Brown, Heidi and Sedda, Luigi and Sumner, Chris and Stefanakos, Elene and Ruberto, Irene and Roach, Matthew (2021) Understanding Mosquito Surveillance Data for Analytic Efforts : A Case Study. Journal of Medical Entomology, 58 (4). pp. 1619-1625. ISSN 0022-2585
JME_2020_0308.R2_Proof_hi.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.
Download (1MB)
Abstract
Mosquito surveillance data can be used for predicting mosquito distribution and dynamics as they relate to human disease. Often these data are collected by independent agencies and aggregated to state and national level portals to characterize broad spatial and temporal dynamics. These larger repositories may also share the data for use in mosquito and/or disease prediction and forecasting models. Assumed, but not always confirmed, is consistency of data across agencies. Subtle differences in reporting may be important for development and the eventual interpretation of predictive models. Using mosquito vector surveillance data from Arizona as a case study, we found differences among agencies in how trapping practices were reported. Inconsistencies in reporting may interfere with quantitative comparisons if the user has only cursory familiarity with mosquito surveillance data. Some inconsistencies can be overcome if they are explicit in the metadata while others may yield biased estimates if they are not changed in how data are recorded. Sharing of metadata and collaboration between modelers and vector control agencies is necessary for improving the quality of the estimations. Efforts to improve sharing, displaying, and comparing vector data from multiple agencies are underway, but existing data must be used with caution.