Aedes Mosquito Early Warning System: Challenges Integrating Public Health Surveillance Data

Title: Aedes Mosquito Early Warning System: Challenges Integrating Public Health Surveillance Data

Authors: Ruby Parcells, Emma McDaniel, Anvith Anand, Ardavan Sassani, Eliza Schuh, Vineeth Chandga,  Dr. Chetan Tiwari, Dr. Suhasini Ramisetty-Mikler 

Faculty Sponsor: Dr. Raj Sunderraman

The mosquito of the Aedes genus is a known vector for several diseases, including dengue, chikungunya, yellow fever, and Zika. Early Warning Systems (EWSs) for mosquito population prediction can play a vital role in planning public health and community-driven interventions aimed at reducing the health burdens posed by arboviral disease outbreaks. Prediction models used by EWSs require the integration of several factors, including environmental characteristics, meteorological conditions, and public health surveillance. The integration of health data is particularly challenging due to the lack of a common standardized format in the collection and dissemination of public health records. Specific challenges include differences in data layouts, variables collected and disseminated, file formats, and language. 

The automation and repeatability of data integration is necessary for developing a global EWS that can be rapidly modified to incorporate data from local jurisdictions for regions across the world. In this research, we develop data pipelines using the Alteryx platform to create a library of reusable data processing workflows that can be used to clean and reformat attribute data files; reconcile differences in the geospatial definitions used across environmental, meteorological, and health datasets; and convert into standardized formats for use by the EWS prediction and visualization engine. 

This research develops a method for automating a labor-intensive and time-consuming process such as data integration. The goal is to produce a repository of data pipelines that can be pieced together and easily modified to fit the needs of future projects.