mosquito activity Have you noticed mosquitoes biting during the day in the past week?

5 Kidenga s Disease Tracker : Bi-directional information exchange USER GENERATED Mosquito species distribution maps CONFIRMED HEALTH DEPARTMENT DATA

6 Kidenga General Mosquito Education

7 Kidenga General Disease Education Kidenga sponsored by University of Arizona with support from the Centers for Disease Control, Skoll Global Threats Fund

8 Spanish Version! Launched August 2017

9 Public Health Benefit and Impact of Coupled Bi-directional Communication and Participatory Surveillance Empowered, aware and educated community takes more actions consistent with CDC and partner guidance Early detection and early response by public health to rapidly reduce vector populations in focal areas Reduce contacts with infectious vectors and flatten the epidemic curve Kidenga, mobile crowd-sourcing surveillance for mosquito-borne diseases.

10 Quick Stats Push notifications were set from late September 2016 to December 2016, and were reinitiated July 1st 2017 Since September 2016: 1012 downloads 586 users reported at least one week 1300 reports 33 States (Mostly Arizona, Texas, and Florida) 116 Counties Solid start but MUCH progress is needed! Fever + Rash (n = 15, 1%) Fever (n = 57, 5%) Fever + Rash + Headache (n = 7,.5%) Ideas for increasing user base welcome!!

11 Seasonal trend is shown with self-reported data consistent with Aedes seasonality in southern US Not specific to Ae. aegypti Unsure reduces over time - increased learning? - increased awareness? 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Seasonal Reporting of Day Biting Mosquitoes Sep-16 Oct-16 Nov-16 Dec-16 Jan-17 Yes Unsure No

12 Targeted Risk Information = Greater Action "Very likely"to take extra precautions 67% 55% 37% 42% 43% You were being bitten but no disease A case in your state A case in your county A case in your zipcode A case on your street

13 Development of Local Tabs Individual health departments can request a local tab This appears as one of the headers in the education section when user is physically within the area Changes when user moves to another country or city Content can be modified to fit the jurisdiction s needs Vector control numbers Updates on spraying or vector control activities Upcoming events Prediction models for area density

14 Next Step: Incorporate Mosquito Density Predictions a good prompt for me in my environment some kind of notification that there was activity checkins relating it to the weather

15 Relative Density Prediction Algorithm Simple algorithm using zipcode level precipitation and temperature data 80% accuracy in Ae. aegypti high, médium, low using historical data Monaghan et al. under review

16 Potential Visualization of Predictive Density Mapping Visualization options currently being tested by user groups

17 Other possible functions Additional functionality can be developed if support is identified Examples: Portal for uploading geo-tagged pictures of potential immature habitat Engagement of community members in setting out ovitraps and reporting results Example of tire pile habitat for Ae aegypti

18 Conclusions Kidenga could be a uniform platform to disseminate both Common messages about mosquitoes, prevention, and mosquito borne disease Tailored information for a specific jurisdiction It can provide a universal platform for community members to share information on Mosquitoes in their area Disease symptoms Travel history It can be leveraged as one of the first platforms moving predictive modeling into applied public health practice to motivate action when it is needed most Currently limited by need to share information from individual jurisdictions, access to ArboNet data at the Federal level would streamline dissemination of information

19 Kidenga Team University of Arizona Kacey Ernst Andrea Rivera Chris Schmidt Htay Hla Nirav Merchant Mona Arora Centers for Disease Control and Prevention Alba Phippard Steve Waterman Heather Joseph Project director Kathy Wirt Skoll Global Threats Fund Jennifer Olsen Adam Crawley Jessica Shao Funding for the development and marketing of Kidenga provided by: CDC and Skoll Global Threats Fund